Breaking the Excitation-Inhibition Balance Makes the Cortical Network's Space-Time Dynamics Distinguish Simple Visual Scenes

Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes.

[1]  Nicholas J. Priebe,et al.  Orientation Selectivity of Synaptic Input to Neurons in Mouse and Cat Primary Visual Cortex , 2011, The Journal of Neuroscience.

[2]  Simon J. Mitchell,et al.  Direct measurement of somatic voltage clamp errors in central neurons , 2008, Nature Neuroscience.

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

[4]  H. B. Barlow,et al.  Possible Principles Underlying the Transformations of Sensory Messages , 2012 .

[5]  D. Senseman,et al.  Correspondence between visually evoked voltage-sensitive dye signals and synaptic activity recorded in cortical pyramidal cells with intracellular microelectrodes , 1996, Visual Neuroscience.

[6]  R Clay Reid,et al.  Laminar processing of stimulus orientation in cat visual cortex , 2002, The Journal of physiology.

[7]  Viktor K. Jirsa,et al.  Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist , 2016, Front. Syst. Neurosci..

[8]  Steven Mennerick,et al.  Diverse Voltage-Sensitive Dyes Modulate GABAAReceptor Function , 2010, The Journal of Neuroscience.

[9]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[10]  P. Roland,et al.  Cortical feedback depolarization waves: A mechanism of top-down influence on early visual areas , 2006, Proceedings of the National Academy of Sciences.

[11]  Per E. Roland,et al.  The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex , 2016, Front. Syst. Neurosci..

[12]  Alain Destexhe,et al.  Inhibition Determines Membrane Potential Dynamics and Controls Action Potential Generation in Awake and Sleeping Cat Cortex , 2007, The Journal of Neuroscience.

[13]  R. Shapley,et al.  The use of m-sequences in the analysis of visual neurons: Linear receptive field properties , 1997, Visual Neuroscience.

[14]  P. Roland,et al.  Non-Linear Population Firing Rates and Voltage Sensitive Dye Signals in Visual Areas 17 and 18 to Short Duration Stimuli , 2008, PloS one.

[15]  E. Halgren,et al.  Dynamic Balance of Excitation and Inhibition in Human and Monkey Neocortex , 2014, Scientific Reports.

[16]  Jordi García-Ojalvo,et al.  Mesoscopic Segregation of Excitation and Inhibition in a Brain Network Model , 2015, PLoS Comput. Biol..

[17]  M. Carandini,et al.  Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. , 2000, Journal of neurophysiology.

[18]  Nicholas J. Priebe,et al.  Direction Selectivity of Excitation and Inhibition in Simple Cells of the Cat Primary Visual Cortex , 2005, Neuron.

[19]  F. Chavane,et al.  Imaging cortical correlates of illusion in early visual cortex , 2004, Nature.

[20]  C. Petersen,et al.  Visualizing the Cortical Representation of Whisker Touch: Voltage-Sensitive Dye Imaging in Freely Moving Mice , 2006, Neuron.

[21]  Per E. Roland,et al.  Dynamic depolarization fields in the cerebral cortex , 2002, Trends in Neurosciences.

[22]  R. Frostig,et al.  Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[23]  Gustavo Deco,et al.  Cortico-cortical communication dynamics , 2014, Front. Syst. Neurosci..

[24]  Akitoshi Hanazawa,et al.  Cortical Dynamics Subserving Visual Apparent Motion , 2008, Cerebral cortex.

[25]  U. Eysel,et al.  Orientation-specific relationship between populations of excitatory and inhibitory lateral connections in the visual cortex of the cat. , 1997, Cerebral cortex.

[26]  A Grinvald,et al.  Coherent spatiotemporal patterns of ongoing activity revealed by real-time optical imaging coupled with single-unit recording in the cat visual cortex. , 1995, Journal of neurophysiology.

[27]  P. König,et al.  Natural scene evoked population dynamics across cat primary visual cortex captured with voltage-sensitive dye imaging. , 2011, Cerebral cortex.

[28]  Michael Okun,et al.  Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities , 2008, Nature Neuroscience.

[29]  Aaditya V. Rangan,et al.  Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[30]  Yves Frégnac,et al.  Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons , 2013, Front. Neural Circuits.

[31]  D. Hubel,et al.  Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.

[32]  S. Thorpe,et al.  Speed of processing in the human visual system , 1996, Nature.

[33]  F. Chavane,et al.  The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave , 2014, Nature Communications.

[34]  P. Rappelsberger,et al.  Current source density analysis: Methods and application to simultaneously recorded field potentials of the rabbit's visual cortex , 2004, Pflügers Archiv.

[35]  Thomas K. Berger,et al.  Combined voltage and calcium epifluorescence imaging in vitro and in vivo reveals subthreshold and suprathreshold dynamics of mouse barrel cortex. , 2007, Journal of neurophysiology.

[36]  Sonata Valentiniene,et al.  Relating Information, Encoding and Adaptation: Decoding the Population Firing Rate in Visual Areas 17/18 in Response to a Stimulus Transition , 2010, PloS one.

[37]  Y. Frégnac,et al.  In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices , 2008, Journal of Neuroscience Methods.

[38]  A. Destexhe,et al.  Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. , 1999, Journal of neurophysiology.

[39]  James G. King,et al.  Reconstruction and Simulation of Neocortical Microcircuitry , 2015, Cell.

[40]  A. Grinvald,et al.  Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys. , 2002, Journal of neurophysiology.

[41]  Denis Fize,et al.  Speed of processing in the human visual system , 1996, Nature.

[42]  G. Edelman,et al.  Large-scale model of mammalian thalamocortical systems , 2008, Proceedings of the National Academy of Sciences.

[43]  Christian Igel,et al.  A Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-Sensitive Dye Imaging , 2010, PLoS Comput. Biol..

[44]  Christian K. Machens,et al.  Efficient codes and balanced networks , 2016, Nature Neuroscience.

[45]  O. Creutzfeldt,et al.  An intracellular analysis of visual cortical neurones to moving stimuli: Responses in a co-operative neuronal network , 2004, Experimental Brain Research.

[46]  Elie Bienenstock,et al.  Precise Spatiotemporal Patterns among Visual Cortical Areas and Their Relation to Visual Stimulus Processing , 2010, The Journal of Neuroscience.

[47]  W. N. Ross,et al.  Changes in axon fluorescence during activity: Molecular probes of membrane potential , 1974, The Journal of Membrane Biology.

[48]  Gustavo Deco,et al.  The role of multi-area interactions for the computation of apparent motion , 2010, NeuroImage.

[49]  J. Fiala,et al.  Dendrite Structure , 2001 .

[50]  E. Puil,et al.  Ionic mechanism of isoflurane's actions on thalamocortical neurons. , 1999, Journal of Neurophysiology.

[51]  D. McCormick,et al.  Neocortical Network Activity In Vivo Is Generated through a Dynamic Balance of Excitation and Inhibition , 2006, The Journal of Neuroscience.

[52]  Per E. Roland,et al.  Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .

[53]  Lyle J. Graham,et al.  Orientation and Direction Selectivity of Synaptic Inputs in Visual Cortical Neurons A Diversity of Combinations Produces Spike Tuning , 2003, Neuron.

[54]  H. Sompolinsky,et al.  Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity , 1996, Science.

[55]  Ankoor S. Shah,et al.  Functional anatomy and interaction of fast and slow visual pathways in macaque monkeys. , 2007, Cerebral cortex.

[56]  P. E. Roland,et al.  Laminar firing and membrane dynamics in four visual areas exposed to two objects moving to occlusion , 2013, Front. Syst. Neurosci..

[57]  Steve Renals,et al.  Chaos in Neural Networks , 1990, EURASIP Workshop.

[58]  Frédéric Chavane,et al.  Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations. , 2016, Journal of neurophysiology.

[59]  M. Carandini,et al.  Inhibition dominates sensory responses in awake cortex , 2012, Nature.

[60]  B J Richmond,et al.  Temporal encoding of two-dimensional patterns by single units in primate primary visual cortex. II. Information transmission. , 1990, Journal of neurophysiology.

[61]  F. Chavane,et al.  Lateral Spread of Orientation Selectivity in V1 is Controlled by Intracortical Cooperativity , 2011, Front. Syst. Neurosci..

[62]  Peter König,et al.  Independent encoding of grating motion across stationary feature maps in primary visual cortex visualized with voltage-sensitive dye imaging , 2011, NeuroImage.

[63]  M. Scanziani,et al.  Equalizing Excitation-Inhibition Ratios across Visual Cortical Neurons , 2014, Nature.

[64]  D. B. Bender,et al.  Visual properties of neurons in inferotemporal cortex of the Macaque. , 1972, Journal of neurophysiology.

[65]  Per E. Roland,et al.  Six Principles of Visual Cortical Dynamics , 2010, Front. Syst. Neurosci..

[66]  A. Grinvald,et al.  Spatiotemporal Dynamics of Sensory Responses in Layer 2/3 of Rat Barrel Cortex Measured In Vivo by Voltage-Sensitive Dye Imaging Combined with Whole-Cell Voltage Recordings and Neuron Reconstructions , 2003, The Journal of Neuroscience.