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CiteULike: Tag feedforward

CiteULike: Tag feedforward


Approximation capabilities of multilayer feedforward networks


Neural Networks, Vol. 4, No. 2. (1991), pp. 251-257, doi:
Kurt Hornik

Processing Oscillatory Signals by Incoherent Feedforward Loops


PLoS Comput Biol, Vol. 12, No. 9. (13 September 2016), e1005101, doi:10.1371/journal.pcbi.1005101

From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs—the ability to process oscillatory signals. Our results indicate that the system’s ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal “counting”. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. From circadian clocks to ultradian rhythms, oscillatory signals are found ubiquitously in nature. These oscillations are crucial in the regulation of cellular processes. While the fundamental design principles underlying the generation of these oscillations are extensively studied, the mechanisms for decoding these signals are underappreciated. With implications in both the basic understanding of how cells process temporal signals and the design of synthetic systems, we use quantitative modeling to probe one mechanism, the counting of pulses. We demonstrate the capability of an Incoherent Feedforward Loop motif for the differentiation between sustained and oscillatory input signals.
Carolyn Zhang, Ryan Tsoi, Feilun Wu, Lingchong You

Question classification in Persian using word vectors and frequencies


In Cognitive Systems Research, Vol. 47 (2018), pp. 16-27, doi:10.1016/j.cogsys.2017.07.002

The necessity of the existence of Question Answering (QA) systems becomes evident by considering the fact that the enormous amount of unstructured data created by humans nowadays, results in ineffectiveness of search engines to provide the exact solution for a given question. However, an outstanding question answering system requires an outstanding Question Classification (QC) system. Question classifier is a system that assigns a label to each question. There exist different ways of solving this problem such as rule-based, machine learning, and hybrid approaches. This paper provides a better solution for QC using machine-learning approaches. Three methods of feature extraction are proposed in this paper. The First method uses clustering algorithms to partition vocabulary into clusters and acquires feature vector corresponding to each question using clustering information. The second one suggests a method of extracting features from questions to dispose of using recurrent neural networks and to use feedforward neural networks, which have the advantage of learning faster and less need for data, instead. Each question is converted to a feature vector, which is obtained by the Word2vec method and weighted by tf-idf coefficients. The results of question classification using Support Vector Machine and Neural Network classifiers indicate the effectiveness of this type of feature vector and based on that, high performance of the proposed QC system. Finally, the third approach keeps the innovation behind first approach, but it also keeps the fact that we are dealing with a sequence based type of data into consideration. Eventually, it would be concluded that even with a limited amount of data it is reasonable to take Recurrent Neural Networks into consideration. © 2017 Elsevier B.V.
M Razzaghnoori, H Sajedi, IK Jazani

Multilayer feedforward networks are universal approximators


Neural Networks, Vol. 2, No. 5. (January 1989), pp. 359-366, doi:10.1016/0893-6080(89)90020-8

This paper rigorously establishes that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available. In this sense, multilayer feedforward networks are a class of universal approximators.
Kurt Hornik, Maxwell Stinchcombe, Halbert White

Beyond the comparator model: a multifactorial two-step account of agency.


Consciousness and cognition, Vol. 17, No. 1. (March 2008), pp. 219-239

There is an increasing amount of empirical work investigating the sense of agency, i.e. the registration that we are the initiators of our own actions. Many studies try to relate the sense of agency to an internal feed-forward mechanism, called the "comparator model". In this paper, we draw a sharp distinction between a non-conceptual level of feeling of agency and a conceptual level of judgement of agency. By analyzing recent empirical studies, we show that the comparator model is not able to explain either. Rather, we argue for a two-step account: a multifactorial weighting process of different agency indicators accounts for the feeling of agency, which is, in a second step, further processed by conceptual modules to form an attribution judgement. This new framework is then applied to disruptions of agency in schizophrenia, for which the comparator model also fails. Two further extensions are discussed: We show that the comparator model can neither be extended to account for the sense of ownership (which also has to be differentiated into a feeling and a judgement of ownership) nor for the sense of agency for thoughts. Our framework, however, is able to provide a unified account for the sense of agency for both actions and thoughts.
Matthis Synofzik, Gottfried Vosgerau, Albert Newen

A model based 2-DOF fault tolerant control strategy


In Control & Automation (MED), 2010 18th Mediterranean Conference on (June 2010), pp. 1073-1078, doi:10.1109/med.2010.5547649

In this paper, a novel concept of model based fault tolerance control (FTC) is presented. The FTC is achieved by 2-DOF control strategy: feedback control and feed forward control. Robustness issues are handled by the optimal feedback control and the time varying fault behavior by feed forward path. Firstly, a fault diagnosis scheme is presented for detecting and estimating the fault behavior from the observer based residual generator. The estimated behavior of the fault is used by the feed-forward control algorithm to make appropriate changes in the manipulated variable which keeps the controlled variable near to its set value. The effectiveness of the proposed scheme is analyzed using behavioral theoretic approach.
T Jain, JJ Yamé, D Sauter

Low Computational Color Secret Sharing Schemes with High Shares Quality Color Secret Sharing


In Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2011 Seventh International Conference on (2011), pp. 157-160, doi:10.1109/IIHMSP.2011.50
CC Chang, KN Chen, YH Huang

Feedforward and feedback sources of choice probability in neural population responses


Current Opinion in Neurobiology, Vol. 37 (April 2016), pp. 126-132, doi:10.1016/j.conb.2016.01.009

Decision-related activity (choice-probabilities [CPs]) in sensory neurons is widely found. Correlated variability in sensory neurons limits information in some cases. The structure of correlated variability in sensory neurons influences CPs. CPs and correlated variability likely have feed-forward and feed-back sources. How the processing of signals carried by sensory neurons supports perceptual decisions is a long-standing question in neuroscience. The ability to record neuronal activity in awake animals while they perform psychophysical tasks near threshold has been a key advance in studying these questions. Trial-to-trial correlations between the activity of sensory neurons and the decisions reported by animals (‘choice probabilities’), even when measured across repeated presentations of an identical stimulus provide insights into this problem. But understanding the sources of such co-variability between sensory neurons and behavior has proven more difficult than it initially appeared. Below, we discuss our current understanding of what gives rise to these correlations.
Bruce Cumming, Hendrikje Nienborg

Crossing the Bridge over Norman's Gulf of Execution: Revealing Feedforward's True Identity


In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2013), pp. 1931-1940, doi:10.1145/2470654.2466255

Feedback and affordances are two of the most well-known principles in interaction design. Unfortunately, the related and equally important notion of feedforward has not been given as much consideration. Nevertheless, feedforward is a powerful design principle for bridging Norman's Gulf of Execution. We reframe feedforward by disambiguating it from related design principles such as feedback and perceived affordances, and identify new classes of feedforward. In addition, we present a reference framework that provides a means for designers to explore and recognize different opportunities for feedforward.
Jo Vermeulen, Kris Luyten, Elise van den Hoven, Karin Coninx

Fold Change of Nuclear NF-κB Determines TNF-Induced Transcription in Single Cells


Molecular Cell, Vol. 53, No. 6. (20 March 2014), pp. 867-879, doi:10.1016/j.molcel.2014.01.026

In response to tumor necrosis factor (TNF), NF-κB enters the nucleus and promotes inflammatory and stress-responsive gene transcription. Because NF-κB deregulation is associated with disease, one might expect strict control of NF-κB localization. However, nuclear NF-κB levels exhibit considerable cell-to-cell variability, even in unstimulated cells. To resolve this paradox and determine how transcription-inducing signals are encoded, we quantified single-cell NF-κB translocation dynamics and transcription in the same cells. We show that TNF-induced transcription correlates best with fold change in nuclear NF-κB, not absolute nuclear NF-κB abundance. Using computational modeling, we find that an incoherent feedforward loop, from competition for binding to κB motifs, could provide memory of the preligand state necessary for fold-change detection. Experimentally, we observed three gene-specific transcriptional patterns that our model recapitulates by modulating competition strength alone. Fold-change detection buffers against stochastic variation in signaling molecules and explains how cells tolerate variability in NF-κB abundance and localization.
Robin Lee, Sarah Walker, Kate Savery, David Frank, Suzanne Gaudet

Hippocampal Theta Input to the Amygdala Shapes Feedforward Inhibition to Gate Heterosynaptic Plasticity


Neuron, Vol. 87, No. 6. (26 September 2015), pp. 1290-1303, doi:10.1016/j.neuron.2015.08.024

The dynamic interactions between hippocampus and amygdala are critical for emotional memory. Theta synchrony between these structures occurs during fear memory retrieval and may facilitate synaptic plasticity, but the cellular mechanisms are unknown. We report that interneurons of the mouse basal amygdala are activated during theta network activity or optogenetic stimulation of ventral CA1 pyramidal cell axons, whereas principal neurons are inhibited. Interneurons provide feedforward inhibition that transiently hyperpolarizes principal neurons. However, synaptic inhibition attenuates during theta frequency stimulation of ventral CA1 fibers, and this broadens excitatory postsynaptic potentials. These effects are mediated by GABAB receptors and change in the Cl? driving force. Pairing theta frequency stimulation of ventral CA1 fibers with coincident stimuli of the lateral amygdala induces long-term potentiation of lateral-basal amygdala excitatory synapses. Hence, feedforward inhibition, known to enforce temporal fidelity of excitatory inputs, dominates hippocampus-amygdala interactions to gate heterosynaptic plasticity.
Michaël Bazelot, Marco Bocchio, Yu Kasugai, David Fischer, Paul Dodson, Francesco Ferraguti, Marco Capogna

Small RNA-based feedforward loop with AND-gate logic regulates extrachromosomal DNA transfer in Salmonella


Proceedings of the National Academy of Sciences (11 August 2015), doi:10.1073/pnas.1507825112

Horizontal gene transfer via plasmid conjugation is a major driving force in microbial evolution but constitutes a complex process that requires synchronization with the physiological state of the host bacteria. Although several host transcription factors are known to regulate plasmid-borne transfer genes, RNA-based regulatory circuits for host–plasmid communication remain unknown. We describe a posttranscriptional mechanism whereby the Hfq-dependent small RNA, RprA, inhibits transfer of pSLT, the virulence plasmid of Salmonella enterica. RprA employs two separate seed-pairing domains to activate the mRNAs of both the sigma-factor σS and the RicI protein, a previously uncharacterized membrane protein here shown to inhibit conjugation. Transcription of ricI requires σS and, together, RprA and σS orchestrate a coherent feedforward loop with AND-gate logic to tightly control the activation of RicI synthesis. RicI interacts with the conjugation apparatus protein TraV and limits plasmid transfer under membrane-damaging conditions. To our knowledge, this study reports the first small RNA-controlled feedforward loop relying on posttranscriptional activation of two independent targets and an unexpected role of the conserved RprA small RNA in controlling extrachromosomal DNA transfer.
Kai Papenfort, Elena Espinosa, Josep Casadesús, Jörg Vogel

Reliability of sensory predictions determines the experience of self-agency.


Behavioural brain research, Vol. 228, No. 2. (17 March 2012), pp. 415-422

This study examines the neurocognitive mechanisms underlying the sense of agency, that is, the experience of causing and controlling events in our environment. Specifically, we tested the hypothesis that the sense of agency depends on an optimal integration of different anticipatory signals, generated by motor and nonmotor systems. An established marker of pre-reflective agency experience is the suppression of cortical responses to actively generated feedback as compared to passively observed feedback, which was measured here by event-related potentials (ERPs). Sensory expectations based on motor-related and unrelated signals were induced by varying the probabilistic contingency between action and feedback, and by priming the feedback prior to the action. Moreover, simultaneous conscious agency judgments were assessed. A reduction of visual N1 response was found to self- as compared to externally generated feedback. In addition, the N1 was modulated by accurate anticipations based on prime stimuli, independent of the precision of motor predictions. Conscious agency judgments, in contrast, were enhanced by prime stimuli only in situations where no precise motor predictions of the action feedback were available. These results indicate that anticipatory signals arising from motor and nonmotor systems are integrated differently depending on the level of agency processing. Our findings suggest that, at a pre-reflective level, the brain's agency system relies on both embodied signals and nonmotor sensory expectations. At higher cognitive levels, motor and nonmotor cues are weighted differently depending on their relative reliability in a given context, thereby providing a basis for robust agentive self-awareness. Copyright © 2011 Elsevier B.V. All rights reserved.
Antje Gentsch, Norbert Kathmann, Simone Schütz-Bosbach

Cortical information flow during flexible sensorimotor decisions.


Science (New York, N.Y.), Vol. 348, No. 6241. (19 June 2015), pp. 1352-1355, doi:10.1126/science.aab0551

During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices. It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions [middle temporal area (MT), visual area four (V4), inferior temporal cortex (IT), lateral intraparietal area (LIP), prefrontal cortex (PFC), and frontal eye fields (FEF)] of monkeys reporting the color or motion of stimuli. After a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex. Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information. Copyright © 2015, American Association for the Advancement of Science.
Markus Siegel, Timothy Buschman, Earl Miller

Top-level dynamics and the regulated gene response of feed-forward loop transcriptional motifs


Physical Review E, Vol. 90, No. 3. (10 September 2014), 032706, doi:10.1103/physreve.90.032706

Feed-forward loops are hierarchical three-node transcriptional subnetworks, wherein a top-level protein regulates the activity of a target gene via two paths: a direct-regulatory path, and an indirect route, whereby the top-level proteins act implicitly through an intermediate transcription factor. Using a transcriptional network of the model bacterium Escherichia coli, we confirmed that nearly all types of feed-forward loop were significantly overrepresented in the bacterial network. We then used mathematical modeling to study their dynamics by manipulating the rise times of the top-level protein concentration, termed the induction time, through alteration of the protein destruction rates. Rise times of the regulated proteins exhibited two qualitatively different regimes, depending on whether top-level inductions were “fast” or “slow.” In the fast regime, rise times were nearly independent of rapid top-level inductions, indicative of biological robustness, and occurred when RNA production rate-limits the protein yield. Alternatively, the protein rise times were dependent upon slower top-level inductions, greater than approximately one bacterial cell cycle. An equation is given for this crossover, which depends upon three parameters of the direct-regulatory path: transcriptional cooperation at the DNA-binding site, a protein-DNA dissociation constant, and the relative magnitude of the top-level protien concentration.
Michael Mayo, Ahmed Abdelzaher, Edward Perkins, Preetam Ghosh

Feedforward and quick recurrent processes in early visual cortex revealed by TMS?


NeuroImage, Vol. 61, No. 3. (2 July 2012), pp. 651-659

Transcranial magnetic stimulation (TMS) can be applied to occipital cortex to abolish (conscious) perception of visual stimuli. TMS research has revealed several time windows of masking relative to visual stimulus onset, most consistently a time window around 100ms post-stimulus. However, the exact nature of visual processing in this 'classical' time window, e.g. whether it represents the feedforward processing of the visual information, or rather a feedback projection from higher visual areas, remains unclear. Here, we used TMS to mask in the same participants two types of stimuli of different complexities (orientation Gratings and Faces) over different time windows. Interestingly, the masking functions were not the same for both stimulus types. We found an earlier peak masking latency for orientation stimuli, and a slower recovery for Faces. In a second, follow-up experiment, we superimposed both types of stimuli to create one composite stimulus set. Depending on the instruction, participants could then perform orientation or face discrimination tasks on the exact same stimuli. In addition, for each participant, stimuli were calibrated to equate task difficulties. The peak masking latency was now identical for both tasks, but the masking function revealed again a slower recovery during the face discrimination task, suggesting top-down (recurrent) effects in the second half of the masking function. Hence, rather than this masking window reflecting either feedforward or feedback processing, the early part of what is traditionally considered one masking window may reflect feedforward processing, while the latter part may already reflect recurrent processing. These findings shed new light on recurrent models of vision and related theoretical accounts of visual awareness. Copyright © 2011 Elsevier Inc. All rights reserved.
Tom de Graaf, Rainer Goebel, Alexander Sack

Active noise cancellation in a suspended interferometer


Review of Scientific Instruments, Vol. 83, No. 2. (01 February 2012), 024501, doi:10.1063/1.3675891

We demonstrate feed-forward vibration isolation on a suspended Fabry-Perot interferometer using Wiener filtering and a variant of the common least mean square adaptive filter algorithm. We compare the experimental results with theoretical estimates of the cancellation efficiency. Using data from the recent Laser InterferometerGravitational Wave Observatory (LIGO) Science Run, we also estimate the impact of this technique on full scale gravitational waveinterferometers. In the future, we expect to use this technique also to remove acoustic, magnetic, and gravitational noise perturbations from the LIGOinterferometers. This noise cancellation technique is simple enough to implement in standard laboratory environments and can be used to improve signal-to-noise ratio for a variety of high precision experiments.
Jennifer Driggers, Matthew Evans, Keenan Pepper, Rana Adhikari

Motif statistics of artificially evolved and biological networks


Physical Review E, Vol. 89, No. 6. (30 June 2014), 062719, doi:10.1103/physreve.89.062719

Topological features of gene regulatory networks can be successfully reproduced by a model population evolving under selection for short dynamical attractors. The evolved population of networks exhibit motif statistics, summarized by significance profiles, which closely match those of E. coli, S. cerevsiae, and B. subtilis, in such features as the excess of linear motifs and feedforward loops, and deficiency of feedback loops. The slow relaxation to stasis is a hallmark of a rugged fitness landscape, with independently evolving populations exploring distinct valleys strongly differing in network properties.
Burçin Danacı, Mehmet Anıl, Ayşe Erzan

Dynamic engagement of human motion detectors across space-time coordinates.


The Journal of neuroscience : the official journal of the Society for Neuroscience, Vol. 34, No. 25. (18 June 2014), pp. 8449-8461, doi:10.1523/jneurosci.5434-13.2014

Motion detection is a fundamental property of the visual system. The gold standard for studying and understanding this function is the motion energy model. This computational tool relies on spatiotemporally selective filters that capture the change in spatial position over time afforded by moving objects. Although the filters are defined in space-time, their human counterparts have never been studied in their native spatiotemporal space but rather in the corresponding frequency domain. When this frequency description is back-projected to spatiotemporal description, not all characteristics of the underlying process are retained, leaving open the possibility that important properties of human motion detection may have remained unexplored. We derived descriptors of motion detectors in native space-time, and discovered a large unexpected dynamic structure involving a >2× change in detector amplitude over the first ∼100 ms. This property is not predicted by the energy model, generalizes across the visual field, and is robust to adaptation; however, it is silenced by surround inhibition and is contrast dependent. We account for all results by extending the motion energy model to incorporate a small network that supports feedforward spread of activation along the motion trajectory via a simple gain-control circuit. Copyright © 2014 the authors 0270-6474/14/348449-13$15.00/0.
Peter Neri

Coherent feedforward transcriptional regulatory motifs enhance drug resistance


Physical Review E, Vol. 89, No. 5. (14 May 2014), doi:10.1103/physreve.89.052708
Daniel Charlebois, Gábor Balázsi, Mads Kærn

The equivalence between fuzzy logic systems and feedforward neural networks


IEEE Transactions on Neural Networks, Vol. 11, No. 2. (00 Mar March 2000), pp. 356-365, doi:10.1109/72.839006

Demonstrates that fuzzy logic systems and feedforward neural networks are equivalent in essence. First, we introduce the concept of interpolation representations of fuzzy logic systems and several important conclusions. We then define mathematical models for rectangular wave neural networks and nonlinear neural networks. With this definition, we prove that nonlinear neural networks can be represented by rectangular wave neural networks. Based on this result, we prove the equivalence between fuzzy logic systems and feedforward neural networks. This result provides us a very useful guideline when we perform theoretical research and applications on fuzzy logic systems, neural networks, or neuro-fuzzy systems
Hong-Xing Li, CLP Chen

Large-Scale Genetic Perturbations Reveal Regulatory Networks and an Abundance of Gene-Specific Repressors


Cell, Vol. 157, No. 3. (April 2014), pp. 740-752, doi:10.1016/j.cell.2014.02.054
Patrick Kemmeren, Katrin Sameith, Loes van de Pasch, Joris Benschop, Tineke Lenstra, Thanasis Margaritis, Eoghan O’Duibhir, Eva Apweiler, Sake van Wageningen, Cheuk Ko, Sebastiaan van Heesch, Mehdi Kashani, Giannis Ampatziadis-Michailidis, Mariel Brok, Nathalie Brabers, Anthony Miles, Diane Bouwmeester, Sander van Hooff, Harm van Bakel, Erik Sluiters, Linda Bakker, Berend Snel, Philip Lijnzaad, Dik van Leenen, Marian Groot Koerkamp, Frank Holstege

Distinct roles of the cortical layers of area V1 in figure-ground segregation.


Current biology : CB, Vol. 23, No. 21. (04 November 2013), pp. 2121-2129, doi:10.1016/j.cub.2013.09.013

What roles do the different cortical layers play in visual processing? We recorded simultaneously from all layers of the primary visual cortex while monkeys performed a figure-ground segregation task. This task can be divided into different subprocesses that are thought to engage feedforward, horizontal, and feedback processes at different time points. These different connection types have different patterns of laminar terminations in V1 and can therefore be distinguished with laminar recordings. We found that the visual response started 40 ms after stimulus presentation in layers 4 and 6, which are targets of feedforward connections from the lateral geniculate nucleus and distribute activity to the other layers. Boundary detection started shortly after the visual response. In this phase, boundaries of the figure induced synaptic currents and stronger neuronal responses in upper layer 4 and the superficial layers ~70 ms after stimulus onset, consistent with the hypothesis that they are detected by horizontal connections. In the next phase, ~30 ms later, synaptic inputs arrived in layers 1, 2, and 5 that receive feedback from higher visual areas, which caused the filling in of the representation of the entire figure with enhanced neuronal activity. The present results reveal unique contributions of the different cortical layers to the formation of a visual percept. This new blueprint of laminar processing may generalize to other tasks and to other areas of the cerebral cortex, where the layers are likely to have roles similar to those in area V1. Copyright © 2013 Elsevier Ltd. All rights reserved.
Matthew Self, Timo van Kerkoerle, Hans Supèr, Pieter Roelfsema

A minimal mechanistic model for temporal signal processing in the lateral geniculate nucleus.


Cognitive neurodynamics, Vol. 6, No. 3. (June 2012), pp. 259-281

The receptive fields of cells in the lateral geniculate nucleus (LGN) are shaped by their diverse set of impinging inputs: feedforward synaptic inputs stemming from retina, and feedback inputs stemming from the visual cortex and the thalamic reticular nucleus. To probe the possible roles of these feedforward and feedback inputs in shaping the temporal receptive-field structure of LGN relay cells, we here present and investigate a minimal mechanistic firing-rate model tailored to elucidate their disparate features. The model for LGN relay ON cells includes feedforward excitation and inhibition (via interneurons) from retinal ON cells and excitatory and inhibitory (via thalamic reticular nucleus cells and interneurons) feedback from cortical ON and OFF cells. From a general firing-rate model formulated in terms of Volterra integral equations, we derive a single delay differential equation with absolute delay governing the dynamics of the system. A freely available and easy-to-use GUI-based MATLAB version of this minimal mechanistic LGN circuit model is provided. We particularly investigate the LGN relay-cell impulse response and find through thorough explorations of the model's parameter space that both purely feedforward models and feedback models with feedforward excitation only, can account quantitatively for previously reported experimental results. We find, however, that the purely feedforward model predicts two impulse response measures, the time to first peak and the biphasic index (measuring the relative weight of the rebound phase) to be anticorrelated. In contrast, the models with feedback predict different correlations between these two measures. This suggests an experimental test assessing the relative importance of feedforward and feedback connections in shaping the impulse response of LGN relay cells.
Eivind Norheim, John Wyller, Eilen Nordlie, Gaute Einevoll

The what, when, where, and how of visual word recognition


Trends in Cognitive Sciences, No. 0., doi:10.1016/j.tics.2013.11.005

A long-standing debate in reading research is whether printed words are perceived in a feedforward manner on the basis of orthographic information, with other representations such as semantics and phonology activated subsequently, or whether the system is fully interactive and feedback from these representations shapes early visual word recognition. We review recent evidence from behavioral, functional magnetic resonance imaging, electroencephalography, magnetoencephalography, and biologically plausible connectionist modeling approaches, focusing on how each approach provides insight into the temporal flow of information in the lexical system. We conclude that, consistent with interactive accounts, higher-order linguistic representations modulate early orthographic processing. We also discuss how biologically plausible interactive frameworks and coordinated empirical and computational work can advance theories of visual word recognition and other domains (e.g., object recognition).
Manuel Carreiras, Blair Armstrong, Manuel Perea, Ram Frost

Increasing LIGO sensitivity by feedforward subtraction of auxiliary length control noise


In APS April Meeting Abstracts (April 2013), H8006

LIGO, the Laser Interferometer Gravitational-wave Observatory [Hanford, Washington and Livingston, Louisiana] measures the differential length of 4-km Michelson arms with Fabry-Perot cavities. Length changes could indicate strain caused by astrophysical sources of gravitational waves. Fundamentally limited by seismic noise, thermal suspension noise, and laser shot noise in different frequency bands, a LIGO interferometer's sensitivity can also be degraded by additional relative motion of the inner arm cavity mirrors due to imperfectly-servoed Michelson motion. In this project we seek to subtract the effects of this residual motion by feedforward correction of the gravitational-wave data channel. We divide data from LIGO's sixth science run into 1024-second time windows and numerically fit a filter representing the frequency-domain transfer function from Michelson servo noise to gravitational wave channel for each window. Finally, the Michelson servo channel is processed through the filter and is subtracted from the gravitational-wave signal channel. The algorithm used in this procedure will be described with a preliminary assessment of the achievable sensitivity improvement.
G Meadors, K Kawabe, K Riles

The distinct modes of vision offered by feedforward and recurrent processing.


Trends in neurosciences, Vol. 23, No. 11. (November 2000), pp. 571-579

An analysis of response latencies shows that when an image is presented to the visual system, neuronal activity is rapidly routed to a large number of visual areas. However, the activity of cortical neurons is not determined by this feedforward sweep alone. Horizontal connections within areas, and higher areas providing feedback, result in dynamic changes in tuning. The differences between feedforward and recurrent processing could prove pivotal in understanding the distinctions between attentive and pre-attentive vision as well as between conscious and unconscious vision. The feedforward sweep rapidly groups feature constellations that are hardwired in the visual brain, yet is probably incapable of yielding visual awareness; in many cases, recurrent processing is necessary before the features of an object are attentively grouped and the stimulus can enter consciousness.
VA Lamme, PR Roelfsema

Blindsight: the role of feedforward and feedback corticocortical connections.


Acta psychologica, Vol. 107, No. 1-3. (April 2001), pp. 209-228

When human subjects suffer from a lesion to the primary visual cortex, they lose all visual percepts in the region of space that corresponds to the site of the lesion. However, they are still capable of responding to stimuli in this region when asked to 'guess' or to execute forced-choice motor commands related to these stimuli. This phenomenon, termed blindsight, is still only partly understood. Here, the possible roles of feedforward and feedback corticocortical connections in the visual brain in the understanding of blindsight are reviewed. What emerges is substantial evidence in favor of the theory that unconscious visuo-motor transformations, as in blindsight, may be executed in an entirely feedforward processing cycle, while visual awareness is critically dependent on feedback connections to the primary visual cortex.
VA Lamme

Why visual attention and awareness are different


Trends Cogn Sci, Vol. 7, No. 1. (1 January 2003), pp. 12-18, doi:au - lamme, victor a.f.

Now that the study of consciousness is warmly embraced by cognitive scientists, much confusion seems to arise between the concepts of visual attention and visual awareness. Often, visual awareness is equated to what is in the focus of attention. There are, however, two sets of arguments to separate attention from awareness: a psychological/theoretical one and a neurobiological one. By combining these arguments I present definitions of visual attention and awareness that clearly distinguish between the two, yet explain why attention and awareness are so intricately related. In fact, there seems more overlap between mechanisms of memory and awareness than between those of attention and awareness.
Victor Lamme

Visual Response Properties of V1 Neurons Projecting to V2 in Macaque


The Journal of Neuroscience, Vol. 33, No. 42. (16 October 2013), pp. 16594-16605, doi:10.1523/jneurosci.2753-13.2013

Visual area V2 of the primate cortex receives the largest projection from area V1. V2 is thought to use its striate inputs as the basis for computations that are important for visual form processing, such as signaling angles, object borders, illusory contours, and relative binocular disparity. However, it remains unclear how selectivity for these stimulus properties emerges in V2, in part because the functional properties of the inputs are unknown. We used antidromic electrical stimulation to identify V1 neurons that project directly to V2 (10% of all V1 neurons recorded) and characterized their electrical and visual responses. V2-projecting neurons were concentrated in the superficial and middle layers of striate cortex, consistent with the known anatomy of this cortico-cortical circuit. Most were fast conducting and temporally precise in their electrical responses, and had broad spike waveforms consistent with pyramidal regular-spiking excitatory neurons. Overall, projection neurons were functionally diverse. Most, however, were tuned for orientation and binocular disparity and were strongly suppressed by large stimuli. Projection neurons included those selective and invariant to spatial phase, with roughly equal proportions. Projection neurons found in superficial layers had longer conduction times, broader spike waveforms, and were more responsive to chromatic stimuli; those found in middle layers were more strongly selective for motion direction and binocular disparity. Collectively, these response properties may be well suited for generating complex feature selectivity in and beyond V2.
Yasmine El-Shamayleh, Romesh Kumbhani, Neel Dhruv, Anthony Movshon

Rapid Feedback Responses Correlate with Reach Adaptation and Properties of Novel Upper Limb Loads


The Journal of Neuroscience, Vol. 33, No. 40. (02 October 2013), pp. 15903-15914, doi:10.1523/jneurosci.0263-13.2013

A hallmark of voluntary motor control is the ability to adjust motor patterns for novel mechanical or visuomotor contexts. Recent work has also highlighted the importance of feedback for voluntary control, leading to the hypothesis that feedback responses should adapt when we learn new motor skills. We tested this prediction with a novel paradigm requiring that human subjects adapt to a viscous elbow load while reaching to three targets. Target 1 required combined shoulder and elbow motion, target 2 required only elbow motion, and target 3 (probe target) required shoulder but no elbow motion. This simple approach controlled muscle activity at the probe target before, during, and after the application of novel elbow loads. Our paradigm allowed us to perturb the elbow during reaching movements to the probe target and identify several key properties of adapted stretch responses. Adapted long-latency responses expressed (de-) adaptation similar to reaching errors observed when we introduced (removed) the elbow load. Moreover, reaching errors during learning correlated with changes in the long-latency response, showing subjects who adapted more to the elbow load displayed greater modulation of their stretch responses. These adapted responses were sensitive to the size and direction of the viscous training load. Our results highlight an important link between the adaptation of feedforward and feedback control and suggest a key part of motor adaptation is to adjust feedback responses to the requirements of novel motor skills.
Tyler Cluff, Stephen Scott

Stabilizing gene regulatory networks through feedforward loops


Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 23, No. 2. (2013), 025107, doi:10.1063/1.4808248

The term canalization was coined by the geneticist C. Waddington to describe the theory that embryonal development is buffered against genetic and environmental perturbations. It is only recently that a molecular basis for this phenomenon has been suggested. Recent research has highlighted how the intrinsic stochasticity of gene expression can drive changes in phenotypes. Short segments of single-stranded RNA, so-called microRNAs (miRNA), represent an entirely novel agent of gene regulation discovered relatively recently and have been proposed to function as canalizing agents that buffer the effects of such stochasticity in gene expression. According to this theory, when miRNA expression is perturbed, stochasticity in gene expression can result in transitions to distinct cellular phenotypes. As miRNAs bind to gene targets, they downregulate translation of target mRNA into protein. Embedded in several different types of so-called feedforward loops, miRNAs help smooth out noise and generate canalizing effects in gene regulation by overriding the effect of certain genes on others. Much experimental work remains to be done in elucidating this concept, and recent years have seen an explosive growth of publications in this area. There have also been a number of computational studies focused on canalization. In this paper, we carry out a computational study of the ability of the feedforward loop motif to buffer a gene regulatory network against intrinsic noise. This is done using stochastic Boolean network models as a computational instantiation of gene regulatory networks. We introduce a measure on networks that captures its “distance-to-deterministic” characteristics in terms of the stability of their attractors. For a given network, we successively introduce feedforward loops and track the resulting change in dynamics. The results show clearly that the feedforward loop motif buffers the network phenotype, in terms of stability of attractors, against perturbations from intrinsic noise.
C Kadelka, D Murrugarra, R Laubenbacher

Neutral Stability, Rate Propagation, and Critical Branching in Feedforward Networks


Neural Computation, Vol. 25, No. 7. (22 April 2013), pp. 1768-1806, doi:10.1162/neco_a_00461

Recent experimental and computational evidence suggests that several dynamical properties may characterize the operating point of functioning neural networks: critical branching, neutral stability, and production of a wide range of firing patterns. We seek the simplest setting in which these properties emerge, clarifying their origin and relationship in random, feedforward networks of McCullochs-Pitts neurons. Two key parameters are the thresholds at which neurons fire spikes and the overall level of feedforward connectivity. When neurons have low thresholds, we show that there is always a connectivity for which the properties in question all occur, that is, these networks preserve overall firing rates from layer to layer and produce broad distributions of activity in each layer. This fails to occur, however, when neurons have high thresholds. A key tool in explaining this difference is the eigenstructure of the resulting mean-field Markov chain, as this reveals which activity modes will be preserved from layer to layer. We extend our analysis from purely excitatory networks to more complex models that include inhibition and local noise, and find that both of these features extend the parameter ranges over which networks produce the properties of interest.
Alex Cayco-Gajic, Eric Shea-Brown

A General Mechanism for Network-Dosage Compensation in Gene Circuits


Science, Vol. 329, No. 5999. (24 September 2010), pp. 1656-1660, doi:10.1126/science.1190544

Coping with variations in network dosage is crucial for maintaining optimal function in gene networks. We explored how network structure facilitates network-level dosage compensation. By using the yeast galactose network as a model, we combinatorially deleted one of the two copies of its four regulatory genes and found that network activity was robust to the change in network dosage. A mathematical analysis revealed that a two-component genetic circuit with elements of opposite regulatory activity (activator and inhibitor) constitutes a minimal requirement for network-dosage invariance. Specific interaction topologies and a one-to-one interaction stoichiometry between the activating and inhibiting agents were additional essential elements facilitating dosage invariance. This mechanism of network-dosage invariance could represent a general design for gene network structure in cells.
Murat Acar, Bernardo Pando, Frances Arnold, Michael Elowitz, Alexander van Oudenaarden

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template


Molecular Systems Biology, Vol. 7, No. 1. (02 August 2011), doi:10.1038/msb.2011.49

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability.
Leonidas Bleris, Zhen Xie, David Glass, Asa Adadey, Eduardo Sontag, Yaakov Benenson

Sparse and Background-Invariant Coding of Vocalizations in Auditory Scenes


Neuron, Vol. 79, No. 1. (10 July 2013), pp. 141-152, doi:10.1016/j.neuron.2013.04.038

Vocal communicators such as humans and songbirds readily recognize individual vocalizations, even in distracting auditory environments. This perceptual ability is likely subserved by auditory neurons whose spiking responses to individual vocalizations are minimally affected by background sounds. However, auditory neurons that produce background-invariant responses to vocalizations in auditory scenes have not been found. Here, we describe a population of neurons in the zebra finch auditory cortex that represent vocalizations with a sparse code and that maintain their vocalization-like firing patterns in levels of background sound that permit behavioral recognition. These same neurons decrease or stop spiking in levels of background sound that preclude behavioral recognition. In contrast, upstream neurons represent vocalizations with dense and background-corrupted responses. We provide experimental evidence suggesting that sparse coding is mediated by feedforward suppression. Finally, we show through simulations that feedforward inhibition can transform a dense representation of vocalizations into a sparse and background-invariant representation. "Auditory cortex transforms a dense sensory code to a sparse code"Sparse coding neurons produce background-invariant responses to songs"SNRs of neural background-invariance match SNRs of behavioral recognition"Feedforward inhibition model reproduces both sparse and background-invariant coding Humans and other animals can recognize individual voices in a background of conspecific chatter. Schneider and Woolley identify a population of neurons in the auditory cortex that mirror this perceptual ability by producing background-invariant responses to vocalizations in auditory scenes.
David Schneider, Sarah Woolley

Simultaneous Top-down Modulation of the Primary Somatosensory Cortex and Thalamic Nuclei during Active Tactile Discrimination


The Journal of Neuroscience, Vol. 33, No. 9. (27 February 2013), pp. 4076-4093, doi:10.1523/jneurosci.1659-12.2013

The rat somatosensory system contains multiple thalamocortical loops (TCLs) that altogether process, in fundamentally different ways, tactile stimuli delivered passively or actively sampled. To elucidate potential top-down mechanisms that govern TCL processing in awake, behaving animals, we simultaneously recorded neuronal ensemble activity across multiple cortical and thalamic areas while rats performed an active aperture discrimination task. Single neurons located in the primary somatosensory cortex (S1), the ventroposterior medial, and the posterior medial thalamic nuclei of the trigeminal somatosensory pathways exhibited prominent anticipatory firing modulations before the whiskers touching the aperture edges. This cortical and thalamic anticipatory firing could not be explained by whisker movements or whisker stimulation, because neither trigeminal ganglion sensory-evoked responses nor EMG activity were detected during the same period. Both thalamic and S1 anticipatory activity were predictive of the animal's discrimination accuracy. Inactivation of the primary motor cortex (M1) with muscimol affected anticipatory patterns in S1 and the thalamus, and impaired the ability to predict the animal's performance accuracy based on thalamocortical anticipatory activity. These findings suggest that neural processing in TCLs is launched in anticipation of whisker contact with objects, depends on top-down effects generated in part by M1 activity, and cannot be explained by the classical feedforward model of the rat trigeminal system.
Miguel Pais-Vieira, Mikhail Lebedev, Michael Wiest, Miguel Nicolelis

Unconscious response priming by shape depends on geniculostriate visual projection


European Journal of Neuroscience, Vol. 35, No. 4. (1 February 2012), pp. 623-633, doi:10.1111/j.1460-9568.2011.07973.x

It has been suggested that unconscious visual processing of some stimulus features might occur without the contribution of early visual cortex (V1/V2). In the present study, the causal role of V1/V2 in unconscious processing of simple shapes in intact human brain was studied by applying transcranial magnetic stimulation (TMS) on early visual cortex or lateral occipital cortex (LO) while observers performed a metacontrast-masked response priming task with arrow figures as visual stimuli. Magnetic stimulation of V1/V2 impaired masked priming 30–90 ms after the onset of the prime. Stimulation of LO reduced the magnitude of masked priming at 90–120 ms, but this effect occurred only in the early parts of the priming experiment. A control task measuring the visibility of masked primes indicated that the orientation of masked primes could not be consciously discriminated and that TMS did not influence the conscious visibility of the primes indirectly by reducing the effectiveness of the mask in the critical time windows. We conclude that feedforward sweep of processing from V1/V2 (30–90 ms) to LO (90 ms and above) is necessary for unconscious priming of shape, whereas conscious perception requires also the contribution of recurrent (feedback) processing.
Mika Koivisto, Linda Henriksson, Antti Revonsuo, Henry Railo

Is reentry critical for visual awareness of object presence?


Vision Research, Vol. 63 (June 2012), pp. 43-49, doi:10.1016/j.visres.2012.05.001

Reentrant processing has been proposed as a critical mechanism in visual perception of an object’s features. In order to test whether reentry is critical for visual awareness of object presence, the success of reentry was manipulated with object substitution masking (OSM) while participants performed a forced-choice target present-absent task and rated their subjective confidence in each trial. Signal detection analyses were performed on the data from the forced-choice task and on the subjective confidence ratings. The results showed that OSM reduced sensitivity to the presence of the target, indicating that reentry is critical for awareness of object presence. Consistent with the idea that OSM leaves feedforward processing intact, confidence ratings in reported target-absent trials were lower for misses (target present, no response) than for correct rejections (target absent, no response), implying that a target-related sensory signal was available for subjective ratings in spite of reported absence of the target. The results suggest that reentry is critical for encoding the target representation into a stable, consciously reportable form. ⺠Reentrant (feedback) processing was manipulated with object substitution masking. ⺠Signal detection analysis of present-absent judgments and subjective confidence. ⺠Substitution masking decreased sensitivity (AUC) to the presence of objects. ⺠Subjective confidence was sensitive to the presence of objects in unaware trials. ⺠Reentry is critical for full-blown visual awareness.
Mika Koivisto

Feedforward and quick recurrent processes in early visual cortex revealed by TMS?


NeuroImage, Vol. 61, No. 3. (July 2012), pp. 651-659, doi:10.1016/j.neuroimage.2011.10.020

Transcranial magnetic stimulation (TMS) can be applied to occipital cortex to abolish (conscious) perception of visual stimuli. TMS research has revealed several time windows of masking relative to visual stimulus onset, most consistently a time window around 100 ms post-stimulus. However, the exact nature of visual processing in this ‘classical’ time window, e.g. whether it represents the feedforward processing of the visual information, or rather a feedback projection from higher visual areas, remains unclear. Here, we used TMS to mask in the same participants two types of stimuli of different complexities (orientation Gratings and Faces) over different time windows. Interestingly, the masking functions were not the same for both stimulus types. We found an earlier peak masking latency for orientation stimuli, and a slower recovery for Faces. In a second, follow-up experiment, we superimposed both types of stimuli to create one composite stimulus set. Depending on the instruction, participants could then perform orientation or face discrimination tasks on the exact same stimuli. In addition, for each participant, stimuli were calibrated to equate task difficulties. The peak masking latency was now identical for both tasks, but the masking function revealed again a slower recovery during the face discrimination task, suggesting top-down (recurrent) effects in the second half of the masking function. Hence, rather than this masking window reflecting either feedforward or feedback processing, the early part of what is traditionally considered one masking window may reflect feedforward processing, while the latter part may already reflect recurrent processing. These findings shed new light on recurrent models of vision and related theoretical accounts of visual awareness. ⺠We applied TMS to mask stimuli of orientation Gratings versus Faces. ⺠There was a later peak masking latency, and slower recovery, for Faces. ⺠We next TMS-masked composite Gratings–Faces images with two tasks. ⺠There was still a later recovery of the masking curve in the Faces task. ⺠The TMS masking window may reflect both feedforward and fast recurrent processing.
Tom de Graaf, Rainer Goebel, Alexander Sack

The Incoherent Feedforward Loop Can Provide Fold-Change Detection in Gene Regulation


Mol Cell, Vol. 36, No. 5. (11 December 2009), pp. 894-899

Many sensory systems (e.g., vision and hearing) show a response that is proportional to the fold-change in the stimulus relative to the background, a feature related to Weber's Law. Recent experiments suggest such a fold-change detection feature in signaling systems in cells: a response that depends on the fold-change in the input signal, and not on its absolute level. It is therefore of interest to find molecular mechanisms of gene regulation that can provide such fold-change detection. Here, we demonstrate theoretically that fold-change detection can be generated by one of the most common network motifs in transcription networks, the incoherent feedforward loop (I1-FFL), in which an activator regulates both a gene and a repressor of the gene. The fold-change detection feature of the I1-FFL applies to the entire shape of the response, including its amplitude and duration, and is valid for a wide range of biochemical parameters.
Lea Goentoro, Oren Shoval, Marc Kirschner, Uri Alon

Thermal conductivity prediction of fruits and vegetables using neural networks


International Journal of Food Properties, Vol. 2, No. 2. (1999), pp. 121-137

Artificial neural network was used to predict the thermal conductivity of various fruits and vegetables (apples, pears, corn starch, raisins and potatoes). Neural networks was also used to model the error between the experimental value and that of the theoretical model developed. Two separate networks were used to perform these separate tasks. The optimum configuration of the networks was obtained by trial and error basis using the multilayered approach with the backpropagation and Levenberg-Marquardt Methods used concurrently in the training of the networks. The results showed that the these networks has the ability to model the thermal conductivity as well as to predict the model/experimental error accurately. The networks can then be used as correction factor to the model in a hybrid approach and gave better prediction of thermal conductivity than the model itself.
MA Hussain, MS Rahman

Neural network based model predictive control for a steel pickling process


Journal of Process Control, Vol. 19, No. 4. (2009), pp. 579-590, doi:DOI 10.1016/j.jprocont.2008.09.003

A multi-layer feedforward neural network model based predictive control scheme is developed for a multivariable nonlinear steel pickling process in this paper. In the acid baths three variables under controlled are the hydrochloric acid concentrations. The baths exhibit the normal features of an industrial system such as nonlinear dynamics and multi-effects among variables. In the modeling, multiple input, single-output recurrent neural network subsystem models are developed using input-output data sets obtaining from mathematical model simulation. The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. The proposed algorithm is tested for control of a steel pickling process in several cases in simulation such as for set point tracking, disturbance, model mismatch and presence of noise. The results for the neural network model predictive control (NNMPC) overall show better performance in the control of the system over the conventional PI controller in all cases. © 2008 Elsevier Ltd. All rights reserved.
P Kittisupakorn, P Thitiyasook, MA Hussain, W Daosud

Approximate Predictive versus Self-Tuning Adaptive Control Strategies of Biodiesel Reactors


Industrial & Engineering Chemistry Research, Vol. 48, No. 24. (2009), pp. 11034-11047, doi:Doi 10.1021/Ie900930k

Producing biodiesel from palm oil as a raw material involves complex transesterification reactions which add up to the process nonlinearity. In this work, more emphasis will be focused on the reactor nonlinearity and ways of solving its control problem. The reactor nonlinearity is addressed via the application of an instantaneous linearization technique to control the reactor temperature and the triglyceride product concentration. A feedforward neural network with delayed inputs and outputs was trained and validated to capture the dynamics of the biodiesel process. The generated nonlinear model was then utilized in an instantaneous linearization algorithm using two control algorithms adopting the self-tuning adaptive control and an approximate model predictive framework. The two algorithms were compared in terms of set-point tracking capability, efficiency, and stability. The minimum variance control algorithm attained poor performance compared to the poleplacement self-tuning adaptive algorithm. However, the approximate model predictive control strategy was superior to the self-tuning control in terms of its ability for forcing the output to follow the set-point trajectory efficiently with smooth controller moves. © 2009 American Chemical Society.
FS Mjalli, MA Hussain

A coherent feedforward loop design principle to sustain robustness of biological networks


Bioinformatics, Vol. 29, No. 5. (1 March 2013), pp. 630-637, doi:10.1093/bioinformatics/btt026

Motivation: Many studies have investigated the relationship between structural properties and dynamic behaviors in biological networks. In particular, feedback loop (FBL) and feedforward loop (FFL) structures have received a great deal of attention. One interesting and common property of FBL and FFL structures is their coherency of coupling. However, the role of coherent FFLs in relation to network robustness is not fully known, whereas that of coherent FBLs has been well established.Results: To establish that coherent FFLs are abundant in biological networks, we examined gene regulatory and signaling networks and found that FFLs are ubiquitous, and are in a coherently coupled form. This result was also observed in the species-based signaling networks that are integrated from KEGG database. By using a random Boolean network model, we demonstrated that these coherent FFLs can improve network robustness against update-rule perturbations. In particular, we found that coherent FFLs increase robustness because these structures induce downstream nodes to be robust against update-rule perturbations. Therefore, coherent FFLs can be considered as a design principle of human signaling networks that improve network robustness against update-rule perturbations.Contact: information: Supplementary data are available at Bioinformatics online.
Duc-Hau Le, Yung-Keun Kwon

Efficiency of polymer electrolyte membrane fuel cell stack


Telkomnika, Vol. 9, No. 2. (2011), pp. 303-310

This paper applies a feedforward control of optimal oxygen excess ratio that maximize net power (improve efficiency) of a NedStack P8.0-64 PEM fuel cell stack (FCS) system. Net powers profile as a function of oxygen excess ratio for some points of operation are analyzed by using FCS model. The relationships between stack current and the corresponding control input voltage that gives an optimal oxygen excess ratio are used to design a feedforward control scheme. The results of this scheme are compared to the results of a feedforward control using a constant oxygen excess ratio. Simulation results show that optimal oxygen excess ratio improves fuel cell performance compared to the results of constant oxygen excess ratio. The same procedures are performed experimentally for the FCS system. The behaviour of the net power of the fuel cell stack with respect to the variation of oxygen excess ratio is analyzed to obtain optimal values. Data of stack current and the corresponding voltage input to the compressor that gives optimal values of oxygen excess ratio are used to develop a feedforward control. Feedforward control based on constant and optimal oxygen excess ratio control, are implemented in the NedStack P8.0-64 PEM fuel cell stack system by using LabVIEW. Implementation results shows that optimal oxygen excess ratio control improves the fuel cell performance compared to the constant oxygen excess ratio control. 2011 Universitas Ahmad Dahlan.
Agung Prayitno, Olive Kubumwe, Hans Bosma, Edwin Tazelaar

Efficiency of polymer electrolyte membrane fuel cell stack


Telkomnika, Vol. 9, No. 2. (2011), pp. 303-310

This paper applies a feedforward control of optimal oxygen excess ratio that maximize net power (improve efficiency) of a NedStack P8.0-64 PEM fuel cell stack (FCS) system. Net powers profile as a function of oxygen excess ratio for some points of operation are analyzed by using FCS model. The relationships between stack current and the corresponding control input voltage that gives an optimal oxygen excess ratio are used to design a feedforward control scheme. The results of this scheme are compared to the results of a feedforward control using a constant oxygen excess ratio. Simulation results show that optimal oxygen excess ratio improves fuel cell performance compared to the results of constant oxygen excess ratio. The same procedures are performed experimentally for the FCS system. The behaviour of the net power of the fuel cell stack with respect to the variation of oxygen excess ratio is analyzed to obtain optimal values. Data of stack current and the corresponding voltage input to the compressor that gives optimal values of oxygen excess ratio are used to develop a feedforward control. Feedforward control based on constant and optimal oxygen excess ratio control, are implemented in the NedStack P8.0-64 PEM fuel cell stack system by using LabVIEW. Implementation results shows that optimal oxygen excess ratio control improves the fuel cell performance compared to the constant oxygen excess ratio control. 2011 Universitas Ahmad Dahlan.
Agung Prayitno, Olive Kubumwe, Hans Bosma, Edwin Tazelaar

Feed-forward, feedback and lateral interactions in membrane potentials and spike trains from the visual cortex in vivo.


J Physiol Paris (10 Nov 2006)

Neurons in the visual cortex receive input from the lateral geniculate nucleus (feed-forward), higher order visual areas (feedback) and local neurons in the surroundings (lateral interactions). Here we first briefly review the approximate timing and proportion of these three types of influences on the membrane potentials in visual areas 17, 18 and 19. Then we present original results from an independent component analysis of multiunit spike trains in the same visual areas to resolve the contribution from these three sources. We stimulated the visual cortex of the ferret with a small transient contrast square stimulus and recorded the multiunit activity in areas 17, 18 and 19 with single or multiple electrodes. The spike trains had three reproducible components having their maxima at 40, 55 and 105ms after the start of the presentation of the stimulus. The time course of the third component was significantly correlated with the population membrane potential in the supragranular layers of areas 17, 18 and 19. The first spike train component was interpreted as a feed-forward response, the second spike train component as driving the laterally spreading depolarization and the third spike train component as the firing caused by the lateral spreading- and the feedback depolarization.
David Eriksson, Per Roland

Synaptic basis for intense thalamocortical activation of feedforward inhibitory cells in neocortex.


Nature neuroscience, Vol. 10 (xx Apr 2007), pp. 462-468

The thalamus provides fundamental input to the neocortex. This input activates inhibitory interneurons more strongly than excitatory neurons, triggering powerful feedforward inhibition. We studied the mechanisms of this selective neuronal activation using a mouse somatosensory thalamocortical preparation. Notably, the greater responsiveness of inhibitory interneurons was not caused by their distinctive intrinsic properties but was instead produced by synaptic mechanisms. Axons from the thalamus made stronger and more frequent excitatory connections onto inhibitory interneurons than onto excitatory cells. Furthermore, circuit dynamics allowed feedforward inhibition to suppress responses in excitatory cells more effectively than in interneurons. Thalamocortical excitatory currents rose quickly in interneurons, allowing them to fire action potentials before significant feedforward inhibition emerged. In contrast, thalamocortical excitatory currents rose slowly in excitatory cells, overlapping with feedforward inhibitory currents that suppress action potentials. These results demonstrate the importance of selective synaptic targeting and precise timing in the initial stages of neocortical processing.
Scott Cruikshank, Timothy Lewis, Barry Connors

Magnocellular projections as the trigger of top-down facilitation in recognition.


The Journal of neuroscience : the official journal of the Society for Neuroscience, Vol. 27 (28 Nov 2007), pp. 13232-13240

Object recognition is traditionally viewed as a hierarchical, bottom-up neural process. This view has been challenged recently by theoretical models and by findings indicating that top-down processes are involved in facilitating recognition. However, how such high-level information can be activated quickly enough to facilitate the bottom-up processing is yet unknown. We propose that such top-down facilitation is triggered by magnocellular information projected early and rapidly to the orbitofrontal cortex. Using human neuroimaging, we show that stimuli designed to bias processing toward the magnocellular pathway differentially activated the orbitofrontal cortex compared with parvocellular-biased stimuli. Although the magnocellular stimuli had a lower contrast than the parvocellular stimuli, they were recognized faster and just as accurately. Moreover, orbitofrontal activity predicted the performance advantage for the magnocellular, but not for the parvocellular-biased, stimuli, whereas the opposite was true in the fusiform gyrus. Last, analyses of effective connectivity using dynamic causal modeling showed that magnocellular-biased stimuli significantly activated pathways from occipital visual cortex to orbitofrontal cortex and from orbitofrontal cortex to fusiform gyrus. Conversely, parvocellular-biased stimuli significantly activated a pathway from the occipital visual cortex to fusiform gyrus. Our findings support the proposal that fast magnocellular projections linking early visual and inferotemporal object recognition regions with the orbitofrontal cortex facilitate object recognition by enabling the generation of early predictions.
Kestutis Kveraga, Jasmine Boshyan, Moshe Bar