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Preview: Human Brain Mapping

Human Brain Mapping



Wiley Online Library : Human Brain Mapping



Published: 2018-03-01T00:00:00-05:00

 



The impact of B1+ correction on MP2RAGE cortical T1 and apparent cortical thickness at 7T

2018-02-18T23:11:24.607069-05:00

Determination of cortical thickness using MRI has often been criticized due to the presence of various error sources. Specifically, anatomical MRI relying on T1 contrast may be unreliable due to spatially variable image contrast between gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Especially at ultra-high field (≥ 7T) MRI, transmit and receive B1-related image inhomogeneities can hamper correct classification of tissue types. In the current paper, we demonstrate that residual B1+ (transmit) inhomogeneities in the T1-weighted and quantitative T1 images using the MP2RAGE sequence at 7T lead to biases in cortical thickness measurements. As expected, post-hoc correction for the spatially varying B1+ profile reduced the apparent T1 values across the cortex in regions with low B1+, and slightly increased apparent T1 in regions with high B1+. As a result, improved contrast-to-noise ratio both at the GM-CSF and GM-WM boundaries can be observed leading to more accurate surface reconstructions and cortical thickness estimates. Overall, the changes in cortical thickness ranged between a 5% decrease to a 70% increase after B1+ correction, reducing the variance of cortical thickness values across the brain dramatically and increasing the comparability with normative data. More specifically, the cortical thickness estimates increased in regions characterized by a strong decrease of apparent T1 after B1+ correction in regions with low B1+ due to improved detection of the pial surface. The current results suggest that cortical thickness can be more accurately determined using MP2RAGE data at 7T if B1+ inhomogeneities are accounted for.



Latent source mining in FMRI via restricted Boltzmann machine

2018-02-18T23:11:11.683661-05:00

Blind source separation (BSS) is commonly used in functional magnetic resonance imaging (fMRI) data analysis. Recently, BSS models based on restricted Boltzmann machine (RBM), one of the building blocks of deep learning models, have been shown to improve brain network identification compared to conventional single matrix factorization models such as independent component analysis (ICA). These models, however, trained RBM on fMRI volumes, and are hence challenged by model complexity and limited training set. In this article, we propose to apply RBM to fMRI time courses instead of volumes for BSS. The proposed method not only interprets fMRI time courses explicitly to take advantages of deep learning models in latent feature learning but also substantially reduces model complexity and increases the scale of training set to improve training efficiency. Our experimental results based on Human Connectome Project (HCP) datasets demonstrated the superiority of the proposed method over ICA and the one that applied RBM to fMRI volumes in identifying task-related components, resulted in more accurate and specific representations of task-related activations. Moreover, our method separated out components representing intermixed effects between task events, which could reflect inherent interactions among functionally connected brain regions. Our study demonstrates the value of RBM in mining complex structures embedded in large-scale fMRI data and its potential as a building block for deeper models in fMRI data analysis.



Cardiorespiratory noise correction improves the ASL signal

2018-02-15T23:27:06.223024-05:00

Cardiorespiratory fluctuations such as changes in heart rate or respiration volume influence the temporal dynamics of cerebral blood flow (CBF) measurements during arterial spin labeling (ASL) fMRI. This “physiological noise” can confound estimates of resting state network activity, and it may lower the signal-to-noise ratio of ASL during task-related experiments. In this study we examined several methods for minimizing the contributions of both synchronized and non-synchronized physiological noise in ASL measures of CBF, by combining the RETROICOR approach with different linear deconvolution models. We evaluated the amount of variance in CBF that could be explained by each method during physiological rest, in both resting state and task performance conditions. To further demonstrate the feasibility of this approach, we induced low-frequency cardiorespiratory deviations via peripheral adrenergic stimulation with isoproterenol, and determined how these fluctuations influenced CBF, before and after applying noise correction. By suppressing physiological noise, we observed substantial improvements in the signal-to-noise ratio at the individual and group activation levels. Our results suggest that variations in cardiac and respiratory parameters can account for a large proportion of the variance in resting and task-based CBF, and indicate that regressing out these non-neuronal signal variations improves the intrinsically low signal-to-noise ratio of ASL. This approach may help to better identify and control physiologically driven activations in ASL resting state and task-based analyses.



Statistical inference in brain graphs using threshold-free network-based statistics

2018-02-15T23:26:31.503831-05:00

The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge-wise group-level statistical inference in brain graphs while controlling for multiple-testing associated false-positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold-free network-based statistics (TFNBS). The TFNBS combines threshold-free cluster enhancement, a method commonly used in voxel-wise statistical inference, and network-based statistic (NBS), which is frequently used for statistical analysis of brain graphs. Unlike the NBS, TFNBS generates edge-wise significance values and does not require the a priori definition of a hard cluster-defining threshold. Other test parameters, nonetheless, need to be set. We show that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false-positive rates. Our results show that the TFNBS is an adequate technique for the statistical assessment of brain graphs.



Community violence exposure correlates with smaller gray matter volume and lower IQ in urban adolescents

2018-02-15T23:25:46.002725-05:00

Adolescents’ exposure to community violence is a significant public health issue in urban settings and has been associated with poorer cognitive performance and increased risk for psychiatric illnesses, including PTSD. However, no study to date has investigated the neural correlates of community violence exposure in adolescents. Sixty-five healthy adolescents (age = 14–18 years; 36 females, 29 males) from moderate- to high-crime neighborhoods in Los Angeles reported their violence exposure, parents’ education level, and free/reduced school lunch status (socio-economic status, SES), and underwent structural neuroimaging and intelligence testing. Violence exposure negatively correlated with measures of SES, IQ, and gray matter volume. Above and beyond the effect of SES, violence exposure negatively correlated with IQ and with gray matter volume in the left inferior frontal gyrus and anterior cingulate cortex, regions involved in high-level cognitive functions and autonomic modulation, and previously shown to be reduced in PTSD and combat-exposed military populations. The current results provide first evidence that frontal brain regions involved in cognition and affect appear to be selectively affected by exposure to community violence, even in healthy nondelinquent adolescents who are not the direct victims or perpetrators of violence.



Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision

2018-02-12T23:21:15.056081-05:00

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision.



Sensorimotor network alterations in children and youth with prenatal alcohol exposure

2018-02-12T23:20:40.593627-05:00

Children with prenatal alcohol exposure (PAE) often have impaired sensorimotor function. While altered brain structure has been noted in sensorimotor areas, the functional brain alterations remain unclear. This study aims to investigate sensorimotor brain networks in children and youth with PAE using resting-state functional magnetic resonance imaging (rs-fMRI). A parcellation-based network analysis was performed to identify brain networks related to hand/lower limb and face/upper limb function in 59 children and youth with PAE and 50 typically developing controls. Participants with PAE and controls had similar organization of the hand and face areas within the primary sensorimotor cortex, but participants with PAE had altered functional connectivity (FC) between the sensorimotor regions and the rest of the brain. The sensorimotor regions in the PAE group showed less connectivity to certain hubs of the default mode network and more connectivity to areas of the salience network. Overall, our results show that despite similar patterns of organization in the sensorimotor network, subjects with PAE have increased FC between this network and other brain areas, perhaps suggesting overcompensation. These alterations in the sensorimotor network lay the foundation for future studies to evaluate interventions and treatments to improve motor function in children with PAE.



Manifold decoding for neural representations of face viewpoint and gaze direction using magnetoencephalographic data

2018-02-11T23:34:09.821672-05:00

The main challenge in decoding neural representations lies in linking neural activity to representational content or abstract concepts. The transformation from a neural-based to a low-dimensional representation may hold the key to encoding perceptual processes in the human brain. In this study, we developed a novel model by which to represent two changeable features of faces: face viewpoint and gaze direction. These features are embedded in spatiotemporal brain activity derived from magnetoencephalographic data. Our decoding results demonstrate that face viewpoint and gaze direction can be represented by manifold structures constructed from brain responses in the bilateral occipital face area and right superior temporal sulcus, respectively. Our results also show that the superposition of brain activity in the manifold space reveals the viewpoints of faces as well as directions of gazes as perceived by the subject. The proposed manifold representation model provides a novel opportunity to gain further insight into the processing of information in the human brain.



Neural and behavioral correlates of negative self-focused thought associated with depression

2018-02-09T23:25:27.771363-05:00

A central feature of major depression (MDD) is heightened negative self-focused thought (negative-SFT). Neuroscientific research has identified abnormalities in a network of brain regions in MDD, including brain areas associated with SFT such as medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). To our knowledge no studies have investigated the behavioral and neural correlates of negative-SFT using a sentence completion task in a sample of individuals with varying depression histories and severities. We test the following hypotheses: (1) negative-SFT will be associated with depression; and (2) depression and negative-SFT will be related to resting-state functional connectivity (rsFC) for brain regions implicated in SFT. Seventy-nine women with varying depression histories and severities completed a sentence completion task and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Standard seed-based voxelwise rsFC was conducted for self-network regions of interest: dorsomedial PFC (dmPFC) and pregenual ACC (pgACC). We performed linear regression analyses to examine the relationships among depression, negative-SFT, and rsFC for the dmPFC and pgACC. Greater negative-SFT was associated with depression history and severity. Greater negative-SFT predicted increased rsFC between dmPFC and pgACC seeds and dorsolateral prefrontal (dlPFC) and parietal regions; depression group was also associated with increased pgACC-dlPFC connectivity. These findings are consistent with previous literature reporting elevated negative-SFT thought in MDD. Our rs-fMRI results provide novel support linking negative-SFT with increased rsFC between self-network and frontoparietal network regions across different levels of depression. Broadly, these findings highlight a dimension of social-affective functioning that may underlie MDD and other psychiatric conditions.



Genetic relatedness of axial and radial diffusivity indices of cerebral white matter microstructure in late middle age

2018-02-09T23:25:23.948454-05:00

Two basic neuroimaging-based characterizations of white matter tracts are the magnitude of water diffusion along the principal tract orientation (axial diffusivity, AD) and water diffusion perpendicular to the principal orientation (radial diffusivity, RD). It is generally accepted that decreases in AD reflect disorganization, damage, or loss of axons, whereas increases in RD are indicative of disruptions to the myelin sheath. Previous reports have detailed the heritability of individual AD and RD measures, but have not examined the extent to which the same or different genetic or environmental factors influence these two phenotypes (except for corpus callosum). We implemented bivariate twin analyses to examine the shared and independent genetic influences on AD and RD. In the Vietnam Era Twin Study of Aging, 393 men (mean age = 61.8 years, SD = 2.6) underwent diffusion-weighted magnetic resonance imaging. We derived fractional anisotropy (FA), mean diffusivity (MD), AD, and RD estimates for 11 major bilateral white matter tracts and the mid-hemispheric corpus callosum, forceps major, and forceps minor. Separately, AD and RD were each highly heritable. In about three-quarters of the tracts, genetic correlations between AD and RD were >.50 (median = .67) and showed both unique and common variance. Genetic variance of FA and MD were predominately explained by RD over AD. These findings are important for informing genetic association studies of axonal coherence/damage and myelination/demyelination. Thus, genetic studies would benefit from examining the shared and unique contributions of AD and RD.



Inferring distinct mechanisms in the absence of subjective differences: Placebo and centrally acting analgesic underlie unique brain adaptations

2018-02-07T23:16:21.461565-05:00

Development and maintenance of chronic pain is associated with structural and functional brain reorganization. However, few studies have explored the impact of drug treatments on such changes. The extent to which long-term analgesia is related to brain adaptations and its effects on the reversibility of brain reorganization remain unclear. In a randomized placebo-controlled clinical trial, we contrasted pain relief (3-month treatment period), and anatomical (gray matter density [GMD], assessed by voxel-based morphometry) and functional connectivity (resting state fMRI nodal degree count [DC]) adaptations, in 39 knee osteoarthritis (OA) patients (22 females), randomized to duloxetine (DLX, 60 mg once daily) or placebo. Pain relief was equivalent between treatment types. However, distinct circuitry (GMD and DC) could explain pain relief in each group: up to 85% of variance for placebo analgesia and 49% of variance for DLX analgesia. No behavioral measures (collected at entry into the study) could independently explain observed analgesia. Identified circuitry were outside of nociceptive circuitry and minimally overlapped with OA-abnormal or placebo response predictive brain regions. Mediation analysis revealed that changes in GMD and DC can influence each other across remote brain regions to explain observed analgesia. Therefore, we can conclude that distinct brain mechanisms underlie DLX and placebo analgesia in OA. The results demonstrate that even in the absence of differences in subjective pain relief, pharmacological treatments can be differentiated from placebo based on objective brain biomarkers. This is a crucial step to untangling mechanisms and advancing personalized therapy approaches for chronic pain.



Functional connectivity corresponding to the tonotopic differentiation of the human auditory cortex

2018-02-07T23:16:13.639003-05:00

Recent research has demonstrated that resting-state functional connectivity (RS-FC) within the human auditory cortex (HAC) is frequency-selective, but whether RS-FC between the HAC and other brain areas is differentiated by frequency remains unclear. Three types of data were collected in this study, including resting-state functional magnetic resonance imaging (fMRI) data, task-based fMRI data using six pure tone stimuli (200, 400, 800, 1,600, 3,200, and 6,400 Hz), and structural imaging data. We first used task-based fMRI to identify frequency-selective cortical regions in the HAC. Six regions of interest (ROIs) were defined based on the responses of 50 participants to the six pure tone stimuli. Then, these ROIs were used as seeds to determine RS-FC between the HAC and other brain regions. The results showed that there was RS-FC between the HAC and brain regions that included the superior temporal gyrus, dorsolateral prefrontal cortex (DL-PFC), parietal cortex, occipital lobe, and subcortical structures. Importantly, significant differences in FC were observed among most of the brain regions that showed RS-FC with the HAC. Specifically, there was stronger RS-FC between (1) low-frequency (200 and 400 Hz) regions and brain regions including the premotor cortex, somatosensory/-association cortex, and DL-PFC; (2) intermediate-frequency (800 and 1,600 Hz) regions and brain regions including the anterior/posterior superior temporal sulcus, supramarginal gyrus, and inferior frontal cortex; (3) intermediate/low-frequency regions and vision-related regions; (4) high-frequency (3,200 and 6,400 Hz) regions and the anterior cingulate cortex or left DL-PFC. These findings demonstrate that RS-FC between the HAC and other brain areas is frequency selective.



PAGANI Toolkit: Parallel graph-theoretical analysis package for brain network big data

2018-02-07T23:15:49.659501-05:00

The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph-theoretical ANalysIs (PAGANI) Toolkit based on a hybrid central processing unit–graphics processing unit (CPU-GPU) framework with a graphical user interface to facilitate the mapping and characterization of high-resolution brain networks. Specifically, the toolkit provides flexible parameters for users to customize computations of graph metrics in brain network analyses. As an empirical example, the PAGANI Toolkit was applied to individual voxel-based brain networks with ∼200,000 nodes that were derived from a resting-state fMRI dataset of 624 healthy young adults from the Human Connectome Project. Using a personal computer, this toolbox completed all computations in ∼27 h for one subject, which is markedly less than the 118 h required with a single-thread implementation. The voxel-based functional brain networks exhibited prominent small-world characteristics and densely connected hubs, which were mainly located in the medial and lateral fronto-parietal cortices. Moreover, the female group had significantly higher modularity and nodal betweenness centrality mainly in the medial/lateral fronto-parietal and occipital cortices than the male group. Significant correlations between the intelligence quotient and nodal metrics were also observed in several frontal regions. Collectively, the PAGANI Toolkit shows high computational performance and good scalability for analyzing connectome big data and provides a friendly interface without the complicated configuration of computing environments, thereby facilitating high-resolution connectomics research in health and disease.



Spatiotemporal integration of looming visual and tactile stimuli near the face

2018-02-06T23:15:58.013856-05:00

Real-world objects approaching or passing by an observer often generate visual, auditory, and tactile signals with different onsets and durations. Prompt detection and avoidance of an impending threat depend on precise binding of looming signals across modalities. Here we constructed a multisensory apparatus to study the spatiotemporal integration of looming visual and tactile stimuli near the face. In a psychophysical experiment, subjects assessed the subjective synchrony between a looming ball and an air puff delivered to the same side of the face with a varying temporal offset. Multisensory stimuli with similar onset times were perceived as completely out of sync and assessed with the lowest subjective synchrony index (SSI). Across subjects, the SSI peaked at an offset between 800 and 1,000 ms, where the multisensory stimuli were perceived as optimally in sync. In an fMRI experiment, tactile, visual, tactile-visual out-of-sync (TVoS), and tactile-visual in-sync (TViS) stimuli were delivered to either side of the face in randomized events. Group-average statistical responses to different stimuli were compared within each surface-based region of interest (sROI) outlined on the cortical surface. Most sROIs showed a preference for contralateral stimuli and higher responses to multisensory than unisensory stimuli. In several bilateral sROIs, particularly the human MT+ complex and V6A, responses to spatially aligned multisensory stimuli (TVoS) were further enhanced when the stimuli were in-sync (TViS), as expressed by TVoS < TViS. This study demonstrates the perceptual and neural mechanisms of multisensory integration near the face, which has potential applications in the development of multisensory entertainment systems and media.



Changes in structural network are associated with cortical demyelination in early multiple sclerosis

2018-02-06T23:15:46.48267-05:00

The aim of this study was to investigate the interplay between structural connectivity and cortical demyelination in early multiple sclerosis. About 27 multiple sclerosis patients and 18 age-matched controls underwent two MRI scanning sessions. The first was done at 7T and involved acquiring quantitative T1 and T2* high-resolution maps to estimate cortical myelination. The second was done on a Connectom scanner and consisted of acquiring high angular resolution diffusion-weighted images to compute white matter structural connectivity metrics: strength, clustering and local efficiency. To further investigate the interplay between structural connectivity and cortical demyelination, patients were divided into four groups according to disease-duration: 0–1 year, 1–2 years, 2–3 years, and >3 years. ANOVA and Spearman's correlations were used to highlight relations between metrics. ANOVA detected a significant effect between disease duration and both cortical myelin (p = 2 × 10−8) and connectivity metrics (p < 10−4). We observed significant cortical myelin loss in the shorter disease-duration cohorts (0–1 year, p = .0015), and an increase in connectivity in the longer disease-duration cohort (2–3 years, strength: p = .01, local efficiency: p = .002, clustering: p = .001). Moreover, significant covariations between myelin estimation and white matter connectivity metrics were observed: Spearman's Rho correlation coefficients of 0.52 (p = .0003), 0.55 (p = .0001), and 0.53 (p = .0001) for strength, local efficiency, and clustering, respectively. An association between cortical myelin loss and changes in white matter connectivity in early multiple sclerosis was detected. These changes in network organization might be the result of compensatory mechanisms in response to the ongoing cortical diffuse damage in the early stages of multiple sclerosis.



Oscillatory dynamics in the dorsal and ventral attention networks during the reorienting of attention

2018-02-06T23:15:38.747274-05:00

The ability to reorient attention within the visual field is central to daily functioning, and numerous fMRI studies have shown that the dorsal and ventral attention networks (DAN, VAN) are critical to such processes. However, despite the instantaneous nature of attentional shifts, the dynamics of oscillatory activity serving attentional reorientation remain poorly characterized. In this study, we utilized magnetoencephalography (MEG) and a Posner task to probe the dynamics of attentional reorienting in 29 healthy adults. MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Voxel time series were then extracted from peak voxels in the functional beamformer images. These time series were used to quantify the dynamics of attentional reorienting, and to compute dynamic functional connectivity. Our results indicated strong increases in theta and decreases in alpha and beta activity across many nodes in the DAN and VAN. Interestingly, theta responses were generally stronger during trials that required attentional reorienting relative to those that did not, while alpha and beta oscillations were more dynamic, with many regions exhibiting significantly stronger responses during non-reorienting trials initially, and the opposite pattern during later processing. Finally, stronger functional connectivity was found following target presentation (575-700 ms) between bilateral superior parietal lobules during attentional reorienting. In sum, these data show that visual attention is served by multiple cortical regions within the DAN and VAN, and that attentional reorienting processes are often associated with spectrally-specific oscillations that have largely distinct spatiotemporal dynamics.



Brain structure differences between Chinese and Caucasian cohorts: A comprehensive morphometry study

2018-02-05T05:56:14.627588-05:00

Numerous behavioral observations and brain function studies have demonstrated that neurological differences exist between East Asians and Westerners. However, the extent to which these factors relate to differences in brain structure is still not clear. As the basis of brain functions, the anatomical differences in brain structure play a primary and critical role in the origination of functional and behavior differences. To investigate the underlying differences in brain structure between the two cultural/ethnic groups, we conducted a comparative study on education-matched right-handed young male adults (age = 22–29 years) from two cohorts, Han Chinese (n = 45) and Caucasians (n = 45), using high-dimensional structural magnetic resonance imaging (MRI) data. Using two well-validated imaging analysis techniques, surface-based morphometry (SBM) and voxel-based morphometry (VBM), we performed a comprehensive vertex-wise morphometric analysis of the brain structures between Chinese and Caucasian cohorts. We identified consistent significant between-group differences in cortical thickness, volume, and surface area in the frontal, temporal, parietal, occipital, and insular lobes as well as the cingulate cortices. The SBM analyses revealed that compared with Caucasians, the Chinese population showed larger cortical structures in the temporal and cingulate regions, and smaller structural measures in the frontal and parietal cortices. The VBM data of the same sample was well-aligned with the SBM findings. Our findings systematically revealed comprehensive brain structural differences between young male Chinese and Caucasians, and provided new neuroanatomical insights to the behavioral and functional distinctions in the two cultural/ethnic populations.



Musical training induces functional and structural auditory-motor network plasticity in young adults

2018-02-05T05:56:00.373262-05:00

Playing music requires a strong coupling of perception and action mediated by multimodal integration of brain regions, which can be described as network connections measured by anatomical and functional correlations between regions. However, the structural and functional connectivities within and between the auditory and sensorimotor networks after long-term musical training remain largely uninvestigated. Here, we compared the structural connectivity (SC) and resting-state functional connectivity (rs-FC) within and between the two networks in 29 novice healthy young adults before and after musical training (piano) with those of another 27 novice participants who were evaluated longitudinally but with no intervention. In addition, a correlation analysis was performed between the changes in FC or SC with practice time in the training group. As expected, participants in the training group showed increased FC within the sensorimotor network and increased FC and SC of the auditory-motor network after musical training. Interestingly, we further found that the changes in FC within the sensorimotor network and SC of the auditory-motor network were positively correlated with practice time. Our results indicate that musical training could induce enhanced local interaction and global integration between musical performance-related regions, which provides insights into the mechanism of brain plasticity in young adults.



Multiscale energy reallocation during low-frequency steady-state brain response

2018-02-01T11:05:48.10117-05:00

Traditional task-evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low-frequency steady-state brain response (lfSSBR) reflects frequency-tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra-slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain–behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency-specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks.



Frequency-dependent tACS modulation of BOLD signal during rhythmic visual stimulation

2018-02-01T11:05:36.448157-05:00

Transcranial alternating current stimulation (tACS) has emerged as a promising tool for modulating cortical oscillations. In previous electroencephalogram (EEG) studies, tACS has been found to modulate brain oscillatory activity in a frequency-specific manner. However, the spatial distribution and hemodynamic response for this modulation remains poorly understood. Functional magnetic resonance imaging (fMRI) has the advantage of measuring neuronal activity in regions not only below the tACS electrodes but also across the whole brain with high spatial resolution. Here, we measured fMRI signal while applying tACS to modulate rhythmic visual activity. During fMRI acquisition, tACS at different frequencies (4, 8, 16, and 32 Hz) was applied along with visual flicker stimulation at 8 and 16 Hz. We analyzed the blood-oxygen-level-dependent (BOLD) signal difference between tACS-ON vs tACS-OFF, and different frequency combinations (e.g., 4 Hz tACS, 8 Hz flicker vs 8 Hz tACS, 8 Hz flicker). We observed significant tACS modulation effects on BOLD responses when the tACS frequency matched the visual flicker frequency or the second harmonic frequency. The main effects were predominantly seen in regions that were activated by the visual task and targeted by the tACS current distribution. These findings bridge different scientific domains of tACS research and demonstrate that fMRI could localize the tACS effect on stimulus-induced brain rhythms, which could lead to a new approach for understanding the high-level cognitive process shaped by the ongoing oscillatory signal.



Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension

2018-01-30T07:21:12.807978-05:00

During face-to-face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued-recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand-area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low- and high-frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low- and high-frequency oscillations in predicting the integration of auditory and visual information at a semantic level.



Linking late cognitive outcome with glioma surgery location using resection cavity maps

2018-01-29T23:16:12.40541-05:00

Patients with a diffuse glioma may experience cognitive decline or improvement upon resective surgery. To examine the impact of glioma location, cognitive alteration after glioma surgery was quantified and related to voxel-based resection probability maps. A total of 59 consecutive patients (range 18–67 years of age) who had resective surgery between 2006 and 2011 for a supratentorial nonenhancing diffuse glioma (grade I–III, WHO 2007) were included in this observational cohort study. Standardized neuropsychological examination and MRI were obtained before and after surgery. Intraoperative stimulation mapping guided resections towards neurological functions (language, sensorimotor function, and visual fields). Maps of resected regions were constructed in standard space. These resection cavity maps were compared between patients with and without new cognitive deficits (z-score difference >1.5 SD between baseline and one year after resection), using a voxel-wise randomization test and calculation of false discovery rates. Brain regions significantly associated with cognitive decline were classified in standard cortical and subcortical anatomy. Cognitive improvement in any domain occurred in 10 (17%) patients, cognitive decline in any domain in 25 (42%), and decline in more than one domain in 10 (17%). The most frequently affected subdomains were attention in 10 (17%) patients and information processing speed in 9 (15%). Resection regions associated with decline in more than one domain were predominantly located in the right hemisphere. For attention decline, no specific region could be identified. For decline in information speed, several regions were found, including the frontal pole and the corpus callosum. Cognitive decline after resective surgery of diffuse glioma is prevalent, in particular, in patients with a tumor located in the right hemisphere without cognitive function mapping.



Neuromodulation with single-element transcranial focused ultrasound in human thalamus

2018-01-29T23:15:56.291958-05:00

Transcranial focused ultrasound (tFUS) has proven capable of stimulating cortical tissue in humans. tFUS confers high spatial resolutions with deep focal lengths and as such, has the potential to noninvasively modulate neural targets deep to the cortex in humans. We test the ability of single-element tFUS to noninvasively modulate unilateral thalamus in humans. Participants (N = 40) underwent either tFUS or sham neuromodulation targeted at the unilateral sensory thalamus that contains the ventro-posterior lateral (VPL) nucleus of thalamus. Somatosensory evoked potentials (SEPs) were recorded from scalp electrodes contralateral to median nerve stimulation. Activity of the unilateral sensory thalamus was indexed by the P14 SEP generated in the VPL nucleus and cortical somatosensory activity by subsequent inflexions of the SEP and through time/frequency analysis. Participants also under went tactile behavioral assessment during either the tFUS or sham condition in a separate experiment. A detailed acoustic model using computed tomography (CT) and magnetic resonance imaging (MRI) is also presented to assess the effect of individual skull morphology for single-element deep brain neuromodulation in humans. tFUS targeted at unilateral sensory thalamus inhibited the amplitude of the P14 SEP as compared to sham. There is evidence of translation of this effect to time windows of the EEG commensurate with SI and SII activities. These results were accompanied by alpha and beta power attenuation as well as time-locked gamma power inhibition. Furthermore, participants performed significantly worse than chance on a discrimination task during tFUS stimulation.



Emergence of the neural network underlying phonological processing from the prereading to the emergent reading stage: A longitudinal study

2018-01-29T23:15:38.311948-05:00

Numerous studies have shown that phonological skills are critical for successful reading acquisition. However, how the brain network supporting phonological processing evolves and how it supports the initial course of learning to read is largely unknown. Here, for the first time, we characterized the emergence of the phonological network in 28 children over three stages (prereading, beginning reading, and emergent reading) longitudinally. Across these three time points, decreases in neural activation in the left inferior parietal cortex (LIPC) were observed during an audiovisual phonological processing task, suggesting a specialization process in response to reading instruction/experience. Furthermore, using the LIPC as the seed, a functional network consisting of the left inferior frontal, left posterior occipitotemporal, and right angular gyri was identified. The connection strength in this network co-developed with the growth of phonological skills. Moreover, children with above-average gains in phonological processing showed a significant developmental increase in connection strength in this network longitudinally, while children with below-average gains in phonological processing exhibited the opposite trajectory. Finally, the connection strength between the LIPC and the left posterior occipitotemporal cortex at the prereading level significantly predicted reading performance at the emergent reading stage. Our findings highlight the importance of the early emerging phonological network for reading development, providing direct evidence for the Interactive Specialization Theory and neurodevelopmental models of reading.



Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia

2018-01-28T23:16:14.058483-05:00

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial “decoupling.” This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC).



Shared and distinct alterations of white matter tracts in remitted and nonremitted patients with schizophrenia

2018-01-28T23:16:04.000642-05:00

Patients with schizophrenia do not usually achieve remission state even after adequate antipsychotics treatment. Previous studies found significant difference in white matter integrity between patients with good outcomes and those with poor outcomes, but difference is still unclear at individual tract level. This study aimed to use a systematic approach to identify the tracts that were associated with remission state in patients with schizophrenia. We evaluated 91 patients with schizophrenia (remitted, 50; nonremitted, 41) and 50 healthy controls through diffusion spectrum imaging. White matter tract integrity was assessed through an automatic tract-specific analysis method to determine the mean generalized fractional anisotropy (GFA) values of the 76 white matter tract bundles in each participant. Analysis of covariance among the 3 groups revealed 12 tracts that were significantly different in GFA values. Post-hoc analysis showed that compared with the healthy controls, the nonremission group had reduced integrity in all 12 tracts, whereas the remission group had reduced integrity in only 4 tracts. Comparison between the remission and nonremission groups revealed 4 tracts with significant difference (i.e., the right fornix, bilateral uncinate fasciculi, and callosal fibers connecting the temporal poles) even after adjusting age, sex, education year, illness duration, and medication dose. Furthermore, all the 4 tracts were correlated with negative symptoms scores of the positive and negative syndrome scale. In conclusion, our study identified the tracts that were associated with remission state of schizophrenia. These tracts might be a potential prognostic marker for the symptomatic remission in patients with schizophrenia.



The retrosplenial cortex: A memory gateway between the cortical default mode network and the medial temporal lobe

2018-01-23T23:25:53.081864-05:00

The default mode network (DMN) involves interacting cortical areas, including the posterior cingulate cortex (PCC) and the retrosplenial cortex (RSC), and subcortical areas, including the medial temporal lobe (MTL). The degree of functional connectivity (FC) within the DMN, particularly between MTL and medial-parietal subsystems, relates to episodic memory (EM) processes. However, past resting-state studies investigating the link between posterior DMN-MTL FC and EM performance yielded inconsistent results, possibly reflecting heterogeneity in the degree of connectivity between MTL and specific cortical DMN regions. Animal work suggests that RSC has structural connections to both cortical DMN regions and MTL, and may thus serve as an intermediate layer that facilitates information transfer between cortical and subcortical DMNs. We studied 180 healthy old adults (aged 64–68 years), who underwent comprehensive assessment of EM, along with resting-state fMRI. We found greater FC between MTL and RSC than between MTL and the other cortical DMN regions (e.g., PCC), with the only significant association with EM observed for MTL-RSC FC. Mediational analysis showed that MTL-cortical DMN connectivity increased with RSC as a mediator. Further analysis using a graph-theoretical approach on DMN nodes revealed the highest betweenness centrality for RSC, confirming that a high proportion of short paths among DMN regions pass through RSC. Importantly, the degree of RSC mediation was associated with EM performance, suggesting that individuals with greater mediation have an EM advantage. These findings suggest that RSC forms a critical gateway between MTL and cortical DMN to support EM in older adults.



Magnetoencephalographic study of event-related fields and cortical oscillatory changes during cutaneous warmth processing

2018-01-23T23:25:34.617736-05:00

Thermoreception is an important cutaneous sense, which plays a role in the maintenance of our body temperature and in the detection of potential noxious heat stimulation. In this study, we investigated event-related fields (ERFs) and neural oscillatory activities, which were modulated by warmth stimulation. We developed a warmth stimulator that could elicit a warmth sensation, without pain or tactile sensation, by using a deep-penetrating 980-nm diode laser. The index finger of each participant (n = 24) was irradiated with the laser warmth stimulus, and the cortical responses were measured using magnetoencephalography (MEG). The ERFs and oscillatory responses had late latencies (∼1.3 s and 1.0–1.5 s for ERFs and oscillatory responses, respectively), which could be explained by a slow conduction velocity of warmth-specific C-fibers. Cortical sources of warmth-related ERFs were seen in the bilateral primary and secondary somatosensory cortices (SI and SII), posterior part of the anterior cingulate cortex (pACC), ipsilateral primary motor, and premotor cortex. Thus, we suggested that SI, SII, and pACC play a role in processing the warmth sensation. Time–frequency analysis demonstrated the suppression of the alpha (8–13 Hz) and beta (18–23 Hz) band power in the bilateral sensorimotor cortex. We proposed that the suppressions in alpha and beta band power are involved in the automatic response to the input of warmth stimulation and sensorimotor interactions. The delta band power (1–4 Hz) increased in the frontal, temporal, and cingulate cortices. The power changes in delta band might be related with the attentional processes during the warmth stimulation.



Socioeconomic disadvantage and altered corticostriatal circuitry in urban youth

2018-01-22T23:27:36.286214-05:00

Socioeconomic disadvantage (SED) experienced in early life is linked to a range of risk behaviors and diseases. Neuroimaging research indicates that this association is mediated by functional changes in corticostriatal reward systems that modulate goal-directed behavior, reward evaluation, and affective processing. Existing research has focused largely on adults and within-household measures as an index of SED, despite evidence that broader community-level SED (e.g., neighborhood poverty levels) has significant and sometimes distinct effects on development and health outcomes. Here, we test effects of both household- and community-level SED on resting-state functional connectivity (rsFC) of the ventral striatum (VS) in 100 racially and economically diverse children and adolescents (ages 6–17). We observed unique effects of household income and community SED on VS circuitry such that higher community SED was associated with reduced rsFC between the VS and an anterior region of the medial prefrontal cortex (mPFC), whereas lower household income was associated with increased rsFC between the VS and the cerebellum, inferior temporal lobe, and lateral prefrontal cortex. Lower VS-mPFC rsFC was also associated with higher self-reported anxiety symptomology, and rsFC mediated the link between community SED and anxiety. These results indicate unique effects of community-level SED on corticostriatal reward circuitry that can be detected in early life, which carries implications for future interventions and targeted therapies. In addition, our findings raise intriguing questions about the distinct pathways through which specific sources of SED can affect brain and emotional development.



Neural correlates of lower limbs proprioception: An fMRI study of foot position matching

2018-01-22T23:27:14.949137-05:00

Little is known about the neural correlates of lower limbs position sense, despite the impact that proprioceptive deficits have on everyday life activities, such as posture and gait control. We used fMRI to investigate in 30 healthy right-handed and right-footed subjects the regional distribution of brain activity during position matching tasks performed with the right dominant and the left nondominant foot. Along with the brain activation, we assessed the performance during both ipsilateral and contralateral matching tasks. Subjects had lower errors when matching was performed by the left nondominant foot. The fMRI analysis suggested that the significant regions responsible for position sense are in the right parietal and frontal cortex, providing a first characterization of the neural correlates of foot position matching.



Time-dependent differences in cortical measures and their associations with behavioral measures following mild traumatic brain injury

2018-01-22T23:26:52.907194-05:00

There is currently a critical need to establish an improved understanding of time-dependent differences in brain structure following mild traumatic brain injury (mTBI). We compared differences in brain structure, specifically cortical thickness (CT), cortical volume (CV), and cortical surface area (CSA) in 54 individuals who sustained a recent mTBI and 33 healthy controls (HCs). Individuals with mTBI were split into three groups, depending on their time since injury. By comparing structural measures between mTBI and HC groups, differences in CT reflected cortical thickening within several areas following 0–3 (time-point, TP1) and 3–6 months (TP2) post-mTBI. Compared with the HC group, the mTBI group at TP2 showed lower CSA within several areas. Compared with the mTBI group at TP2, the mTBI group during the most chronic stage (TP3: 6–18 months post-mTBI) showed significantly higher CSA in several areas. All the above reported differences in CT and CSA were significant at a cluster-forming p < .01 (corrected for multiple comparisons). We also found that in the mTBI group at TP2, CT within two clusters (i.e., the left rostral middle frontal gyrus (L. RMFG) and the right postcentral gyrus (R. PostCG)) was negatively correlated with basic attention abilities (L. RMFG: r = −.41, p = .05 and R. PostCG: r = −.44, p = .03). Our findings suggest that alterations in CT and associated neuropsychological assessments may be more prominent during the early stages of mTBI. However, alterations in CSA may reflect compensatory structural recovery during the chronic stages of mTBI.



The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders

2018-01-18T23:32:16.568587-05:00

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra—that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.



Spatiotemporal, metabolic, and therapeutic characterization of altered functional connectivity in major depressive disorder

2018-01-17T09:41:05.202633-05:00

Although imbalanced functional integration has been increasingly reported in major depressive disorder (MDD), there still lacks a general framework to characterize common characteristic and origin shared by the integrative disturbances. Here we examined spatial selectivity, temporal uniqueness, metabolic basis, and therapeutic response of altered functional connectivity (FC) in MDD by analyzing both cross-sectional and longitudinal multimodal functional magnetic resonance imaging data from 35 patients and 34 demographically matched healthy controls. First, based on a voxel-wise, data-driven, graph-based degree centrality approach, the bilateral anterior cingulate gyri, middle frontal gyri and superior frontal gyri, and the right parahippocampal gyrus were robustly identified to show decreased FC in MDD. Further spatiotemporal analyses revealed that these regions exhibited hub-like features and were selectively located in limbic and default mode networks spatially and, relative to other areas in the brain, exhibited unique, frequency-dependent oscillation power (stronger within 0.01–0.027 Hz and weaker within 0.027–0.073 Hz) and less dynamical variability of whole-brain FC profiles temporally. Moreover, a cross-modality fusion analysis showed that all MDD-related FC impairments were associated with reduced cerebral blood flow (CBF); however, there existed multiple regions that showed reduced CBF but had intact FC in the patients, which resulted in a decreased FC-CBF coupling and implied an earlier emergence of reduced CBF than impaired FC in MDD. Finally, the disrupted FC in MDD gradually recovered over the course of drug treatment (2 and 12 weeks). Altogether, these findings could help establish a general framework to provide mechanistic insights into integrative dysfunctions in MDD.



The relationship between thalamic GABA content and resting cortical rhythm in neuropathic pain

2018-01-17T09:40:34.314421-05:00

Recurrent thalamocortical connections are integral to the generation of brain rhythms and it is thought that the inhibitory action of the thalamic reticular nucleus is critical in setting these rhythms. Our work and others' has suggested that chronic pain that develops following nerve injury, that is, neuropathic pain, results from altered thalamocortical rhythm, although whether this dysrhythmia is associated with thalamic inhibitory function remains unknown. In this investigation, we used electroencephalography and magnetic resonance spectroscopy to investigate cortical power and thalamic GABAergic concentration in 20 patients with neuropathic pain and 20 pain-free controls. First, we found thalamocortical dysrhythmia in chronic orofacial neuropathic pain; patients displayed greater power than controls over the 4–25 Hz frequency range, most marked in the theta and low alpha bands. Furthermore, sensorimotor cortex displayed a strong positive correlation between cortical power and pain intensity. Interestingly, we found no difference in thalamic GABA concentration between pain subjects and control subjects. However, we demonstrated significant linear relationships between thalamic GABA concentration and enhanced cortical power in pain subjects but not controls. Whilst the difference in relationship between thalamic GABA concentration and resting brain rhythm between chronic pain and control subjects does not prove a cause and effect link, it is consistent with a role for thalamic inhibitory neurotransmitter release, possibly from the thalamic reticular nucleus, in altered brain rhythms in individuals with chronic neuropathic pain.



Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity

2018-01-16T23:26:45.948378-05:00

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI periods that precede hallucinations versus periods that do not. When applied to whole-brain fMRI data, state-of-the-art classification methods, such as support vector machines (SVM), yield dense solutions that are difficult to interpret. We proposed to extend the existing sparse classification methods by taking the spatial structure of brain images into account with structured sparsity using the total variation penalty. Based on this approach, we obtained reliable classifying performances associated with interpretable predictive patterns, composed of two clearly identifiable clusters in speech-related brain regions. The variation in transition-to-hallucination functional patterns not only from one patient to another but also from one occurrence to the next (e.g., also depending on the sensory modalities involved) appeared to be the major difficulty when developing effective classifiers. Consequently, second, this article aimed to characterize the variability within the prehallucination patterns using an extension of principal component analysis with spatial constraints. The principal components (PCs) and the associated basis patterns shed light on the intrinsic structures of the variability present in the dataset. Such results are promising in the scope of innovative fMRI-guided therapy for drug-resistant hallucinations, such as fMRI-based neurofeedback.



At the core of reasoning: Dissociating deductive and non-deductive load

2018-01-16T23:26:31.333914-05:00

In recent years, neuroimaging methods have been used to investigate how the human mind carries out deductive reasoning. According to some, the neural substrate of language is integral to deductive reasoning. According to others, deductive reasoning is supported by a language-independent distributed network including left frontopolar and frontomedial cortices. However, it has been suggested that activity in these frontal regions might instead reflect non-deductive factors such as working memory load and general cognitive difficulty. To address this issue, 20 healthy volunteers participated in an fMRI experiment in which they evaluated matched simple and complex deductive and non-deductive arguments in a 2 × 2 design. The contrast of complex versus simple deductive trials resulted in a pattern of activation closely matching previous work, including frontopolar and frontomedial “core” areas of deduction as well as other “cognitive support” areas in frontoparietal cortices. Conversely, the contrast of complex and simple non-deductive trials resulted in a pattern of activation that does not include any of the aforementioned “core” areas. Direct comparison of the load effect across deductive and non-deductive trials further supports the view that activity in the regions previously interpreted as “core” to deductive reasoning cannot merely reflect non-deductive load, but instead might reflect processes specific to the deductive calculus. Finally, consistent with previous reports, the classical language areas in left inferior frontal gyrus and posterior temporal cortex do not appear to participate in deductive inference beyond their role in encoding stimuli presented in linguistic format.



Test–retest reliability and longitudinal analysis of automated hippocampal subregion volumes in healthy ageing and Alzheimer's disease populations

2018-01-16T23:25:28.560632-05:00

The hippocampal formation is a complex brain structure that is important in cognitive processes such as memory, mood, reward processing and other executive functions. Histological and neuroimaging studies have implicated the hippocampal region in neuropsychiatric disorders as well as in neurodegenerative diseases. This highly plastic limbic region is made up of several subregions that are believed to have different functional roles. Therefore, there is a growing interest in imaging the subregions of the hippocampal formation rather than modelling the hippocampus as a homogenous structure, driving the development of new automated analysis tools. Consequently, there is a pressing need to understand the stability of the measures derived from these new techniques. In this study, an automated hippocampal subregion segmentation pipeline, released as a developmental version of Freesurfer (v6.0), was applied to T1-weighted magnetic resonance imaging (MRI) scans of 22 healthy older participants, scanned on 3 separate occasions and a separate longitudinal dataset of 40 Alzheimer's disease (AD) patients. Test–retest reliability of hippocampal subregion volumes was assessed using the intra-class correlation coefficient (ICC), percentage volume difference and percentage volume overlap (Dice). Sensitivity of the regional estimates to longitudinal change was estimated using linear mixed effects (LME) modelling. The results show that out of the 24 hippocampal subregions, 20 had ICC scores of 0.9 or higher in both samples; these regions include the molecular layer, granule cell layer of the dentate gyrus, CA1, CA3 and the subiculum (ICC > 0.9), whilst the hippocampal fissure and fimbria had lower ICC scores (0.73–0.88). Furthermore, LME analysis of the independent AD dataset demonstrated sensitivity to group and individual differences in the rate of volume change over time in several hippocampal subregions (CA1, molecular layer, CA3, hippocampal tail, fissure and presubiculum). These results indicate that this automated segmentation method provides a robust method with which to measure hippocampal subregions, and may be useful in tracking disease progression and measuring the effects of pharmacological intervention.



Response selection codes in neurophysiological data predict conjoint effects of controlled and automatic processes during response inhibition

2018-01-15T05:14:49.511216-05:00

The inhibition of prepotent responses is a requirement for goal-directed behavior and several factors determine corresponding successful response inhibition processes. One factor relates to the degree of automaticity of pre-potent response tendencies and another factor relates to the degree of cognitive control that is exerted during response inhibition. However, both factors can conjointly modulate inhibitory control. Cognitive theoretical concepts suggest that codings of stimulus-response translations may underlie such conjoint effects. Yet, it is unclear in how far such specific codes, as assumed in cognitive psychological concepts, are evident in neurophysiological processes and whether there are specific functional neuroanatomical structures associated with the processing of such codes. Applying a temporal decomposition method of EEG data in combination with source localization methods we show that there are different, intermingled codes (i.e., “stimulus codes” and “response selection codes”) at the neurophysiological level during conjoint effects of “automatic” and “controlled” processes in response inhibition. Importantly, only “response selection codes” predict behavioral performance, and are subject to conjoint modulations by “automatic” and “controlled” processes. These modulations are associated with inferior and superior parietal areas (BA40/BA7), possibly reflecting an updating of internal representations when information is complex and probably difficult to categorize, but essential for behavioral control. Codes proposed by cognitive, psychological concepts seem to have a neurophysiological analogue that fits into current views on functions of inferior and superior parietal regions.



The retinal ganglion cell layer predicts normal-appearing white matter tract integrity in multiple sclerosis: A combined diffusion tensor imaging and optical coherence tomography approach

2018-01-15T05:14:28.08685-05:00

We investigated the relationship between retinal layers and normal-appearing white matter (WM) integrity in the brain of patients with relapsing-remitting multiple sclerosis (MS), using a combined diffusion tensor imaging and high resolution optical coherence tomography approach. Fifty patients and 62 controls were recruited. The patients were divided into two groups according to presence (n = 18) or absence (n = 32) of optic neuritis. Diffusion tensor data were analyzed with a voxel-wise whole brain analysis of diffusion metrics in WM with tract-based spatial statistics. Thickness measurements were obtained for each individual retinal layer. Partial correlation and multivariate regression analyses were performed, assessing the association between individual retinal layers and diffusion metrics across all groups. Region-based analysis was performed, by focusing on tracts associated with the visual system. Receiver operating characteristic (ROC) curves were computed to compare the biomarker potential for the diagnosis of MS, using the thickness of each retinal layer and diffusion metrics. In patients without optic neuritis, both ganglion cell layer (GCL) and inner plexiform layer thickness correlated with the diffusion metrics within and outside the visual system. GCL thickness was a significant predictor of diffusion metrics in the whole WM skeleton, unlike other layers. No association was observed for either controls or patients with a history of optic neuritis. ROC analysis showed that the biomarker potential for the diagnosis of MS based on the GCL was high when compared to other layers. We conclude that GCL integrity is a predictor of whole-brain WM disruption in MS patients without optic neuritis.



Controlling the Temporal Structure of Brain Oscillations by Focused Attention Meditation

2018-01-13T07:36:23.488227-05:00

Our focus of attention naturally fluctuates between different sources of information even when we desire to focus on a single object. Focused attention (FA) meditation is associated with greater control over this process, yet the neuronal mechanisms underlying this ability are not entirely understood. Here, we hypothesize that the capacity of attention to transiently focus and swiftly change relates to the critical dynamics emerging when neuronal systems balance at a point of instability between order and disorder. In FA meditation, however, the ability to stay focused is trained, which may be associated with a more homogeneous brain state. To test this hypothesis, we applied analytical tools from criticality theory to EEG in meditation practitioners and meditation-naïve participants from two independent labs. We show that in practitioners—but not in controls—FA meditation strongly suppressed long-range temporal correlations (LRTC) of neuronal oscillations relative to eyes-closed rest with remarkable consistency across frequency bands and scalp locations. The ability to reduce LRTC during meditation increased after one year of additional training and was associated with the subjective experience of fully engaging one's attentional resources, also known as absorption. Sustained practice also affected normal waking brain dynamics as reflected in increased LRTC during an eyes-closed rest state, indicating that brain dynamics are altered beyond the meditative state. Taken together, our findings suggest that the framework of critical brain dynamics is promising for understanding neuronal mechanisms of meditative states and, specifically, we have identified a clear electrophysiological correlate of the FA meditation state.



Regional hippocampal vulnerability in early multiple sclerosis: Dynamic pathological spreading from dentate gyrus to CA1

2018-01-13T07:36:09.826437-05:00

Background Whether hippocampal subfields are differentially vulnerable at the earliest stages of multiple sclerosis (MS) and how this impacts memory performance is a current topic of debate. Method We prospectively included 56 persons with clinically isolated syndrome (CIS) suggestive of MS in a 1-year longitudinal study, together with 55 matched healthy controls at baseline. Participants were tested for memory performance and scanned with 3 T MRI to assess the volume of 5 distinct hippocampal subfields using automatic segmentation techniques. Results At baseline, CA4/dentate gyrus was the only hippocampal subfield with a volume significantly smaller than controls (p < .01). After one year, CA4/dentate gyrus atrophy worsened (−6.4%, p < .0001) and significant CA1 atrophy appeared (both in the stratum-pyramidale and the stratum radiatum-lacunosum-moleculare, −5.6%, p < .001 and −6.2%, p < .01, respectively). CA4/dentate gyrus volume at baseline predicted CA1 volume one year after CIS (R2 = 0.44 to 0.47, p < .001, with age, T2 lesion-load, and global brain atrophy as covariates). The volume of CA4/dentate gyrus at baseline was associated with MS diagnosis during follow-up, independently of T2-lesion load and demographic variables (p < .05). Whereas CA4/dentate gyrus volume was not correlated with memory scores at baseline, CA1 atrophy was an independent correlate of episodic verbal memory performance one year after CIS (ß = 0.87, p < .05). Conclusion The hippocampal degenerative process spread from dentate gyrus to CA1 at the earliest stage of MS. This dynamic vulnerability is associated with MS diagnosis after CIS and will ultimately impact hippocampal-dependent memory performance.



ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data

2018-01-13T07:36:02.70969-05:00

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.



Exploring the advantages of multiband fMRI with simultaneous EEG to investigate coupling between gamma frequency neural activity and the BOLD response in humans

2018-01-13T07:35:39.074226-05:00

We established an optimal combination of EEG recording during sparse multiband (MB) fMRI that preserves high-resolution, whole-brain fMRI coverage while enabling broad-band EEG recordings which are uncorrupted by MRI gradient artefacts (GAs). We first determined the safety of simultaneous EEG recording during MB fMRI. Application of MB factor = 4 produced <1°C peak heating of electrode/hardware during 20 min of GE-EPI data acquisition. However, higher SAR sequences require specific safety testing, with greater heating observed using PCASL with MB factor = 4. Heating was greatest in the electrocardiogram channel, likely due to it possessing longest lead length. We investigated the effect of MB factor on the temporal signal-to-noise ratio for a range of GE-EPI sequences (varying MB factor and temporal interval between slice acquisitions). We found that, for our experimental purpose, the optimal acquisition was achieved with MB factor = 3, 3mm isotropic voxels, and 33 slices providing whole head coverage. This sequence afforded a 2.25 s duration quiet period (without GAs) in every 3 s TR. Using this sequence, we demonstrated the ability to record gamma frequency (55–80 Hz) EEG oscillations, in response to right index finger abduction, that are usually obscured by GAs during continuous fMRI data acquisition. In this novel application of EEG-MB fMRI to a motor task, we observed a positive correlation between gamma and BOLD responses in bilateral motor regions. These findings support and extend previous work regarding coupling between neural and hemodynamic measures of brain activity in humans and showcase the utility of EEG-MB fMRI for future investigations.



Neuroanatomical correlates of grit: Growth mindset mediates the association between gray matter structure and trait grit in late adolescence

2018-01-13T07:35:22.98458-05:00

There is a long-standing interest in exploring the factors related to student achievement. As a newly explored personality trait, grit is defined as a person's tendency to pursue long-term goals with continual perseverance and passion, and grit plays a critical role in student achievement. Increasing evidence has shown that growth mindset, the belief that one's basic abilities are malleable and can be developed through effort, is a potential factor for cultivating grit. However, less is known about the association between grit and the brain and the role of growth mindset in this association. Here, we utilized voxel-based morphometry to examine the neuroanatomical correlates of grit in 231 healthy adolescent students by performing structural magnetic resonance imaging. The whole-brain regression analyses revealed that the regional gray matter volume (rGMV) in the left dorsolateral prefrontal cortex (DLPFC) negatively predicted grit. In contrast, the rGMV in the right putamen positively predicted grit. Furthermore, mediating analyses suggested that growth mindset served as a mediator in the association between left DLPFC volume and grit. Our results persisted even after controlling for the influences of self-control and delayed gratification. Overall, our study presents novel evidence for the neuroanatomical basis of grit and highlights that growth mindset might play an essential role in cultivating a student's grit level.



Differences in white matter structure and cortical thickness between patients with traumatic and idiopathic chronic neck pain: Associations with cognition and pain modulation?

2018-01-11T23:30:41.687996-05:00

Brain alterations are hypothesized to be present in patients with chronic whiplash-associated disorders (CWAD). The aim of this case–control study was to examine alterations in cortical thickness and white matter (WM) structure, and the presence of brain microhemorrhages in a patient group encountering chronic neck pain of traumatic origin (i.e., CWAD) when compared with a patient group characterized by nontraumatic chronic neck pain [i.e., chronic idiopathic neck pain (CINP)], and healthy controls. Furthermore, we aimed to investigate associations between brain structure on one hand and cognitive performance and central sensitization (CS) on the other hand. T1-weighted, diffusion-weighted and T2*-weighted magnetic resonance images of the brain were acquired in 105 women (31 controls, 37 CINP, 37 CWAD) to investigate regional cortical thickness, WM structure, and microhemorrhages, respectively. Next, cognitive performance, and CS encompassing distant hyperalgesia and conditioned pain modulation (CPM) efficacy were examined. Cortical thinning in the left precuneus was revealed in CWAD compared with CINP patients. Also, decreased fractional anisotropy, together with increased values of mean diffusivity and radial diffusivity could be observed in the left cingulum hippocampus and tapetum in CWAD compared with CINP, and in the left tapetum in CWAD patients compared with controls. Moreover, the extent of WM structural deficits in the left tapetum coincided with decreased CPM efficacy in the CWAD group. This yields evidence for associations between decreased endogenous pain inhibition, and the degree of regional WM deficits in CWAD. Our results emphasize the role of structural brain alterations in women with CWAD compared with CINP.



Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation

2018-01-10T23:30:31.785792-05:00

Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. However, with respect to performance, well-controlled functional imaging studies on MI training are sparse. We investigated changes in fMRI representation going along with performance changes of a finger sequence (error and velocity) after MI training in 48 healthy young volunteers. Before training, we tested the vividness of kinesthetic and visual imagery. During tests, participants were instructed to move or to imagine moving the fingers of the right hand in a specific order. During MI training, participants repeatedly imagined the sequence for 15 min. Imaging analysis was performed using a full-factorial design to assess brain changes due to imagery training. We also used regression analyses to identify those who profited from training (performance outcome and gain) with initial imagery scores (vividness) and fMRI activation magnitude during MI at pre-test (MIpre). After training, error rate decreased and velocity increased. We combined both parameters into a common performance index. FMRI activation in the left inferior parietal lobe (IPL) was associated with MI and increased over time. In addition, fMRI activation in the right IPL during MIpre was associated with high initial kinesthetic vividness. High kinesthetic imagery vividness predicted a high performance after training. In contrast, occipital activation, associated with visual imagery strategies, showed a negative predictive value for performance. Our data echo the importance of high kinesthetic vividness for MI training outcome and consider IPL as a key area during MI and through MI training.



Subclinical depressive symptoms during late midlife and structural brain alterations: A longitudinal study of Danish men born in 1953

2018-01-10T23:28:36.706913-05:00

We explored whether depressive symptoms measured three times during midlife were associated with structural brain alterations quantified using magnetic resonance imaging measurements of volume, cortical thickness, and intensity texture. In 192 men born in 1953 with depressive symptoms measured at age 51, 56, and 59 years, magnetic resonance imaging was performed at age 59. All data processing was performed using the Freesurfer software package except for the texture-scores that were computed using in-house software. Structural brain alterations and associations between depressive symptoms and brain structure outcomes were tested using Pearson's correlation, t test, and linear regression. Depressive symptoms at age 51 showed clear inverse correlations with total gray matter, pallidum, and hippocampal volume with the strongest estimate for hippocampal volume (r = −.22, p < .01). After exclusion of men (n = 3) with scores in the range of clinical depression the inverse correlation between depressive symptoms and hippocampal volume became insignificant (r = −13, p = .08). Depressive symptoms at age 59 correlated positively with hippocampal and amygdala texture-potential early markers of atrophy. Inverse relations with total gray matter and pallidum volumes lost significance when the analysis was adjusted for intracranial volume. In men, depressive symptoms at age 51 were associated with a reduced volume of the hippocampus at age 59 independent of later symptoms. Amygdala and hippocampal textures might be the early markers for brain alterations associated with depression in midlife.



Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity

2018-01-10T23:28:34.133867-05:00

Prevalence of certain forms of psychopathology, such as autism and depression, differs between genders and understanding gender differences of the neurotypical brain may provide insights into risk and protective factors. In recent research, resting state functional magnetic resonance imaging (rfMRI) is widely used to map the inherent functional networks of the brain. Although previous studies have reported gender differences in rfMRI, the robustness of gender differences is not well characterized. In this study, we use a large data set to test whether rfMRI functional connectivity (FC) can be used to predict gender and identify FC features that are most predictive of gender. We utilized rfMRI data from 820 healthy controls from the Human Connectome Project. By applying a predefined functional template and partial least squares regression modeling, we achieved a gender prediction accuracy of 87% when multi-run rfMRI was used. Permutation tests confirmed that gender prediction was reliable ( p<.001). Effects of motion, age, handedness, blood pressure, weight, and brain volume on gender prediction are discussed. Further, we found that FC features within the default mode (DMN), fronto-parietal and sensorimotor networks contributed most to gender prediction. In the DMN, right fusiform gyrus and right ventromedial prefrontal cortex were important contributors. The above regions have been previously implicated in aspects of social functioning and this suggests potential gender differences in social cognition mediated by the DMN. Our findings demonstrate that gender can be reliably predicted using rfMRI data and highlight the importance of controlling for gender in brain imaging studies.



Abnormal fronto-striatal activation as a marker of threshold and subthreshold Bulimia Nervosa

2018-01-10T23:28:25.928161-05:00

This study aimed to determine whether functional disturbances in fronto-striatal control circuits characterize adolescents with Bulimia Nervosa (BN) spectrum eating disorders regardless of clinical severity. FMRI was used to assess conflict-related brain activations during performance of a Simon task in two samples of adolescents with BN symptoms compared with healthy adolescents. The BN samples differed in the severity of their clinical presentation, illness duration and age. Multi-voxel pattern analyses (MVPAs) based on machine learning were used to determine whether patterns of fronto-striatal activation characterized adolescents with BN spectrum disorders regardless of clinical severity, and whether accurate classification of less symptomatic adolescents (subthreshold BN; SBN) could be achieved based on patterns of activation in adolescents who met DSM5 criteria for BN. MVPA classification analyses revealed that both BN and SBN adolescents could be accurately discriminated from healthy adolescents based on fronto-striatal activation. Notably, the patterns detected in more severely ill BN compared with healthy adolescents accurately discriminated less symptomatic SBN from healthy adolescents. Deficient activation of fronto-striatal circuits can characterize BN early in its course, when clinical presentations are less severe, perhaps pointing to circuit-based disturbances as useful biomarker or risk factor for the disorder, and a tool for understanding its developmental trajectory, as well as the development of early interventions.



A window-less approach for capturing time-varying connectivity in fMRI data reveals the presence of states with variable rates of change

2018-01-09T09:50:03.443584-05:00

Functional connectivity during the resting state has been shown to change over time (i.e., has a dynamic connectivity). However, resting-state fluctuations, in contrast to task-based experiments, are not initiated by an external stimulus. Consequently, a more complicated method needs to be designed to measure the dynamic connectivity. Previous approaches have been based on assumptions regarding the nature of the underlying dynamic connectivity to compensate for this knowledge gap. The most common assumption is what we refer to as locality assumption. Under a locality assumption, a single connectivity state can be estimated from data that are close in time. This assumption is so natural that it has been either explicitly or implicitly embedded in many current approaches to capture dynamic connectivity. However, an important drawback of methods using this assumption is they are unable to capture dynamic changes in connectivity beyond the embedded rate while, there has been no evidence that the rate of change in brain connectivity matches the rates enforced by this assumption. In this study, we propose an approach that enables us to capture functional connectivity with arbitrary rates of change, varying from very slow to the theoretically maximum possible rate of change, which is only imposed by the sampling rate of the imaging device. This method allows us to observe unique patterns of connectivity that were not observable with previous approaches. As we explain further, these patterns are also significantly correlated to the age and gender of study subjects, which suggests they are also neurobiologically related.



Four-way multimodal fusion of 7 T imaging data using an mCCA+jICA model in first-episode schizophrenia

2018-01-09T09:49:53.536371-05:00

Acquisition of multimodal brain imaging data for the same subject has become more common leading to a growing interest in determining the intermodal relationships between imaging modalities to further elucidate the pathophysiology of schizophrenia. Multimodal data have previously been individually analyzed and subsequently integrated; however, these analysis techniques lack the ability to examine true modality inter-relationships. The utilization of a multiset canonical correlation and joint independent component analysis (mCCA + jICA) model for data fusion allows shared or distinct abnormalities between modalities to be examined. In this study, first-episode schizophrenia patients (nSZ=19) and matched controls (nHC=21) completed a resting-state functional magnetic resonance imaging (fMRI) scan at 7 T. Grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and amplitude of low frequency fluctuation (ALFF) maps were used as features in a mCCA + jICA model. Results of the mCCA + jICA model indicated three joint group-discriminating components (GM-CSF, WM-ALFF, GM-ALFF) and two modality-unique group-discriminating components (GM, WM). The joint component findings are highlighted by GM basal ganglia, somatosensory, parietal lobe, and thalamus abnormalities associated with ventricular CSF volume; WM occipital and frontal lobe abnormalities associated with temporal lobe function; and GM frontal, temporal, parietal, and occipital lobe abnormalities associated with caudate function. These results support and extend major findings throughout the literature using independent single modality analyses. The multimodal fusion of 7 T data in this study provides a more comprehensive illustration of the relationships between underlying neuronal abnormalities associated with schizophrenia than examination of imaging data independently.



Default mode network modifications in Fabry disease: A resting-state fMRI study with structural correlations

2018-01-09T03:05:28.222706-05:00

Aim of the study was to evaluate the presence of Default Mode Network (DMN) modifications in Fabry Disease (FD), and their possible correlations with structural alterations and neuropsychological scores. Thirty-two FD patients with a genetically confirmed diagnosis of classical FD (12 males, mean age 43.3 ± 12.2) were enrolled, along with 35 healthy controls (HC) of comparable age and sex (14 males, mean age 42.1 ± 14.5). Resting-State fMRI data were analyzed using a seed-based approach, with six different seeds sampling the main hubs of the DMN. Structural modifications were assessed by means of Voxel-Based Morphometry (VBM) and Tract-Based Spatial Statistics analyses. Between-group differences and correlations with neuropsychological variables were probed voxelwise over the whole brain. Possible correlations between FC modifications and global measures of microstructural alteration were also tested in FD patients with a partial correlation analysis. In the FD group, clusters of increased functional connectivity involving both supratentorial and infratentorial regions emerged, partially correlated to the widespread white matter (WM) damage found in these patients. No gray matter volume differences were found at VBM between the two groups. The connectivity between right inferior frontal gyrus and precuneus was significantly correlated with the Corsi block-tapping test results (p = .0001). Widespread DMN changes are present in FD patients that correlate with WM alterations and cognitive performance. Our results confirm the current view of a cerebral involvement in FD patients not simply associated to major cerebrovascular events, but also related to significant and diffuse microstructural and functional changes.



Differentially categorized structural brain hubs are involved in different microstructural, functional, and cognitive characteristics and contribute to individual identification

2018-01-04T07:45:45.783028-05:00

Very little is known regarding whether structural hubs of human brain networks that enable efficient information communication may be classified into different categories. Using three multimodal neuroimaging data sets, we construct individual structural brain networks and further identify hub regions based on eight widely used graph-nodal metrics, followed by comprehensive characteristics and reproducibility analyses. We show the three categories of structural hubs in the brain network, namely, aggregated, distributed, and connector hubs. Spatially, these distinct categories of hubs are primarily located in the default-mode system and additionally in the visual and limbic systems for aggregated hubs, in the frontoparietal system for distributed hubs, and in the sensorimotor and ventral attention systems for connector hubs. These categorized hubs exhibit various distinct characteristics to support their differentiated roles, involving microstructural organization, wiring costs, topological vulnerability, functional modular integration, and cognitive flexibility; moreover, these characteristics are better in the hubs than nonhubs. Finally, all three categories of hubs display high across-session spatial similarities and act as structural fingerprints with high predictive rates (100%, 100%, and 84.2%) for individual identification. Collectively, we highlight three categories of brain hubs with differential microstructural, functional and, cognitive associations, which shed light on topological mechanisms of the human connectome.



Motivation but not valence modulates neuroticism-dependent cingulate cortex and insula activity

2018-01-04T07:45:33.707845-05:00

Neuroticism has been found to specifically modulate amygdala activations during differential processing of valence and motivation while other brain networks yet are unexplored for associated effects. The main purpose of this study was to investigate whether neural mechanisms processing valence or motivation are prone to neuroticism in the salience network (SN), a network that is anchored in the anterior cingulate cortex (ACC) and the anterior insula. This study used functional magnetic resonance imaging (fMRI) and an approach/avoid emotional pictures task to investigate brain activations modulated by pictures’ valence or motivational status between high and low neurotic individuals. We found that neuroticism-dependent SN and the parahippocampal-fusiform area activations were modulated by motivation but not valence. Valence in contrast interacted with neuroticism in the lateral orbitofrontal cortex. We suggested that neuroticism modulated valence and motivation processing, however, under the influence of the two distinct networks. Neuroticism modulated the motivation through the SN while it modulated the valence through the orbitofrontal networks.



The role of the dorsal anterior insula in sexual risk: Evidence from an erotic Go/NoGo task and real-world risk-taking

2018-01-03T08:30:06.501188-05:00

The insula plays an important role in response inhibition. Most relevant here, it has been proposed that the dorsal anterior insular cortex (dAIC) plays a central role in a salience network that is responsible for switching between the default mode network and the executive control network. However, the insula's role in sexually motivated response inhibition has not yet been studied. In this study, eighty-five 18- to 30-year-old sexually active men who have sex with men (MSM) performed an erotic Go/NoGo task while in an MRI scanner. Participants' real-world sexual risk-taking (frequency of condomless anal intercourse over the past 90 days) was then correlated with their neural activity during the task. We found greater activity in bilateral anterior insular cortex (both dorsal and ventral) on contrasts with stronger motivational information (attractive naked male pictures versus pictures of clothed, middle-aged females) and on contrasts requiring greater response inhibition (NoGo versus Go). We also found that activity in the right dAIC was negatively correlated with participants' real-world sexual risk-taking. Our results confirmed the involvement of the insular cortex in motivated response inhibition. Especially, the decreased right dAIC activity may reduce the likelihood that the executive control network will come online when individuals are faced with situations requiring inhibitory control and thus lead them to make more risky choices.



Neural correlates of subjective CS/UCS association in appetitive conditioning

2018-01-03T06:46:26.231775-05:00

Explicit knowledge of conditioned stimulus (CS)/unconditioned stimulus (UCS) associations is proposed as important factor in classical conditioning. However, while previous studies have focused on its roles in fear conditioning, it has been neglected in the context of appetitive conditioning. The present functional magnetic resonance study aimed to investigate neural activation and functional connectivity linked to subjective CS/UCS association in appetitive conditioning. In total, 85 subjects participated in an appetitive acquisition procedure in which a neutral stimulus (CS+) was paired with a monetary reward, while another neutral stimulus (CS-) was never paired with the reward. Directly afterwards, subjective CS/UCS association was assessed by measuring the extent to which the CS+ was thought to be associated with the UCS compared to the CS-. Close relationships were established between subjective CS/UCS association and activations in the primary visual cortex (V1) during the early phase of conditioning and in the striatum during the late conditioning phase. In addition, we observed inverse relationships between subjective CS/UCS association and both V1/ventromedial prefrontal cortex (vmPFC) and striatal/vmPFC connectivity. The results suggest the involvement of decoupling vmPFC connectivity in reward learning in general and the roles of attentional processes in the formation of the subjective CS/UCS association during the early phase and reward prediction during the late phase of appetitive conditioning.



EEG/MEG source imaging using fMRI informed time-variant constraints

2018-01-02T08:51:37.044785-05:00

Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) or magnetoencephalography (MEG) is able to provide high spatiotemporal resolution mapping of brain activity. However, the accuracy of fMRI-constrained EEG/MEG source imaging may be degraded by potential spatial mismatches between the locations of fMRI activation and electrical source activities. To address this problem, we propose a novel fMRI informed time-variant constraint (FITC) method. The weights in FITC are determined by combining the fMRI activities and electrical source activities in a time-variant manner to reduce the impact of the fMRI extra sources. The fMRI weights are modified using cross-talk matrix and normalized partial area under the curve to reduce the impact of fMRI missing sources. Monte Carlo simulations were performed to compare the source estimates produced by L2-minimum norm estimation (MNE), fMRI-weighted minimum norm estimation (fMNE), FITC, and depth-weighted FITC (wFITC) algorithms with various spatial mismatch conditions. Localization error and temporal correlation were calculated to compare the four algorithms under different conditions. The simulation results indicated that the FITC and wFITC methods were more robust than the MNE and fMNE algorithms. Moreover, FITC and wFITC were significantly better than fMNE under the fMRI missing sources condition. A human visual-stimulus EEG, MEG, and fMRI test was performed, and the experimental data revealed that FITC and wFITC displayed more focal areas than fMNE and MNE. In conclusion, the proposed FITC method is able to better resolve the spatial mismatch problems encountered in fMRI-constrained EEG/MEG source imaging.



Neural predictors of sensorimotor adaptation rate and savings

2017-12-23T04:35:40.908416-05:00

In this study, we investigate whether individual variability in the rate of visuomotor adaptation and multiday savings is associated with differences in regional gray matter volume and resting-state functional connectivity. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. Functional connectivity strength between sensorimotor, dorsal cingulate, and temporoparietal regions of the brain was found to predict the rate of learning during the early phase of the adaptation task. In contrast, default mode network connectivity strength was found to predict both the rate of learning during the late adaptation phase and savings. As for structural predictors, greater gray matter volume in temporoparietal and occipital regions predicted faster early learning, whereas greater gray matter volume in superior posterior regions of the cerebellum predicted faster late learning. These findings suggest that the offline neural predictors of early adaptation may facilitate the cognitive aspects of sensorimotor adaptation, supported by the involvement of temporoparietal and cingulate networks. The offline neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations.



Metabolic correlates of cognitive function in children with unilateral Sturge–Weber syndrome: Evidence for regional functional reorganization and crowding

2017-12-23T04:35:28.724389-05:00

To evaluate metabolic changes in the ipsi- and contralateral hemisphere in children showing a cognitive profile consistent with early reorganization of cognitive function, we evaluated the regional glucose uptake, interhemispheric metabolic connectivity, and cognitive function in children with unilateral SWS. Interictal 2-deoxy-2[18F]fluoro-D-glucose (FDG)-PET scans of 27 children with unilateral SWS and mild epilepsy and 27 age-matched control (non-SWS children with epilepsy and normal FDG-PET) were compared using statistical parametric mapping (SPM). Regional FDG-PET abnormalities calculated as SPM(t) scores in the SWS group were correlated with cognitive function (IQ) in left- and right-hemispheric subgroups. Interhemispheric metabolic connectivity between homotopic cortical regions was also calculated. Verbal IQ was substantially (≥10 points difference) higher than non-verbal IQ in 61% of the right- and 71% of the left-hemispheric SWS group. FDG SPM(t) scores in the affected hemisphere showed strong positive correlations with IQ in the left-hemispheric, but not in right-hemispheric SWS group in several frontal, parietal, and temporal cortical regions. Significant positive interhemispheric metabolic connectivity, present in controls, was diminished in the SWS group. In addition, the left-hemispheric SWS group showed inverse metabolic interhemispheric correlations in specific parietal, temporal, and occipital regions. FDG SPM(t) scores in the same regions of the right (unaffected) hemisphere showed inverse correlations with IQ. These findings suggest that left-hemispheric lesions in SWS often result in early reorganization of verbal functions while interfering with (“crowding”) their non-verbal cognitive abilities. These cognitive changes are associated with specific metabolic abnormalities in the contralateral hemisphere not directly affected by SWS.



Networks of myelin covariance

2017-12-21T22:07:15.317638-05:00

Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, ). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin-Nets). The Myelin-Nets were built from quantitative Magnetization Transfer data—an in-vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin-Nets. We therefore selected two age groups: Young-Age (20–31 years old) and Old-Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin-Nets aging trajectory study. We found that the topological organization of the Myelin-Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin-Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging.



Cover Image

2018-02-09T08:53:09.429604-05:00

COVER ILLUSTRATION: Trauma such as motor vehicle accidents resulting in post-traumatic stress disorder (PTSD) has been linked to compromised integrity of the uncinate fasciculus (UF) white matter tract. The UF which provides connection between the amygdala, and anterior cingulate cortex. Significant negative correlations have been found between PTSD symptoms and UF fractional anisotropy values of PTSD subjects. For details, see O'Doherty et al. White matter integrity alterations in post-traumatic stress disorder in this issue.



Editorial board - TOC

2018-02-09T08:53:01.366738-05:00




SIENA-XL for improving the assessment of gray and white matter volume changes on brain MRI

2017-12-08T23:17:07.976794-05:00

In this article, SIENA-XL, a new segmentation-based longitudinal pipeline is introduced, for: (i) increasing the precision of longitudinal volume change estimation for white (WM) and gray (GM) matter separately, compared with cross-sectional segmentation methods such as SIENAX; and (ii) avoiding potential biases in registration-based methods when Jacobians are used, with a smoothing extent larger than spatial scale between tissue-interfaces, which is where atrophy usually occurs. SIENA-XL implements a new brain extraction procedure and a multi-time-point intensity equalization step before performing the final segmentation that also includes separate segmentation of deep GM structures by using FMRIB's Integrated Registration and Segmentation Tool. The detection of GM and WM volume changes with SIENA-XL was evaluated using different healthy control (HC) and multiple sclerosis (MS) MRI datasets and compared with the traditional SIENAX and two Jacobian-based approaches, SPM12 and SIENAX-JI (a version of SIENAX including Jacobian integration - JI). In scan-rescan data from HCs, SIENA-XL showed: (i) a significant decrease in error, of 50–70% when compared with SIENAX; (ii) no significant differences in error when compared with SIENAX-JI and SPM12 in a scan-rescan HC dataset that included repositioning. When tested in a HC dataset with scan-rescan both at baseline and after 1 year of follow-up, SIENA-XL showed: (i) significantly higher precision (P < 0.01) than SIENAX; (ii) no significant differences to SIENAX-JI and SPM12. Finally, in a dataset of 79 MS patients with a 2 years follow-up, SIENA-XL showed a substantial reduction of sample size, by comparison with SIENAX, SIENAX-JI, and SPM12, for detecting treatment effects of 25, 30, and 50%. Hum Brain Mapp 39:1063–1077, 2018. © 2017 Wiley Periodicals, Inc.



Network dynamics engaged in the modulation of motor behavior in stroke patients

2017-11-28T23:15:55.658909-05:00

Stroke patients with motor deficits typically feature enhanced neural activity in several cortical areas when moving their affected hand. However, also healthy subjects may show higher levels of neural activity in tasks with higher motor demands. Therefore, the question arises to what extent stroke-related overactivity reflects performance-level-associated recruitment of neural resources rather than stroke-induced neural reorganization. We here investigated which areas in the lesioned brain enable the flexible adaption to varying motor demands compared to healthy subjects. Accordingly, eleven well-recovered left-hemispheric chronic stroke patients were scanned using functional magnetic resonance imaging. Motor system activity was assessed for fist closures at increasing movement frequencies performed with the affected/right or unaffected/left hand. In patients, an increasing movement rate of the affected hand was associated with stronger neural activity in ipsilesional/left primary motor cortex (M1) but unlike in healthy controls also in contralesional/right dorsolateral premotor cortex (PMd) and contralesional/right superior parietal lobule (SPL). Connectivity analyses using dynamic causal modeling revealed stronger coupling of right SPL onto affected/left M1 in patients but not in controls when moving the affected/right hand independent of the movement speed. Furthermore, coupling of right SPL was positively coupled with the “active” ipsilesional/left M1 when stroke patients moved their affected/right hand with increasing movement frequency. In summary, these findings are compatible with a supportive role of right SPL with respect to motor function of the paretic hand in the reorganized brain.



Validation of T1w-based segmentations of white matter hyperintensity volumes in large-scale datasets of aging

2017-11-27T23:15:58.473241-05:00

Introduction Fluid-attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter hyperintensities (WMHs) in aging and Alzheimer's disease populations. However, many existing large multisite studies forgo their acquisition in favor of other MRI sequences due to economic and time constraints. Methods In this article, we have investigated whether FLAIR and T2w/PD sequences are necessary to detect WMHs in Alzheimer's and aging studies, compared to using only T1w images. Using a previously validated automated tool based on a Random Forests classifier, WMHs were segmented for the baseline visits of subjects from ADC, ADNI1, and ADNI2/GO studies with and without T2w/PD and FLAIR information. The obtained WMH loads (WMHLs) in different lobes were then correlated with manually segmented WMHLs, each other, age, cognitive, and clinical measures to assess the strength of the correlations with and without using T2w/PD and FLAIR information. Results The WMHLs obtained from T1w-Only segmentations correlated with the manual WMHLs (ADNI1: r = .743, p < .001, ADNI2/GO: r = .904, p < .001), segmentations obtained from T1w + T2w + PD for ADNI1 (r = .888, p < .001) and T1w + FLAIR for ADNI2/GO (r = .969, p < .001), age (ADNI1: r = .391, p < .001, ADNI2/GO: r = .466, p < .001), and ADAS13 (ADNI1: r = .227, p < .001, ADNI2/GO: r = .190, p < 0.001), and NPI (ADNI1: r = .290, p < .001, ADNI2/GO: r = 0.144, p < .001), controlling for age. Conclusion Our results suggest that while T2w/PD and FLAIR provide more accurate estimates of the true WMHLs, T1w-Only segmentations can still provide estimates that hold strong correlations with the actual WMHLs, age, and performance on various cognitive/clinical scales, giving added value to datasets where T2w/PD or FLAIR are not available.



Changing brain connectivity dynamics: From early childhood to adulthood

2017-12-05T05:48:31.014745-05:00

Brain maturation through adolescence has been the topic of recent studies. Previous works have evaluated changes in morphometry and also changes in functional connectivity. However, most resting-state fMRI studies have focused on static connectivity. Here we examine the relationship between age/maturity and the dynamics of brain functional connectivity. Utilizing a resting fMRI dataset comprised 421 subjects ages 3–22 from the PING study, we first performed group ICA to extract independent components and their time courses. Next, dynamic functional network connectivity (dFNC) was calculated via a sliding window followed by clustering of connectivity patterns into 5 states. Finally, we evaluated the relationship between age and the amount of time each participant spent in each state as well as the transitions among different states. Results showed that older participants tend to spend more time in states which reflect overall stronger connectivity patterns throughout the brain. In addition, the relationship between age and state transition is symmetric. This can mean individuals change functional connectivity through time within a specific set of states. On the whole, results indicated that dynamic functional connectivity is an important factor to consider when examining brain development across childhood.



Functional connectivity in dementia with Lewy bodies: A within- and between-network analysis

2017-11-29T07:45:39.383051-05:00

Dementia with Lewy bodies (DLB) is a common form of dementia and is characterized by cognitive fluctuations, visual hallucinations, and Parkinsonism. The phenotypic expression of the disease may, in part, relate to alterations in functional connectivity within and between brain networks. This resting-state study sought to clarify this in DLB, how networks differed from Alzheimer's disease (AD), and whether they were related to clinical symptoms in DLB. Resting-state networks were estimated using independent component analysis. We investigated functional connectivity changes in 31 DLB patients compared to 31 healthy controls and a disease comparator group of 29 AD patients using dual regression and FSLNets. Within-network connectivity was generally decreased in DLB compared to controls, mainly in motor, temporal, and frontal networks. Between-network connectivity was mainly intact; only the connection between a frontal and a temporal network showed increased connectivity in DLB. Differences between AD and DLB were subtle and we did not find any significant correlations with the severity of clinical symptoms in DLB. This study emphasizes the importance of reduced connectivity within motor, frontal, and temporal networks in DLB with relative sparing of the default mode network. The lack of significant correlations between connectivity measures and clinical scores indicates that the observed reduced connectivity within these networks might be related to the presence, but not to the severity of motor and cognitive impairment in DLB patients. Furthermore, our results suggest that AD and DLB may show more similarities than differences in patients with mild disease.



Corticospinal tract diffusion properties and robotic visually guided reaching in children with hemiparetic cerebral palsy

2017-11-29T23:20:47.489037-05:00

Perinatal stroke is the leading cause of hemiparetic cerebral palsy (CP), resulting in life-long disability. In this study, we examined the relationship between robotic upper extremity motor impairment and corticospinal tract (CST) diffusion properties. Thirty-three children with unilateral perinatal ischemic stroke (17 arterial, 16 venous) and hemiparesis were recruited from a population-based research cohort. Bilateral CSTs were defined using diffusion tensor imaging (DTI) and four diffusion metrics were quantified: fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivities. Participants completed a visually guided reaching task using the KINARM robot to define 10 movement parameters including movement time and maximum speed. Twenty-six typically developing children underwent the same evaluations. Partial correlations assessed the relationship between robotic reaching and CST diffusion parameters. All diffusion properties of the lesioned CST differed from controls in the arterial group, whereas only FA was reduced in the venous group. Non-lesioned CST diffusion measures were similar between stroke groups and controls. Both stroke groups demonstrated impaired reaching performance. Multiple reaching parameters of the affected limb correlated with lesioned CST diffusion properties. Lower FA and higher MD were associated with greater movement time. Few correlations were observed between non-lesioned CST diffusion and unaffected limb function though FA was associated with reaction time (R = −0.39, p < .01). Diffusion properties of the lesioned CST are altered after perinatal stroke, the degree of which correlates with specific elements of visually guided reaching performance, suggesting specific relevance of CST structural connectivity to clinical motor function in hemiparetic children.



Fronto-parietal coding of goal-directed actions performed by artificial agents

2017-12-05T05:48:13.996255-05:00

With advances in technology, artificial agents such as humanoid robots will soon become a part of our daily lives. For safe and intuitive collaboration, it is important to understand the goals behind their motor actions. In humans, this process is mediated by changes in activity in fronto-parietal brain areas. The extent to which these areas are activated when observing artificial agents indicates the naturalness and easiness of interaction. Previous studies indicated that fronto-parietal activity does not depend on whether the agent is human or artificial. However, it is unknown whether this activity is modulated by observing grasping (self-related action) and pointing actions (other-related action) performed by an artificial agent depending on the action goal. Therefore, we designed an experiment in which subjects observed human and artificial agents perform pointing and grasping actions aimed at two different object categories suggesting different goals. We found a signal increase in the bilateral inferior parietal lobule and the premotor cortex when tool versus food items were pointed to or grasped by both agents, probably reflecting the association of hand actions with the functional use of tools. Our results show that goal attribution engages the fronto-parietal network not only for observing a human but also a robotic agent for both self-related and social actions. The debriefing after the experiment has shown that actions of human-like artificial agents can be perceived as being goal-directed. Therefore, humans will be able to interact with service robots intuitively in various domains such as education, healthcare, public service, and entertainment.



Disruption of network for visual perception of natural motion in primary dystonia

2017-12-06T23:22:31.276085-05:00

In healthy subjects, brain activation in motor regions is greater during the visual perception of “natural” target motion, which complies with the two-thirds power law, than of “unnatural” motion, which does not. It is unknown whether motion perception is normally mediated by a specific network that can be altered in the setting of disease. We used block-design functional magnetic resonance imaging and covariance analysis to identify normal network topographies activated in response to “natural” versus “unnatural” motion. A visual motion perception-related pattern (VPRP) was identified in 12 healthy subjects, characterized by covarying activation responses in the inferior parietal lobule, frontal operculum, lateral occipitotemporal cortex, amygdala, and cerebellum (Crus I). Selective VPRP activation during “natural” motion was confirmed in 12 testing scans from healthy subjects. Consistent network activation was not seen, however, in 29 patients with dystonia, a neurodevelopmental disorder in which motion perception pathways may be involved. Using diffusion tractography, we evaluated the integrity of anatomical connections between the major VPRP nodes. Indeed, fiber counts in these pathways were substantially reduced in the dystonia subjects. In aggregate, the findings associate normal motion perception with a discrete brain network which can be disrupted under pathological conditions.



Cerebral sex dimorphism and sexual orientation

2017-12-11T07:20:45.426794-05:00

The neurobiology of sexual orientation is frequently discussed in terms of cerebral sex dimorphism (defining both functional and structural sex differences). Yet, the information about possible cerebral differences between sex-matched homo and heterosexual persons is limited, particularly among women. In this multimodal MRI study, we addressed these issues by investigating possible cerebral differences between homo and heterosexual persons, and by asking whether there is any sex difference in this aspect. Measurements of cortical thickness (Cth), subcortical volumes, and functional and structural resting-state connections among 40 heterosexual males (HeM) and 40 heterosexual females (HeF) were compared with those of 30 homosexual males (HoM) and 30 homosexual females (HoF). Congruent with previous reports, sex differences were detected in heterosexual controls with regard to fractional anisotropy (FA), Cth, and several subcortical volumes. Homosexual groups did not display any sex differences in FA values. Furthermore, their functional connectivity was significantly less pronounced in the mesial prefrontal and precuneus regions. In these two particular regions, HoM also displayed thicker cerebral cortex than other groups, whereas HoF did not differ from HeF. In addition, in HoM the parietal Cth showed “sex-reversed” values, not observed in HoF. Homosexual orientation seems associated with a less pronounced sexual differentiation of white matter tracts and a less pronounced functional connectivity of the self-referential networks compared to heterosexual orientation. Analyses of Cth suggest that male and female homosexuality are not simple analogues of each other and that differences from heterosexual controls are more pronounced in HoM.



Intraclass correlation: Improved modeling approaches and applications for neuroimaging

2017-12-07T23:19:00.300534-05:00

Intraclass correlation (ICC) is a reliability metric that gauges similarity when, for example, entities are measured under similar, or even the same, well-controlled conditions, which in MRI applications include runs/sessions, twins, parent/child, scanners, sites, and so on. The popular definitions and interpretations of ICC are usually framed statistically under the conventional ANOVA platform. Here, we provide a comprehensive overview of ICC analysis in its prior usage in neuroimaging, and we show that the standard ANOVA framework is often limited, rigid, and inflexible in modeling capabilities. These intrinsic limitations motivate several improvements. Specifically, we start with the conventional ICC model under the ANOVA platform, and extend it along two dimensions: first, fixing the failure in ICC estimation when negative values occur under degenerative circumstance, and second, incorporating precision information of effect estimates into the ICC model. These endeavors lead to four modeling strategies: linear mixed-effects (LME), regularized mixed-effects (RME), multilevel mixed-effects (MME), and regularized multilevel mixed-effects (RMME). Compared to ANOVA, each of these four models directly provides estimates for fixed effects and their statistical significances, in addition to the ICC estimate. These new modeling approaches can also accommodate missing data and fixed effects for confounding variables. More importantly, we show that the MME and RMME approaches offer more accurate characterization and decomposition among the variance components, leading to more robust ICC computation. Based on these theoretical considerations and model performance comparisons with a real experimental dataset, we offer the following general-purpose recommendations. First, ICC estimation through MME or RMME is preferable when precision information (i.e., weights that more accurately allocate the variances in the data) is available for the effect estimate; when precision information is unavailable, ICC estimation through LME or the RME is the preferred option. Second, even though the absolute agreement version, ICC(2,1), is prese[...]



Differential patterns of dynamic functional connectivity variability of striato–cortical circuitry in children with benign epilepsy with centrotemporal spikes

2017-12-05T09:46:11.191474-05:00

Benign epilepsy with centrotemporal spikes (BECTS) is characterized by abnormal (static) functional interactions among cortical and subcortical regions, regardless of the active or chronic epileptic state. However, human brain connectivity is dynamic and associated with ongoing rhythmic activity. The dynamic functional connectivity (dFC) of the distinct striato–cortical circuitry associated with or without interictal epileptiform discharges (IEDs) are poorly understood in BECTS. Herein, we captured the pattern of dFC using sliding window correlation of putamen subregions in the BECTS (without IEDs, n = 23; with IEDs, n = 20) and sex- and age-matched healthy controls (HCs, n = 28) during rest. Furthermore, we quantified dFC variability using their standard deviation. Compared with HCs and patients without IEDs, patients with IEDs exhibited excessive variability in the dorsal striatal-sensorimotor circuitry related to typical seizure semiology. By contrast, excessive stability (decreased dFC variability) was found in the ventral striatal–cognitive circuitry (p < .05, GRF corrected). In addition, correlation analysis revealed that the excessive variability in the dorsal striatal-sensorimotor circuitry was related to highly frequent IEDs (p < .05, uncorrected). Our finding of excessive variability in the dorsal striatal-sensorimotor circuitry could be an indication of increased sensitivity to regional fluctuations in the epileptogenic zone, while excessive stability in the ventral striatal–cognitive circuitry could represent compensatory mechanisms that prevent or postpone cognitive impairments in BECTS. Overall, the differentiated dynamics of the striato–cortical circuitry extend our understanding of interactions among epileptic activity, striato–cortical functional architecture, and neurocognitive processes in BECTS.



Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface-based reconstruction

2017-12-05T09:45:34.718629-05:00

Motion-related artifacts are one of the major challenges associated with pediatric neuroimaging. Recent studies have shown a relationship between visual quality ratings of T1 images and cortical reconstruction measures. Automated algorithms offer more precision in quantifying movement-related artifacts compared to visual inspection. Thus, the goal of this study was to test three different automated quality assessment algorithms for structural MRI scans. The three algorithms included a Fourier-, integral-, and a gradient-based approach which were run on raw T1-weighted imaging data collected from four different scanners. The four cohorts included a total of 6,662 MRI scans from two waves of the Generation R Study, the NIH NHGRI Study, and the GUSTO Study. Using receiver operating characteristics with visually inspected quality ratings of the T1 images, the area under the curve (AUC) for the gradient algorithm, which performed better than either the integral or Fourier approaches, was 0.95, 0.88, and 0.82 for the Generation R, NHGRI, and GUSTO studies, respectively. For scans of poor initial quality, repeating the scan often resulted in a better quality second image. Finally, we found that even minor differences in automated quality measurements were associated with FreeSurfer derived measures of cortical thickness and surface area, even in scans that were rated as good quality. Our findings suggest that the inclusion of automated quality assessment measures can augment visual inspection and may find use as a covariate in analyses or to identify thresholds to exclude poor quality data.



Connectivity-based parcellation of the nucleus accumbens into core and shell portions for stereotactic target localization and alterations in each NAc subdivision in mTLE patients

2017-12-20T23:55:40.063088-05:00

The nucleus accumbens (NAc), an important target of deep brain stimulation for some neuropsychiatric disorders, is thought to be involved in epileptogenesis, especially the shell portion. However, little is known about the exact parcellation within the NAc, and its structural abnormalities or connections alterations of each NAc subdivision in temporal lobe epilepsy (TLE) patients. Here, we used diffusion probabilistic tractography to subdivide the NAc into core and shell portions in individual TLE patients to guide stereotactic localization of NAc shell. The structural and connection abnormalities in each NAc subdivision in the groups were then estimated. We successfully segmented the NAc in 24 of 25 controls, 14 of 16 left TLE patients, and 14 of 18 right TLE patients. Both left and right TLE patients exhibited significantly decreased fractional anisotropy (FA) and increased radial diffusivity (RD) in the shell, while there was no significant alteration in the core. Moreover, relatively distinct structural connectivity of each NAc subdivision was demonstrated. More extensive connection abnormalities were detected in the NAc shell in TLE patients. Our results indicate that neuronal degeneration and damage caused by seizure mainly exists in NAc shell and provide anatomical evidence to support the role of NAc shell in epileptogenesis. Remarkably, those NAc shell tracts with increased connectivities in TLE patients were found decreased in FA, which indicates disruption of fiber integrity. This finding suggests the regeneration of aberrant connections, a compensatory and repair process ascribed to recurrent seizures that constitutes part of the characteristic changes in the epileptic network.



Task-related effective connectivity reveals that the cortical rich club gates cortex-wide communication

2017-12-08T23:17:16.961858-05:00

Higher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs—referred to as the rich club—has been hypothesized to support task-specific functional integration. In the present paper, we use a whole-cortex model to estimate directed interactions between 68 cortical regions from functional magnetic resonance imaging activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state-dependent input and output effective connectivity (EC) of the structural rich club and relate these to whole-cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing EC during task performance as compared with rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task-specific. Furthermore, we observe that whole-cortex dynamics are faster during task as compared with rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing EC. Together our findings speak to a gating mechanism of the rich club that supports fast-paced information exchange among relevant peripheral regions in a task-specific and goal-directed fashion, while constantly listening to the whole network.



Neuronal responses to the scratching and caressing of one's own skin in patients with skin-picking disorder

2017-12-07T23:16:55.038718-05:00

Skin-picking disorder (SPD) is a common mental disorder. The predominant symptom involves the repeated scratching and picking of one's own skin. This behavior causes severe tissue damage (sores, scars, and infections), often leading to disfigurement. Besides physical injury, SPD is associated with clinically significant distress and impairment in important areas of functioning. The neurobiological mechanisms of SPD are still poorly understood. In this study, 30 SPD patients and 31 control participants (35 women, 26 men) with a mean age of 34 years were instructed to either scratch or gently stroke a small skin area on their arms during functional magnetic resonance imaging. Gender-specific effects were revealed. In the female sample, SPD patients showed less activation in the middle frontal gyrus (MFG) and primary/secondary somatosensory cortices during caressing relative to scratching than controls. In addition, contrasting caressing with a rest condition revealed reduced activation in the somatosensory cortex (concerned with the decoding and integration of tactile information) and the MFG (attention/cognitive monitoring) in female patients. No differential brain activation was found in the male sample. This symptom provocation study hints at a reduced sensitivity of pleasant touch in women with SPD.



Structural connectivity of the amygdala in young adults with autism spectrum disorder

2017-12-19T04:15:33.147869-05:00

Autism spectrum disorder (ASD) is characterized by impairments in social cognition, a function associated with the amygdala. Subdivisions of the amygdala have been identified which show specificity of structure, connectivity, and function. Little is known about amygdala connectivity in ASD. The aim of this study was to investigate the microstructural properties of amygdala—cortical connections and their association with ASD behaviours, and whether connectivity of specific amygdala subregions is associated with particular ASD traits. The brains of 51 high-functioning young adults (25 with ASD; 26 controls) were scanned using MRI. Amygdala volume was measured, and amygdala—cortical connectivity estimated using probabilistic tractography. An iterative ‘winner takes all’ algorithm was used to parcellate the amygdala based on its primary cortical connections. Measures of amygdala connectivity were correlated with clinical scores. In comparison with controls, amygdala volume was greater in ASD (F(1,94) = 4.19; p = .04). In white matter (WM) tracts connecting the right amygdala to the right cortex, ASD subjects showed increased mean diffusivity (t = 2.35; p = .05), which correlated with the severity of emotion recognition deficits (rho = −0.53; p = .01). Following amygdala parcellation, in ASD subjects reduced fractional anisotropy in WM connecting the left amygdala to the temporal cortex was associated with with greater attention switching impairment (rho = −0.61; p = .02). This study demonstrates that both amygdala volume and the microstructure of connections between the amygdala and the cortex are altered in ASD. Findings indicate that the microstructure of right amygdala WM tracts are associated with overall ASD severity, but that investigation of amygdala subregions can identify more specific associations.



Physical neglect during childhood alters white matter connectivity in healthy young males

2017-12-17T23:28:26.439469-05:00

Background Childhood adversity (CA) leads to greater vulnerability for psychopathology by causing structural as well as functional brain abnormalities. Recent findings on gray matter effects point towards the importance of identifying CA outcome as a function of different CA types, varying in the dimensions of threat and deprivation. Using diffusion tensor imaging, we investigate whether different forms of CA impact differently on white matter connectivity in a healthy cohort not confounded by other aspects of disease. Methods In 120 healthy young males, we assessed different forms of maltreatment during childhood with the Childhood Trauma Questionnaire (CTQ). Fractional anisotropy (FA) and mean diffusivity (MD) images were generated and projected onto a white matter skeleton using tract-based spatial statistics. Correlational analysis between FA, MD, and CTQ subscores was then performed using voxelwise statistics. Results Of all CTQ-subscores, only physical neglect (PN) predicted a decrease of FA but not MD in the bilateral anterior thalamic radiation around the middle frontal gyrus and the right inferior fronto-occipital fasciculus, the inferior longitudinal fasciculus, the cingulum and precuneus. Reduced FA in the posterior cingulum was related to the effects of PN during childhood on anxiety levels at trend level. Conclusions PN may have severe consequences and should be considered equally important to more active forms of abuse. FA changes, particularly in the cingulum, actually appear to a functional consequence and are linked to trait anxiety, a personality dimension that is suggested to be a transdiagnostic risk factor of affective disorders. Potentially this reveals a mechanistic chain that forms one pathyway from CA to disease.



Intrinsic functional connectivity of the central extended amygdala

2017-12-12T23:23:56.879219-05:00

The central extended amygdala (EAc)—including the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce)—plays a critical role in triggering fear and anxiety and is implicated in the development of a range of debilitating neuropsychiatric disorders. Although it is widely believed that these disorders reflect the coordinated activity of distributed neural circuits, the functional architecture of the EAc network and the degree to which the BST and the Ce show distinct patterns of functional connectivity is unclear. Here, we used a novel combination of imaging approaches to trace the connectivity of the BST and the Ce in 130 healthy, racially diverse, community-dwelling adults. Multiband imaging, high-precision registration techniques, and spatially unsmoothed data maximized anatomical specificity. Using newly developed seed regions, whole-brain regression analyses revealed robust functional connectivity between the BST and Ce via the sublenticular extended amygdala, the ribbon of subcortical gray matter encompassing the ventral amygdalofugal pathway. Both regions displayed coupling with the ventromedial prefrontal cortex (vmPFC), midcingulate cortex (MCC), insula, and anterior hippocampus. The BST showed stronger connectivity with the thalamus, striatum, periaqueductal gray, and several prefrontal territories. The only regions showing stronger functional connectivity with the Ce were neighboring regions of the dorsal amygdala, amygdalohippocampal area, and anterior hippocampus. These observations provide a baseline against which to compare a range of special populations, inform our understanding of the role of the EAc in normal and pathological fear and anxiety, and showcase image registration techniques that are likely to be useful for researchers working with “deidentified” neuroimaging data.



The intraparietal sulcus governs multisensory integration of audiovisual information based on task difficulty

2017-12-12T23:21:32.885636-05:00

Object recognition benefits maximally from multimodal sensory input when stimulus presentation is noisy, or degraded. Whether this advantage can be attributed specifically to the extent of overlap in object-related information, or rather, to object-unspecific enhancement due to the mere presence of additional sensory stimulation, remains unclear. Further, the cortical processing differences driving increased multisensory integration (MSI) for degraded compared with clear information remain poorly understood. Here, two consecutive studies first compared behavioral benefits of audio-visual overlap of object-related information, relative to conditions where one channel carried information and the other carried noise. A hierarchical drift diffusion model indicated performance enhancement when auditory and visual object-related information was simultaneously present for degraded stimuli. A subsequent fMRI study revealed visual dominance on a behavioral and neural level for clear stimuli, while degraded stimulus processing was mainly characterized by activation of a frontoparietal multisensory network, including IPS. Connectivity analyses indicated that integration of degraded object-related information relied on IPS input, whereas clear stimuli were integrated through direct information exchange between visual and auditory sensory cortices. These results indicate that the inverse effectiveness observed for identification of degraded relative to clear objects in behavior and brain activation might be facilitated by selective recruitment of an executive cortical network which uses IPS as a relay mediating crossmodal sensory information exchange.



White matter integrity alterations in post-traumatic stress disorder

2017-12-19T05:20:42.595689-05:00

Post-traumatic stress disorder (PTSD) is a debilitating condition which can develop after exposure to traumatic stressors. Seventy-five adults were recruited from the community, 25 diagnosed with PTSD along with 25 healthy and 25 trauma-exposed age- and gender-matched controls. Participants underwent clinical assessment and magnetic resonance imaging. A previous voxel based morphometry (VBM) study using the same subject cohort identified decreased grey matter (GM) volumes within frontal/subcortical brain regions including the hippocampus, amygdala, and anterior cingulate cortex (ACC). This study examines the microstructural integrity of white matter (WM) tracts connecting the aforementioned regions/structures. Using diffusion tensor imaging, we investigated the integrity of frontal/subcortical WM tracts between all three subject groups. Trauma exposed subjects with and without PTSD diagnosis were identified to have significant disruption in WM integrity as indexed by decreased fractional anisotropy (FA) in the uncinate fasciculus (UF), cingulum cingulate gyrus (CCG), and corpus callosum (CC), when compared with healthy non-trauma-exposed controls. Significant negative correlations were found between total Clinician Administered PTSD scale (CAPS) lifetime clinical subscores and FA values of PTSD subjects in the right UF, CCG, CC body, and right superior longitudinal fasciculus (SLF). An analysis between UF and SLF FA values and VBM determined rostral ACC GM values found a negative correlation in PTSD subjects. Findings suggest that compromised WM integrity in important tracts connecting limbic structures such as the amygdala to frontal regions including the ACC (i.e., the UF and CCG) may contribute to impairments in threat/fear processing associated with PTSD.



Stimulating neural plasticity with real-time fMRI neurofeedback in Huntington's disease: A proof of concept study

2017-12-13T23:21:53.290403-05:00

Novel methods that stimulate neuroplasticity are increasingly being studied to treat neurological and psychiatric conditions. We sought to determine whether real-time fMRI neurofeedback training is feasible in Huntington's disease (HD), and assess any factors that contribute to its effectiveness. In this proof-of-concept study, we used this technique to train 10 patients with HD to volitionally regulate the activity of their supplementary motor area (SMA). We collected detailed behavioral and neuroimaging data before and after training to examine changes of brain function and structure, and cognitive and motor performance. We found that patients overall learned to increase activity of the target region during training with variable effects on cognitive and motor behavior. Improved cognitive and motor performance after training predicted increases in pre-SMA grey matter volume, fMRI activity in the left putamen, and increased SMA–left putamen functional connectivity. Although we did not directly target the putamen and corticostriatal connectivity during neurofeedback training, our results suggest that training the SMA can lead to regulation of associated networks with beneficial effects in behavior. We conclude that neurofeedback training can induce plasticity in patients with Huntington's disease despite the presence of neurodegeneration, and the effects of training a single region may engage other regions and circuits implicated in disease pathology.



Through your eyes or mine? The neural correlates of mental state recognition in Huntington's disease

2017-12-17T23:28:58.733326-05:00

Huntington's disease (HD) can impair social cognition. This study investigated whether patients with HD exhibit neural differences to healthy controls when they are considering mental and physical states relating to the static expressions of human eyes. Thirty-two patients with HD and 28 age-matched controls were scanned with fMRI during two versions of the Reading the Mind in the Eyes Task: The standard version requiring mental state judgments, and a comparison version requiring judgments about age. HD was associated with behavioral deficits on only the mental state eyes task. Contrasting the two versions of the eyes task (mental state > age judgment) revealed hypoactivation within left middle frontal gyrus and supramarginal gyrus in HD. Subgroup analyses comparing premanifest HD patients to age-matched controls revealed reduced activity in right supramarginal gyrus and increased activity in anterior cingulate during mental state recognition in these patients, while manifest HD was associated with hypoactivity in left insula and left supramarginal gyrus. When controlling for the effects of healthy aging, manifest patients exhibited declining activation within areas including right temporal pole. Our findings provide compelling evidence for a selective impairment of internal emotional status when patients with HD appraise facial features in order to make social judgements. Differential activity in temporal and anterior cingulate cortices may suggest that poor emotion regulation and emotional egocentricity underlie impaired mental state recognition in premanifest patients, while more extensive mental state recognition impairments in manifest disease reflect dysfunction in neural substrates underlying executive functions, and the experience and interpretation of emotion.



Resting-state functional connectivity of the bed nucleus of the stria terminalis in post-traumatic stress disorder and its dissociative subtype

2017-12-20T23:56:23.862751-05:00

The bed nucleus of the stria terminals (BNST) is a subcortical structure involved in anticipatory and sustained reactivity to threat and is thus essential to the understanding of anxiety and stress responses. Although chronic stress and anxiety represent a hallmark of post-traumatic stress disorder (PTSD), to date, few studies have examined the functional connectivity of the BNST in PTSD. Here, we used resting state functional Magnetic Resonance Imaging (fMRI) to investigate the functional connectivity of the BNST in PTSD (n = 70), its dissociative subtype (PTSD + DS) (n = 41), and healthy controls (n = 50). In comparison to controls, PTSD showed increased functional connectivity of the BNST with regions of the reward system (ventral and dorsal striatum), possibly underlying stress-induced reward-seeking behaviors in PTSD. By contrast, comparing PTSD + DS to controls, we observed increased functional connectivity of the BNST with the claustrum, a brain region implicated in consciousness and a primary site of kappa-opioid receptors, which are critical to the dynorphin-mediated dysphoric stress response. Moreover, PTSD + DS showed increased functional connectivity of the BNST with brain regions involved in attention and salience detection (anterior insula and caudate nucleus) as compared to PTSD and controls. Finally, BNST functional connectivity positively correlated with default-mode network regions as a function of state identity dissociation, suggesting a role of BNST networks in the disruption of self-relevant processing characterizing the dissociative subtype. These findings represent an important first step in elucidating the role of the BNST in aberrant functional networks underlying PTSD and its dissociative subtype.



Functional connectivity based parcellation of early visual cortices

2017-12-17T23:29:53.18964-05:00

Human brain can be divided into multiple brain regions based on anatomical and functional properties. Recent studies showed that resting-state connectivity can be utilized for parcellating brain regions and identifying their distinctive roles. In this study, we aimed to parcellate the primary and secondary visual cortices (V1 and V2) into several subregions based on functional connectivity and to examine the functional characteristics of each subregion. We used resting-state data from a research database and also acquired resting-state data with retinotopy results from a local site. The long-range connectivity profile and three different algorithms (i.e., K-means, Gaussian mixture model distribution, and Ward's clustering algorithms) were adopted for the parcellation. We compared the parcellation results within V1 and V2 with the eccentric map in retinotopy. We found that the boundaries between subregions within V1 and V2 were located in the parafovea, indicating that the anterior and posterior subregions within V1 and V2 corresponded to peripheral and central visual field representations, respectively. Next, we computed correlations between each subregion within V1 and V2 and intermediate and high-order regions in ventral and dorsal visual pathways. We found that the anterior subregions of V1 and V2 were strongly associated with regions in the dorsal stream (V3A and inferior parietal gyrus), whereas the posterior subregions of V1 and V2 were highly related to regions in the ventral stream (V4v and inferior temporal gyrus). Our findings suggest that the anterior and posterior subregions of V1 and V2, parcellated based on functional connectivity, may have distinct functional properties.



The neural dynamics of competition resolution for language production in the prefrontal cortex

2017-12-19T05:20:30.953495-05:00

Previous research suggests a pivotal role of the prefrontal cortex (PFC) in word selection during tasks of confrontation naming (CN) and verb generation (VG), both of which feature varying degrees of competition between candidate responses. However, discrepancies in prefrontal activity have also been reported between the two tasks, in particular more widespread and intense activation in VG extending into (left) ventrolateral PFC, the functional significance of which remains unclear. We propose that these variations reflect differences in competition resolution processes tied to distinct underlying lexico-semantic operations: Although CN involves selecting lexical entries out of limited sets of alternatives, VG requires exploration of possible semantic relations not readily evident from the object itself, requiring prefrontal areas previously shown to be recruited in top-down retrieval of information from lexico-semantic memory. We tested this hypothesis through combined independent component analysis of functional imaging data and information-theoretic measurements of variations in selection competition associated with participants’ performance in overt CN and VG tasks. Selection competition during CN engaged the anterior insula and surrounding opercular tissue, while competition during VG recruited additional activity of left ventrolateral PFC. These patterns remained after controlling for participants’ speech onset latencies indicative of possible task differences in mental effort. These findings have implications for understanding the neural–computational dynamics of cognitive control in language production and how it relates to the functional architecture of adaptive behavior.



Functional reorganization of intra- and internetwork connectivity in major depressive disorder after electroconvulsive therapy

2017-12-20T23:55:57.737491-05:00

Electroconvulsive therapy (ECT) is an effective and rapid treatment for major depressive disorder (MDD). However, the neurobiological underpinnings of ECT are still largely unknown. Recent studies have identified dysregulated brain networks in MDD. Therefore, we hypothesized that ECT may improve MDD symptoms through reorganizing these networks. To test this hypothesis, we used resting-state functional connectivity to investigate changes to the intra- and internetwork architecture of five reproducible resting-state networks: the default mode network (DMN), dorsal attention network (DAN), executive control network (CON), salience network (SAL), and sensory-motor network. Twenty-three MDD patients were assessed before and after ECT, along with 25 sex-, age-, and education-matched healthy controls. At the network level, enhanced intranetwork connectivities were found in the CON in MDD patients after ECT. Furthermore, enhanced internetwork connectivities between the DMN and SAL, and between the CON and DMN, DAN, and SAL were also identified. At the nodal level, the posterior cingulate cortex had increased connections with the left posterior cerebellum, right posterior intraparietal sulcus (rpIPS), and right anterior prefrontal cortex. The rpIPS had increased connections with the medial PFC (mPFC) and left anterior cingulate cortex. The left lateral parietal had increased connections with the dorsal mPFC (dmPFC), left anterior prefrontal cortex, and right anterior cingulate cortex. The dmPFC had increased connection with the left anterolateral prefrontal cortex. Our findings indicate that enhanced interactions in intra- and internetworks may contribute to the ECT response in MDD patients. These [...]



Affective and cooperative social interactions modulate effective connectivity within and between the mirror and mentalizing systems

2017-12-19T05:21:00.125147-05:00

Decoding the meaning of others’ actions, a crucial step for social cognition, involves different neural mechanisms. While the “mirror” and “mentalizing” systems have been associated with, respectively, the processing of biological actions versus more abstract information, their respective contribution to intention understanding is debated. Processing social interactions seems to recruit both neural systems, with a different weight depending on cues emphasizing either shared action goals or shared mental states. We have previously shown that observing cooperative and affective social interactions elicits stronger activity in key nodes of, respectively, the mirror (left posterior superior temporal sulcus (pSTS), superior parietal cortex (SPL), and ventral/dorsal premotor cortex (vPMC/dPMC)) and mentalizing (ventromedial prefrontal cortex (vmPFC)) systems. To unveil their causal organization, we investigated the effective connectivity underlying the observation of human social interactions expressing increasing cooperativity (involving left pSTS, SPL, and vPMC) versus affectivity (vmPFC) via dynamic causal modeling in 36 healthy human subjects. We found strong evidence for a model including the pSTS and vPMC as input nodes for the observed interactions. The extrinsic connectivity of this model undergoes oppositely valenced modulations, with cooperativity promoting positive modulations of connectivity between pSTS and both SPL (forward) and vPMC (mainly backward), and affectivity promoting reciprocal positive modulations of connectivity between pSTS and vmPFC (mainly backward). Alongside fMRI data, such divergent effective connectivity suggests that differe[...]



A functional near-infrared spectroscopic investigation of speech production during reading

2017-12-19T23:21:18.560812-05:00

This study was designed to test the extent to which speaking processes related to articulation and voicing influence Functional Near Infrared Spectroscopy (fNIRS) measures of cortical hemodynamics and functional connectivity. Participants read passages in three conditions (oral reading, silent mouthing, and silent reading) while undergoing fNIRS imaging. Area under the curve (AUC) analyses of the oxygenated and deoxygenated hemodynamic response function concentration values were compared for each task across five regions of interest. There were significant region main effects for both oxy and deoxy AUC analyses, and a significant region × task interaction for deoxy AUC favoring the oral reading condition over the silent reading condition for two nonmotor regions. Assessment of functional connectivity using Granger Causality revealed stronger networks between motor areas during oral reading and stronger networks between language areas during silent reading. There was no evidence that the hemodynamic flow from motor areas during oral reading compromised measures of language-related neural activity in nonmotor areas. However, speech movements had small, but measurable effects on fNIRS measures of neural connections between motor and nonmotor brain areas across the perisylvian region, even after wavelet filtering. Therefore, researchers studying speech processes with fNIRS should use wavelet filtering during preprocessing to reduce speech motion artifacts, incorporate a nonspeech communication or language control task into the research design, and conduct a connectivity analysis to adequately assess the impact of functional speech on the [...]



Neural mechanism and heritability of complex motor sequence and audiovisual integration: A healthy twin study

2017-12-19T23:20:56.679192-05:00

Complex motor sequencing and sensory integration are two key items in scales assessing neurological soft signs. However, the underlying neural mechanism and heritability of these two functions is not known. Using a healthy twin design, we adopted two functional brain imaging tasks focusing on fist-edge-palm (FEP) complex motor sequence and audiovisual integration (AVI). Fifty-six monozygotic twins and 56 dizygotic twins were recruited in this study. The pre- and postcentral, temporal and parietal gyri, the supplementary motor area, and the cerebellum were activated during the FEP motor sequence, whereas the precentral, temporal, and fusiform gyri, the thalamus, and the caudate were activated during AVI. Activation in the supplementary motor area during FEP motor sequence and activation in the precentral gyrus and the thalamic nuclei during AVI exhibited significant heritability estimates, ranging from 0.5 to 0.62. These results suggest that activation in cortical motor areas, the thalamus and the cerebellum associated with complex motor sequencing and audiovisual integration function may be heritable.



Confirmation of a gyral bias in diffusion MRI fiber tractography

2017-12-19T23:21:52.64457-05:00

Diffusion MRI fiber tractography has been increasingly used to map the structural connectivity of the human brain. However, this technique is not without limitations; for example, there is a growing concern over anatomically correlated bias in tractography findings. In this study, we demonstrate that there is a bias for fiber tracking algorithms to terminate preferentially on gyral crowns, rather than the banks of sulci. We investigate this issue by comparing diffusion MRI (dMRI) tractography with equivalent measures made on myelin-stained histological sections. We begin by investigating the orientation and trajectories of axons near the white matter/gray matter boundary, and the density of axons entering the cortex at different locations along gyral blades. These results are compared with dMRI orientations and tract densities at the same locations, where we find a significant gyral bias in many gyral blades across the brain. This effect is shown for a range of tracking algorithms, both deterministic and probabilistic, and multiple diffusion models, including the diffusion tensor and a high angular resolution diffusion imaging technique. Additionally, the gyral bias occurs for a range of diffusion weightings, and even for very high-resolution datasets. The bias could significantly affect connectivity results using the current generation of tracking algorithms.