Facilitating the propagation of spiking activity in feedforward networks by including feedback

Transient oscillations in network activity upon sensory stimulation have been reported in different sensory areas of the brain. These evoked oscillations are the generic response of networks of excitatory and inhibitory neurons (EI-networks) to a transient external input. Recently, it has been shown that this resonance property of EI-networks can be exploited for communication in modular neuronal networks by enabling the transmission of sequences of synchronous spike volleys (’pulse packets’), despite the sparse and weak connectivity between the modules. The condition for successful transmission is that the pulse packet (PP) intervals match the period of the modules’ resonance frequency. Hence, the mechanism was termed communication through resonance (CTR). This mechanism has three severe constraints, though. First, it needs periodic trains of PPs, whereas single PPs fail to propagate. Second, the inter-PP interval needs to match the network resonance. Third, transmission is very slow, because in each module, the network resonance needs to build up over multiple oscillation cycles. Here, we show that, by adding appropriate feedback connections to the network, the CTR mechanism can be improved and the aforementioned constraints relaxed. Specifically, we show that adding feedback connections between two upstream modules, called the resonance pair, in an otherwise feedforward modular network can support successful propagation of a single PP throughout the entire network. The key condition for successful transmission is that the sum of the forward and backward delays in the resonance pair matches the resonance frequency of the network modules. The transmission is much faster, by more than a factor of two, than in the original CTR mechanism. Moreover, it distinctly lowers the threshold for successful communication by synchronous spiking in modular networks of weakly coupled networks. Thus, our results suggest a new functional role of bidirectional connectivity for the communication in cortical area networks.

[1]  Arvind Kumar,et al.  The High-Conductance State of Cortical Networks , 2008, Neural Computation.

[2]  Thomas Schanze,et al.  Possible Neural Mechanisms of Feature Linking in the Visual System: Stimulus-Locked and Stimulus-Induced Synchronizations , 1991 .

[3]  R. Douglas,et al.  A Quantitative Map of the Circuit of Cat Primary Visual Cortex , 2004, The Journal of Neuroscience.

[4]  D. C. Essen,et al.  The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles , 2018, Neuron.

[5]  Angela J. Yu,et al.  Uncertainty, Neuromodulation, and Attention , 2005, Neuron.

[6]  A. Angelucci,et al.  Top-down feedback controls spatial summation and response amplitude in primate visual cortex , 2018, Nature Communications.

[7]  W. Singer,et al.  Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Ad Aertsen,et al.  Propagation of cortical synfire activity: survival probability in single trials and stability in the mean , 2001, Neural Networks.

[9]  Jordi García-Ojalvo,et al.  Role of frequency mismatch in neuronal communication through coherence , 2014, Journal of Computational Neuroscience.

[10]  T. Sejnowski,et al.  Model of Thalamocortical Slow-Wave Sleep Oscillations and Transitions to Activated States , 2002, The Journal of Neuroscience.

[11]  A. Aertsen,et al.  Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding , 2010, Nature Reviews Neuroscience.

[12]  P. Fries.  Neuronal gamma-band synchronization as a fundamental process in cortical computation. , 2009, Annual review of neuroscience.

[13]  Henry Kennedy,et al.  Long-distance feedback projections to area V1: Implications for multisensory integration, spatial awareness, and visual consciousness , 2004, Cognitive, affective & behavioral neuroscience.

[14]  Marc-Oliver Gewaltig,et al.  NEST (NEural Simulation Tool) , 2007, Scholarpedia.

[15]  M. Abeles,et al.  Corticonics: Anatomy of the cerebral cortex , 1991 .

[16]  Ad Aertsen,et al.  Stable propagation of synchronous spiking in cortical neural networks , 1999, Nature.

[17]  Arvind Kumar,et al.  Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity , 2015, Scientific Reports.

[18]  R. Desimone,et al.  Laminar differences in gamma and alpha coherence in the ventral stream , 2011, Proceedings of the National Academy of Sciences.

[19]  Nikola T. Markov,et al.  Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex , 2013, The Journal of comparative neurology.

[20]  Xiao-Jing Wang,et al.  Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex , 2016, Science Advances.

[21]  Haluk Öğmen,et al.  Feedforward and feedback processes in vision , 2015, Front. Psychol..

[22]  Ad Aertsen,et al.  Gating of Signal Propagation in Spiking Neural Networks by Balanced and Correlated Excitation and Inhibition , 2010, The Journal of Neuroscience.

[23]  W. Singer,et al.  Dynamic predictions: Oscillations and synchrony in top–down processing , 2001, Nature Reviews Neuroscience.

[24]  P. Fries.  A mechanism for cognitive dynamics: neuronal communication through neuronal coherence , 2005, Trends in Cognitive Sciences.

[25]  Ad Aertsen,et al.  Recovery of dynamics and function in spiking neural networks with closed-loop control , 2015 .

[26]  Ad Aertsen,et al.  Role of Input Correlations in Shaping the Variability and Noise Correlations of Evoked Activity in the Neocortex , 2015, The Journal of Neuroscience.

[27]  Xun Zhu,et al.  Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage , 2016, Nature Communications.

[28]  G. Buzsáki,et al.  The log-dynamic brain: how skewed distributions affect network operations , 2014, Nature Reviews Neuroscience.

[29]  Markus Diesmann,et al.  Multi-scale account of the network structure of macaque visual cortex , 2017, Brain Structure and Function.

[30]  Tian-De Shou,et al.  The functional roles of feedback projections in the visual system , 2010, Neuroscience bulletin.

[31]  P. Fries,et al.  Robust Gamma Coherence between Macaque V1 and V2 by Dynamic Frequency Matching , 2013, Neuron.

[32]  N. Tamamaki,et al.  Three-dimensional analysis of the whole axonal arbors originating from single CA2 pyramidal neurons in the rat hippocampus with the aid of a computer graphic technique , 1988, Brain Research.

[33]  Yun Wang,et al.  Hierarchical organization of cortical and thalamic connectivity , 2019, Nature.

[34]  Markus Diesmann,et al.  Activity dynamics and propagation of synchronous spiking in locally connected random networks , 2003, Biological Cybernetics.

[35]  Rufin van Rullen,et al.  A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure , 2016, PLoS Comput. Biol..

[36]  L.F. Abbott,et al.  Gating Multiple Signals through Detailed Balance of Excitation and Inhibition in Spiking Networks , 2009, Nature Neuroscience.

[37]  Thomas K. Berger,et al.  A synaptic organizing principle for cortical neuronal groups , 2011, Proceedings of the National Academy of Sciences.

[38]  E. G. Jones.  Cerebral Cortex , 1987, Cerebral Cortex.

[39]  Nicolas Brunel,et al.  Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons , 2000, Journal of Computational Neuroscience.

[40]  Xiao-Jing Wang,et al.  Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex , 2017, Neuron.

[41]  M. Rosenblum,et al.  Delayed feedback control of collective synchrony: an approach to suppression of pathological brain rhythms. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[42]  Fred Wolf,et al.  Flexible information routing by transient synchrony , 2017, Nature Neuroscience.

[43]  Guangyu Robert Yang,et al.  Inter-areal balanced amplification enhances signal propagation in a large-scale circuit model of the primate cortex , 2017 .

[44]  Nikola T. Markov,et al.  A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex , 2012, Cerebral cortex.

[45]  Markus Diesmann,et al.  Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neural Network Simulations , 2007, Neural Computation.

[46]  Qing Nie,et al.  Primary visual cortex shows laminar‐specific and balanced circuit organization of excitatory and inhibitory synaptic connectivity , 2016, The Journal of physiology.

[47]  Maxim Bazhenov,et al.  Feedback stabilizes propagation of synchronous spiking in cortical neural networks , 2015, Proceedings of the National Academy of Sciences.

[48]  Louise S. Delicato,et al.  Attention Reduces Stimulus-Driven Gamma Frequency Oscillations and Spike Field Coherence in V1 , 2010, Neuron.

[49]  D. Modha,et al.  Network architecture of the long-distance pathways in the macaque brain , 2010, Proceedings of the National Academy of Sciences.

[50]  R. Desimone,et al.  Stimulus repetition modulates gamma-band synchronization in primate visual cortex , 2014, Proceedings of the National Academy of Sciences.

[51]  M. Young,et al.  Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[52]  J. Bullier.  Feedback connections and conscious vision , 2001, Trends in Cognitive Sciences.

[53]  Moshe Abeles,et al.  Corticonics: Neural Circuits of Cerebral Cortex , 1991 .

[54]  A. Kohn,et al.  Coordinated Neuronal Activity Enhances Corticocortical Communication , 2015, Neuron.

[55]  D. Amaral,et al.  Organization of intrahippocampal projections originating from CA3 pyramidal cells in the rat , 1990, The Journal of comparative neurology.

[56]  Ad Aertsen,et al.  Physiology and Impact of Horizontal Connections in Rat Neocortex. , 2015, Cerebral cortex.

[57]  A. Aertsen,et al.  Beyond the Cortical Column: Abundance and Physiology of Horizontal Connections Imply a Strong Role for Inputs from the Surround , 2011, Front. Neurosci..

[58]  Ad Aertsen,et al.  Functional consequences of correlated excitatory and inhibitory conductances in cortical networks , 2010, Journal of Computational Neuroscience.

[59]  R. Shapley,et al.  Is Gamma-Band Activity in the Local Field Potential of V1 Cortex a “Clock” or Filtered Noise? , 2011, The Journal of Neuroscience.

[60]  T. Sejnowski,et al.  Control of Spatiotemporal Coherence of a Thalamic Oscillation by Corticothalamic Feedback , 1996, Science.

[61]  Jessica A. Cardin,et al.  Driving fast-spiking cells induces gamma rhythm and controls sensory responses , 2009, Nature.

[62]  Victor A. F. Lamme.  Blindsight: the role of feedforward and feedback corticocortical connections. , 2001, Acta psychologica.

[63]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[64]  Michael E. Hasselmo,et al.  Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and cognitive modulation of signal detection , 2005, Brain Research Reviews.

[65]  R. Eckhorn,et al.  Coherent oscillations: A mechanism of feature linking in the visual cortex? , 1988, Biological Cybernetics.

[66]  Sen Song,et al.  Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.

[67]  Dimitri M. Kullmann,et al.  Oscillatory multiplexing of population codes for selective communication in the mammalian brain , 2014, Nature Reviews Neuroscience.

[68]  Lorenz Pammer,et al.  Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex , 2019, Neuron.

[69]  P. Roelfsema,et al.  Distinct Feedforward and Feedback Effects of Microstimulation in Visual Cortex Reveal Neural Mechanisms of Texture Segregation , 2017, Neuron.

[70]  A. Burkhalter,et al.  Sequential development of connections between striate and extrastriate visual cortical areas in the rat , 1988, The Journal of comparative neurology.

[71]  Simon Sponberg,et al.  Precise timing is ubiquitous, consistent, and coordinated across a comprehensive, spike-resolved flight motor program , 2019, Proceedings of the National Academy of Sciences.

[72]  S. Kastner,et al.  Communication between Brain Areas Based on Nested Oscillations , 2017, eNeuro.

[73]  M. Hashemi,et al.  Effect of duration of synaptic activity on spike rate of a Hodgkin-Huxley neuron with delayed feedback. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[74]  Nicolas Brunel,et al.  Dynamics of Networks of Excitatory and Inhibitory Neurons in Response to Time-Dependent Inputs , 2011, Front. Comput. Neurosci..

[75]  A. Aertsen,et al.  Conditions for Propagating Synchronous Spiking and Asynchronous Firing Rates in a Cortical Network Model , 2008, The Journal of Neuroscience.

[76]  Sonja Grün,et al.  Analysis of Parallel Spike Trains , 2010 .

[77]  Reinhard Eckhorn,et al.  Stimulus-Specific Synchronizations in the Visual Cortex: Linking of Local Features Into Global Figures? , 1991 .

[78]  Ad Aertsen,et al.  Portraits of communication in neuronal networks , 2018, Nature Reviews Neuroscience.

[79]  Alireza Valizadeh,et al.  High frequency neurons determine effective connectivity in neuronal networks , 2018, NeuroImage.

[80]  Arvind Kumar,et al.  Communication through Resonance in Spiking Neuronal Networks , 2014, PLoS Comput. Biol..

[81]  Peter A. Tass,et al.  Delayed feedback control of synchronization in locally coupled neuronal networks , 2005, Neurocomputing.

[82]  N. Logothetis,et al.  The effects of electrical microstimulation on cortical signal propagation , 2010, Nature Neuroscience.

[83]  Xiao-Jing Wang,et al.  What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. , 2003, Journal of neurophysiology.

[84]  Byron M. Yu,et al.  Cortical Areas Interact through a Communication Subspace , 2019, Neuron.

[85]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.