Low-noise encoding of active touch by layer 4 in the somatosensory cortex

Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise. DOI: http://dx.doi.org/10.7554/eLife.06619.001

[1]  Jude F. Mitchell,et al.  Spatial Attention Decorrelates Intrinsic Activity Fluctuations in Macaque Area V4 , 2009, Neuron.

[2]  Andrew M. Clark,et al.  Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.

[3]  M. Shadlen,et al.  Limits to the temporal fidelity of cortical spike rate signals , 2002, Nature Neuroscience.

[4]  R. Reid,et al.  Low Response Variability in Simultaneously Recorded Retinal, Thalamic, and Cortical Neurons , 2000, Neuron.

[5]  David G. Stork,et al.  Pattern Classification , 1973 .

[6]  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.

[7]  张静,et al.  Banana Ovate family protein MaOFP1 and MADS-box protein MuMADS1 antagonistically regulated banana fruit ripening , 2015 .

[8]  C. Stevens,et al.  Input synchrony and the irregular firing of cortical neurons , 1998, Nature Neuroscience.

[9]  Nathan G. Clack,et al.  Vibrissa-Based Object Localization in Head-Fixed Mice , 2010, The Journal of Neuroscience.

[10]  Nathan G. Clack,et al.  The Mechanical Variables Underlying Object Localization along the Axis of the Whisker , 2013, The Journal of Neuroscience.

[11]  B. Sakmann,et al.  Cortex Is Driven by Weak but Synchronously Active Thalamocortical Synapses , 2006, Science.

[12]  Zengcai V. Guo,et al.  Flow of Cortical Activity Underlying a Tactile Decision in Mice , 2014, Neuron.

[13]  K. Svoboda,et al.  Interdigitated Paralemniscal and Lemniscal Pathways in the Mouse Barrel Cortex , 2006, PLoS biology.

[14]  R. Lin,et al.  Thalamic afferents of the rat barrel cortex: a light- and electron-microscopic study using Phaseolus vulgaris leucoagglutinin as an anterograde tracer. , 1993, Somatosensory & motor research.

[15]  J. Assad,et al.  Beyond Poisson: Increased Spike-Time Regularity across Primate Parietal Cortex , 2009, Neuron.

[16]  Peter Dayan,et al.  Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .

[17]  Tim Gollisch,et al.  Rapid Neural Coding in the Retina with Relative Spike Latencies , 2008, Science.

[18]  Per Magne Knutsen,et al.  Haptic Object Localization in the Vibrissal System: Behavior and Performance , 2006, The Journal of Neuroscience.

[19]  T. Albright,et al.  Efficient Discrimination of Temporal Patterns by Motion-Sensitive Neurons in Primate Visual Cortex , 1998, Neuron.

[20]  Christof Koch,et al.  Temporal Precision of Spike Trains in Extrastriate Cortex of the Behaving Macaque Monkey , 1999, Neural Computation.

[21]  K. Svoboda,et al.  The subcellular organization of neocortical excitatory connections , 2009, Nature.

[22]  C. Petersen,et al.  The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex , 2009, Neuron.

[23]  A. Litwin-Kumar,et al.  Slow dynamics and high variability in balanced cortical networks with clustered connections , 2012, Nature Neuroscience.

[24]  Zengcai V. Guo,et al.  Procedures for Behavioral Experiments in Head-Fixed Mice , 2014, PloS one.

[25]  Byron M. Yu,et al.  Dimensionality reduction for large-scale neural recordings , 2014, Nature Neuroscience.

[26]  D Kleinfeld,et al.  Central versus peripheral determinants of patterned spike activity in rat vibrissa cortex during whisking. , 1997, Journal of neurophysiology.

[27]  Michael J. Berry,et al.  Refractoriness and Neural Precision , 1997, The Journal of Neuroscience.

[28]  Stefano Panzeri,et al.  Reading spike timing without a clock: intrinsic decoding of spike trains , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[29]  Jude F. Mitchell,et al.  Differential Attention-Dependent Response Modulation across Cell Classes in Macaque Visual Area V4 , 2007, Neuron.

[30]  Vijay Iyer,et al.  Ephus: Multipurpose Data Acquisition Software for Neuroscience Experiments , 2010, Front. Neural Circuits.

[31]  C. Petersen,et al.  Correlating whisker behavior with membrane potential in barrel cortex of awake mice , 2006, Nature Neuroscience.

[32]  Daniel N. Hill,et al.  Primary Motor Cortex Reports Efferent Control of Vibrissa Motion on Multiple Timescales , 2011, Neuron.

[33]  Zengcai V. Guo,et al.  Neural coding during active somatosensation revealed using illusory touch , 2013, Nature Neuroscience.

[34]  Colin W G Clifford,et al.  Informational Basis of Sensory Adaptation: Entropy and Single-Spike Efficiency in Rat Barrel Cortex , 2013, The Journal of Neuroscience.

[35]  J. Movshon,et al.  The statistical reliability of signals in single neurons in cat and monkey visual cortex , 1983, Vision Research.

[36]  D. Sheinberg,et al.  Spike Count Reliability and the Poisson Hypothesis , 2006, The Journal of Neuroscience.

[37]  K. Svoboda,et al.  Neural Activity in Barrel Cortex Underlying Vibrissa-Based Object Localization in Mice , 2010, Neuron.

[38]  D. Kleinfeld,et al.  Neuronal Basis for Object Location in the Vibrissa Scanning Sensorimotor System , 2011, Neuron.

[39]  S. Arber,et al.  A Developmental Switch in the Response of DRG Neurons to ETS Transcription Factor Signaling , 2005, PLoS biology.

[40]  D. Kleinfeld,et al.  Phase-to-rate transformations encode touch in cortical neurons of a scanning sensorimotor system , 2009, Nature Neuroscience.

[41]  Timothée Masquelier,et al.  Neural variability, or lack thereof , 2013, Front. Comput. Neurosci..

[42]  S. Thorpe,et al.  Spike times make sense , 2005, Trends in Neurosciences.

[43]  R. Masterton,et al.  The sensory contribution of a single vibrissa's cortical barrel. , 1986, Journal of neurophysiology.

[44]  Joseph H. Solomon,et al.  Biomechanical models for radial distance determination by the rat vibrissal system. , 2007, Journal of neurophysiology.

[45]  Matthew Crosby,et al.  Association for the Advancement of Artificial Intelligence , 2014 .

[46]  D. Simons Response properties of vibrissa units in rat SI somatosensory neocortex. , 1978, Journal of neurophysiology.

[47]  D. Snodderly,et al.  Response Variability of Neurons in Primary Visual Cortex (V1) of Alert Monkeys , 1997, The Journal of Neuroscience.

[48]  Eugene W. Myers,et al.  Automated Tracking of Whiskers in Videos of Head Fixed Rodents , 2012, PLoS Comput. Biol..

[49]  W. Newsome,et al.  The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.

[50]  Allan R. Jones,et al.  A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing , 2012, Nature Neuroscience.

[51]  William R. Softky,et al.  The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[52]  R. Reid,et al.  Predicting Every Spike A Model for the Responses of Visual Neurons , 2001, Neuron.

[53]  M S Lewicki,et al.  A review of methods for spike sorting: the detection and classification of neural action potentials. , 1998, Network.

[54]  M. London,et al.  Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex , 2010, Nature.

[55]  A. Pouget,et al.  Information-limiting correlations , 2014, Nature Neuroscience.

[56]  D. Kleinfeld,et al.  'Where' and 'what' in the whisker sensorimotor system , 2008, Nature Reviews Neuroscience.

[57]  Garrett B. Stanley,et al.  Thalamic Synchrony and the Adaptive Gating of Information Flow to Cortex , 2010, Nature Neuroscience.

[58]  M. DeWeese,et al.  Binary Spiking in Auditory Cortex , 2003, The Journal of Neuroscience.

[59]  G. Feng,et al.  Cell type–specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function , 2011, Nature Methods.

[60]  Bryan M. Hooks,et al.  Laminar Analysis of Excitatory Local Circuits in Vibrissal Motor and Sensory Cortical Areas , 2011, PLoS biology.

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

[62]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[63]  D. Fitzpatrick,et al.  Three-dimensional mapping of microcircuit correlation structure , 2013, Front. Neural Circuits.

[64]  D. Simons,et al.  Cytochrome oxidase staining in the rat smI barrel cortex , 1985, The Journal of comparative neurology.

[65]  Hans-Peter Kriegel,et al.  OPTICS: ordering points to identify the clustering structure , 1999, SIGMOD '99.

[66]  David Kleinfeld,et al.  Sniffing and whisking in rodents , 2012, Current Opinion in Neurobiology.

[67]  Matteo Carandini,et al.  Somatosensory Integration Controlled by Dynamic Thalamocortical Feed-Forward Inhibition , 2005, Neuron.

[68]  Jason Wolfe,et al.  Sparse temporal coding of elementary tactile features during active whisker sensation , 2009, Nature Neuroscience.

[69]  T. Sejnowski,et al.  Reliability of spike timing in neocortical neurons. , 1995, Science.

[70]  Michael J. Berry,et al.  The structure and precision of retinal spike trains. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[71]  R. Johansson,et al.  First spikes in ensembles of human tactile afferents code complex spatial fingertip events , 2004, Nature Neuroscience.

[72]  Christian K. Machens,et al.  Variability in neural activity and behavior , 2014, Current Opinion in Neurobiology.

[73]  Robin A A Ince,et al.  Low-Dimensional Sensory Feature Representation by Trigeminal Primary Afferents , 2013, The Journal of Neuroscience.