Experience shapes activity dynamics and stimulus coding of VIP inhibitory and excitatory cells in visual cortex

Cortical circuits are flexible and can change with experience and learning. However, the effects of experience on specific cell types including distinct inhibitory types are not well understood. Here we studied how excitatory and VIP inhibitory cells in layer 2/3 of mouse visual cortex were impacted by visual experience in the context of a behavioral task. Mice learned to perform an image change detection task with a set of eight natural scene images. Subsequently, during 2-photon imaging experiments, mice performed the task with these familiar images and three additional sets of novel images. Familiar images evoked less overall activity in both excitatory and VIP populations, and excitatory cells showed higher selectivity for familiar images. The temporal dynamics of VIP cells differed markedly between novel and familiar images: VIP cells were stimulus-driven for novel images but displayed ramping activity during the inter-stimulus interval for familiar images. Moreover, when a familiar stimulus was omitted, VIP cells showed extended ramping activity until the subsequent image flash. This prominent shift in response dynamics suggests that VIP cells may adopt different modes of processing during familiar versus novel conditions. HIGHLIGHTS Experience with natural images in a change detection task reduces overall activity of cortical excitatory and VIP inhibitory cells Encoding of natural images is sharpened with experience in excitatory neurons VIP cells are stimulus-driven by novel images but show pre-stimulus ramping for familiar images VIP cells show strong ramping activity during the omission of an expected stimulus

[1]  Y. Dan,et al.  Delay Activity of Specific Prefrontal Interneuron Subtypes Modulates Memory-Guided Behavior , 2017, Nature Neuroscience.

[2]  M. Bear,et al.  Instructive Effect of Visual Experience in Mouse Visual Cortex , 2006, Neuron.

[3]  M. Scanziani,et al.  Inhibition of Inhibition in Visual Cortex: The Logic of Connections Between Molecularly Distinct Interneurons , 2013, Nature Neuroscience.

[4]  J. H. Hateren,et al.  Independent component filters of natural images compared with simple cells in primary visual cortex , 1998 .

[5]  C. Olson,et al.  Image familiarization sharpens response dynamics of neurons in inferotemporal cortex , 2014, Nature Neuroscience.

[6]  Y. Dan,et al.  Long-range and local circuits for top-down modulation of visual cortex processing , 2014, Science.

[7]  John H. R. Maunsell,et al.  Physiological correlates of perceptual learning in monkey V1 and V2. , 2002, Journal of neurophysiology.

[8]  J. V. van Hateren,et al.  Independent component filters of natural images compared with simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[9]  K. Grill-Spector,et al.  Repetition and the brain: neural models of stimulus-specific effects , 2006, Trends in Cognitive Sciences.

[10]  Demetris K. Roumis,et al.  Removable cranial windows for long-term imaging in awake mice , 2014, Nature Protocols.

[11]  George H. Denfield,et al.  Pupil Fluctuations Track Fast Switching of Cortical States during Quiet Wakefulness , 2014, Neuron.

[12]  M. Bear,et al.  Reward Timing in the Primary Visual Cortex , 2006, Science.

[13]  K. Kuchibhotla,et al.  Neural encoding of sensory and behavioral complexity in the auditory cortex , 2018, Current Opinion in Neurobiology.

[14]  Yang Dan,et al.  Cell-type-specific modulation of neocortical activity by basal forebrain input , 2013, Front. Syst. Neurosci..

[15]  David L. Sheinberg,et al.  Effects of familiarity on neural activity in monkey inferior temporal lobe. , 2008, Cerebral cortex.

[16]  K. Rottner,et al.  How distinct Arp2/3 complex variants regulate actin filament assembly , 2015, Nature Cell Biology.

[17]  I. Rentschler,et al.  Peripheral vision and pattern recognition: a review. , 2011, Journal of vision.

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

[19]  M. Carandini,et al.  Vision and Locomotion Shape the Interactions between Neuron Types in Mouse Visual Cortex , 2016, Neuron.

[20]  S. Denéve,et al.  Neural processing as causal inference , 2011, Current Opinion in Neurobiology.

[21]  Georg B. Keller,et al.  Predictive Processing: A Canonical Cortical Computation , 2018, Neuron.

[22]  James H. Marshel,et al.  Functional Specialization of Seven Mouse Visual Cortical Areas , 2011, Neuron.

[23]  M. Higley,et al.  Preserving the balance: diverse forms of long-term GABAergic synaptic plasticity , 2019, Nature Reviews Neuroscience.

[24]  Amy M LeMessurier,et al.  Plasticity of population coding in primary sensory cortex , 2018, Current Opinion in Neurobiology.

[25]  F. D. Lange,et al.  How Do Expectations Shape Perception? , 2018, Trends in Cognitive Sciences.

[26]  D. Tolhurst,et al.  Characterizing the sparseness of neural codes , 2001 .

[27]  Hassana K. Oyibo,et al.  Experience-dependent spatial expectations in mouse visual cortex , 2016, Nature Neuroscience.

[28]  Lars Muckli,et al.  Contributions of cortical feedback to sensory processing in primary visual cortex , 2014, Front. Psychol..

[29]  Jessica A. Cardin,et al.  Sensation during Active Behaviors , 2017, The Journal of Neuroscience.

[30]  Michael P Stryker,et al.  A cortical disinhibitory circuit for enhancing adult plasticity , 2015, eLife.

[31]  G. Fishell,et al.  Interneuron cell types are fit to function , 2014, Nature.

[32]  J L Gallant,et al.  Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.

[33]  S. Hillyard,et al.  Attending to global versus local stimulus features modulates neural processing of low versus high spatial frequencies: an analysis with event-related brain potentials , 2014, Front. Psychol..

[34]  Y. Dan,et al.  Neuromodulation of Brain States , 2012, Neuron.

[35]  Y. Dan,et al.  Activity Recall in Visual Cortical Ensemble , 2012, Nature Neuroscience.

[36]  Anna C. Nobre,et al.  Anticipated moments: temporal structure in attention , 2017, Nature Reviews Neuroscience.

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

[38]  J. Maunsell,et al.  The Effect of Perceptual Learning on Neuronal Responses in Monkey Visual Area V4 , 2004, The Journal of Neuroscience.

[39]  Giulio Matteucci,et al.  Nonlinear Processing of Shape Information in Rat Lateral Extrastriate Cortex , 2018, The Journal of Neuroscience.

[40]  M. Stryker,et al.  A Cortical Circuit for Gain Control by Behavioral State , 2014, Cell.

[41]  Mark F. Bear,et al.  Learned spatiotemporal sequence recognition and prediction in primary visual cortex , 2014, Nature Neuroscience.

[42]  M. Sahani,et al.  Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex , 2018, Nature Neuroscience.

[43]  G. Fishell,et al.  A disinhibitory circuit mediates motor integration in the somatosensory cortex , 2013, Nature Neuroscience.

[44]  S. Hofer,et al.  Contextual signals in visual cortex , 2018, Current Opinion in Neurobiology.

[45]  M. Larkum A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex , 2013, Trends in Neurosciences.

[46]  David L. Sheinberg,et al.  Effects of Long-Term Visual Experience on Responses of Distinct Classes of Single Units in Inferior Temporal Cortex , 2012, Neuron.

[47]  Joshua I. Sanders,et al.  Cortical interneurons that specialize in disinhibitory control , 2013, Nature.

[48]  J. Stahl,et al.  Eye orientation during static tilts and its relationship to spontaneous head pitch in the laboratory mouse , 2008, Brain Research.

[49]  Kenneth D. Harris,et al.  Coherent encoding of subjective spatial position in visual cortex and hippocampus , 2018, Nature.

[50]  Nathalie L Rochefort,et al.  Action and learning shape the activity of neuronal circuits in the visual cortex , 2018, Current Opinion in Neurobiology.

[51]  Jessica A. Cardin,et al.  Waking State: Rapid Variations Modulate Neural and Behavioral Responses , 2015, Neuron.

[52]  C. Niell,et al.  Distinct functional classes of excitatory neurons in mouse V1 are differentially modulated by learning and task engagement , 2019, bioRxiv.

[53]  Martin Vinck,et al.  Modulation of cortical circuits by top-down processing and arousal state in health and disease , 2018, Current Opinion in Neurobiology.

[54]  Takaki Komiyama,et al.  Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning , 2015, Nature Neuroscience.

[55]  Michael J. Goard,et al.  Fast Modulation of Visual Perception by Basal Forebrain Cholinergic Neurons , 2013, Nature Neuroscience.

[56]  M. Bear,et al.  A Cholinergic Mechanism for Reward Timing within Primary Visual Cortex , 2013, Neuron.

[57]  B. Willmore,et al.  Sparse coding in striate and extrastriate visual cortex. , 2011, Journal of neurophysiology.

[58]  David L. Sheinberg,et al.  Context Familiarity Enhances Target Processing by Inferior Temporal Cortex Neurons , 2007, The Journal of Neuroscience.

[59]  Steffen Katzner,et al.  Learning Enhances Sensory Processing in Mouse V1 before Improving Behavior , 2017, The Journal of Neuroscience.

[60]  Andriana Olmos,et al.  A biologically inspired algorithm for the recovery of shading and reflectance images , 2004 .

[61]  M. Hasselmo Neuromodulation and cortical function: modeling the physiological basis of behavior , 1995, Behavioural Brain Research.

[62]  Georg B. Keller,et al.  Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex , 2015, Neuron.

[63]  Johannes J. Letzkus,et al.  A disinhibitory microcircuit for associative fear learning in the auditory cortex , 2011, Nature.

[64]  Adam Kepecs,et al.  From circuit motifs to computations: mapping the behavioral repertoire of cortical interneurons , 2014, Current Opinion in Neurobiology.

[65]  Rufin Vogels,et al.  Recent Visual Experience Shapes Visual Processing in Rats through Stimulus-Specific Adaptation and Response Enhancement , 2017, Current Biology.

[66]  Grace W. Lindsay,et al.  Parallel processing by cortical inhibition enables context-dependent behavior , 2016, Nature Neuroscience.

[67]  Christof Koch,et al.  A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex , 2018, bioRxiv.

[68]  D. Tolhurst,et al.  Characterizing the sparseness of neural codes , 2001, Network.

[69]  Jordan M. Sorokin,et al.  Brain-Wide Maps of Synaptic Input to Cortical Interneurons , 2016, The Journal of Neuroscience.

[70]  Rajesh P. N. Rao,et al.  Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. , 1999 .

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

[72]  J. Ashby References and Notes , 1999 .

[73]  G. Rainer,et al.  Cognitive neuroscience: Neural mechanisms for detecting and remembering novel events , 2003, Nature Reviews Neuroscience.

[74]  Ian Nauhaus,et al.  Topography and Areal Organization of Mouse Visual Cortex , 2014, The Journal of Neuroscience.

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

[76]  William Muñoz,et al.  Layer-specific modulation of neocortical dendritic inhibition during active wakefulness , 2017, Science.

[77]  Rafael Yuste,et al.  Somatostatin Interneurons Control a Key Component of Mismatch Negativity in Mouse Visual Cortex. , 2016, Cell reports.

[78]  Michael J. Berry,et al.  Predictive Coding of Novel versus Familiar Stimuli in the Primary Visual Cortex , 2017, bioRxiv.

[79]  G. Orban,et al.  Practising orientation identification improves orientation coding in V1 neurons , 2001, Nature.

[80]  I. Nelken,et al.  Mismatch Negativity and Stimulus-Specific Adaptation in Animal Models , 2007 .

[81]  G. Rhodes,et al.  Sex-specific norms code face identity. , 2011, Journal of vision.

[82]  E. Miller,et al.  Experience-dependent sharpening of visual shape selectivity in inferior temporal cortex. , 2005, Cerebral cortex.