Sensory and decision-related activity propagate in a cortical feedback loop during touch perception

The brain transforms physical sensory stimuli into meaningful perceptions. In animals making choices about sensory stimuli, neuronal activity in successive cortical stages reflects a progression from sensation to decision. Feedforward and feedback pathways connecting cortical areas are critical for this transformation. However, the computational functions of these pathways are poorly understood because pathway-specific activity has rarely been monitored during a perceptual task. Using cellular-resolution, pathway-specific imaging, we measured neuronal activity across primary (S1) and secondary (S2) somatosensory cortices of mice performing a tactile detection task. S1 encoded the stimulus better than S2, while S2 activity more strongly reflected perceptual choice. S1 neurons projecting to S2 fed forward activity that predicted choice. Activity encoding touch and choice propagated in an S1–S2 loop along feedforward and feedback axons. Our results suggest that sensory inputs converge into a perceptual outcome as feedforward computations are reinforced in a feedback loop.

[1]  Philipp Schnepel,et al.  Structure of a Single Whisker Representation in Layer 2 of Mouse Somatosensory Cortex , 2015, The Journal of Neuroscience.

[2]  Takayuki Yamashita,et al.  Target-specific membrane potential dynamics of neocortical projection neurons during goal-directed behavior , 2016, eLife.

[3]  Debashis Kushary,et al.  Bootstrap Methods and Their Application , 2000, Technometrics.

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

[5]  C. Petersen,et al.  Membrane potential correlates of sensory perception in mouse barrel cortex , 2013, Nature Neuroscience.

[6]  R. Romo,et al.  Neural correlate of subjective sensory experience gradually builds up across cortical areas , 2006, Proceedings of the National Academy of Sciences.

[7]  C. Koch,et al.  Recurrent excitation in neocortical circuits , 1995, Science.

[8]  Hongdian Yang,et al.  Origins of choice-related activity in mouse somatosensory cortex , 2015, Nature Neuroscience.

[9]  M. Cohen,et al.  Measuring and interpreting neuronal correlations , 2011, Nature Neuroscience.

[10]  David J. Freedman,et al.  Choice-correlated activity fluctuations underlie learning of neuronal category representation , 2015, Nature Communications.

[11]  M. Diamond,et al.  Complementary Contributions of Spike Timing and Spike Rate to Perceptual Decisions in Rat S1 and S2 Cortex , 2015, Current Biology.

[12]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

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

[14]  Karel Svoboda,et al.  ScanImage: Flexible software for operating laser scanning microscopes , 2003, Biomedical engineering online.

[15]  D. Kleinfeld,et al.  Distributed representation of vibrissa movement in the upper layers of somatosensory cortex revealed with voltage‐sensitive dyes , 1996, The Journal of comparative neurology.

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

[17]  F. Helmchen,et al.  Pathway-specific reorganization of projection neurons in somatosensory cortex during learning , 2015, Nature Neuroscience.

[18]  K. H. Britten,et al.  A relationship between behavioral choice and the visual responses of neurons in macaque MT , 1996, Visual Neuroscience.

[19]  C. Petersen,et al.  Long‐range connectivity of mouse primary somatosensory barrel cortex , 2010, The European journal of neuroscience.

[20]  C. Gilbert,et al.  Top-down influences on visual processing , 2013, Nature Reviews Neuroscience.

[21]  F. Helmchen,et al.  Behaviour-dependent recruitment of long-range projection neurons in somatosensory cortex , 2013, Nature.

[22]  Liam Paninski,et al.  Spatiotemporal receptive fields of barrel cortex revealed by reverse correlation of synaptic input , 2014, Nature Neuroscience.

[23]  Lindsey L. Glickfeld,et al.  Cortico-cortical projections in mouse visual cortex are functionally target specific , 2013, Nature Neuroscience.

[24]  Mitra Javadzadeh,et al.  Long-range population dynamics of anatomically defined neocortical networks , 2016, eLife.

[25]  Lin Tian,et al.  Activity in motor-sensory projections reveals distributed coding in somatosensation , 2012, Nature.

[26]  L. Cauller Layer I of primary sensory neocortex: where top-down converges upon bottom-up , 1995, Behavioural Brain Research.

[27]  Karel Svoboda,et al.  The Functional Properties of Barrel Cortex Neurons Projecting to the Primary Motor Cortex , 2010, The Journal of Neuroscience.

[28]  Benjamin A. Suter,et al.  Reciprocal Interareal Connections to Corticospinal Neurons in Mouse M1 and S2 , 2015, The Journal of Neuroscience.

[29]  Ralf M. Haefner,et al.  A Modality-Specific Feedforward Component of Choice-Related Activity in MT , 2015, Neuron.

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

[31]  S. Sherman,et al.  The corticothalamocortical circuit drives higher-order cortex in the mouse , 2009, Nature Neuroscience.

[32]  B W Connors,et al.  Backward cortical projections to primary somatosensory cortex in rats extend long horizontal axons in layer I , 1998, The Journal of comparative neurology.

[33]  Anthony J. Movshon,et al.  Visual Response Properties of Striate Cortical Neurons Projecting to Area MT in Macaque Monkeys , 1996, The Journal of Neuroscience.

[34]  Yves Kremer,et al.  Membrane Potential Dynamics of Neocortical Projection Neurons Driving Target-Specific Signals , 2013, Neuron.

[35]  D. Simons,et al.  Thalamic and corticocortical connections of the second somatic sensory area of the mouse , 1987, The Journal of comparative neurology.

[36]  J. Simon Wiegert,et al.  Multiple dynamic representations in the motor cortex during sensorimotor learning , 2012, Nature.

[37]  Michael I. Jordan,et al.  The Handbook of Brain Theory and Neural Networks , 2002 .

[38]  Karl J. Friston,et al.  Canonical Microcircuits for Predictive Coding , 2012, Neuron.

[39]  A. Keller,et al.  Response properties of whisker-related neurons in rat second somatosensory cortex. , 2004, Journal of neurophysiology.

[40]  A. Parker,et al.  Sense and the single neuron: probing the physiology of perception. , 1998, Annual review of neuroscience.

[41]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Xiao-Jing Wang,et al.  Probabilistic Decision Making by Slow Reverberation in Cortical Circuits , 2002, Neuron.

[43]  Alison L. Barth,et al.  Experimental evidence for sparse firing in the neocortex , 2012, Trends in Neurosciences.

[44]  Brenda C. Shields,et al.  Thy1-GCaMP6 Transgenic Mice for Neuronal Population Imaging In Vivo , 2014, PloS one.

[45]  R. Douglas,et al.  Opening the grey box , 1991, Trends in Neurosciences.

[46]  Stefan R. Pulver,et al.  Ultra-sensitive fluorescent proteins for imaging neuronal activity , 2013, Nature.

[47]  R. Reid,et al.  Broadly Tuned Response Properties of Diverse Inhibitory Neuron Subtypes in Mouse Visual Cortex , 2010, Neuron.

[48]  D. Simons,et al.  Somatotopic organization of the second somatosensory area (SII) in the cerebral cortex of the mouse. , 1986, Somatosensory research.

[49]  S. Manita,et al.  A Top-Down Cortical Circuit for Accurate Sensory Perception , 2015, Neuron.

[50]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[51]  J. Movshon,et al.  A computational analysis of the relationship between neuronal and behavioral responses to visual motion , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[52]  K. Svoboda,et al.  A Cellular Resolution Map of Barrel Cortex Activity during Tactile Behavior , 2015, Neuron.

[53]  Bruce G Cumming,et al.  Decision-related activity in sensory neurons: correlations among neurons and with behavior. , 2012, Annual review of neuroscience.

[54]  J Anthony Movshon,et al.  Visual Response Properties of V1 Neurons Projecting to V2 in Macaque , 2013, The Journal of Neuroscience.

[55]  J. Rinn,et al.  DeCoN: Genome-wide Analysis of In Vivo Transcriptional Dynamics during Pyramidal Neuron Fate Selection in Neocortex , 2015, Neuron.

[56]  Takaki Komiyama,et al.  Learning enhances the relative impact of top-down processing in the visual cortex , 2015, Nature Neuroscience.

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

[58]  Karel Svoboda,et al.  Long-Range Neuronal Circuits Underlying the Interaction between Sensory and Motor Cortex , 2011, Neuron.

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