Three-dimensional mapping of microcircuit correlation structure

Great progress has been made toward understanding the properties of single neurons, yet the principles underlying interactions between neurons remain poorly understood. Given that connectivity in the neocortex is locally dense through both horizontal and vertical connections, it is of particular importance to characterize the activity structure of local populations of neurons arranged in three dimensions. However, techniques for simultaneously measuring microcircuit activity are lacking. We developed an in vivo 3D high-speed, random-access two-photon microscope that is capable of simultaneous 3D motion tracking. This allows imaging from hundreds of neurons at several hundred Hz, while monitoring tissue movement. Given that motion will induce common artifacts across the population, accurate motion tracking is absolutely necessary for studying population activity with random-access based imaging methods. We demonstrate the potential of this imaging technique by measuring the correlation structure of large populations of nearby neurons in the mouse visual cortex, and find that the microcircuit correlation structure is stimulus-dependent. Three-dimensional random access multiphoton imaging with concurrent motion tracking provides a novel, powerful method to characterize the microcircuit activity in vivo.

[1]  C. Gilbert,et al.  The projections of cells in different layers of the cat's visual cortex , 1975, The Journal of comparative neurology.

[2]  B. Nikolaus,et al.  Two-Photon Laser , 1981 .

[3]  W. Denk,et al.  Two-photon laser scanning fluorescence microscopy. , 1990, Science.

[4]  P. Saggau,et al.  Presynaptic calcium is increased during normal synaptic transmission and paired-pulse facilitation, but not in long-term potentiation in area CA1 of hippocampus , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[5]  Daniel J. Gauthier,et al.  The Two-Photon Laser , 1994 .

[6]  Ehud Zohary,et al.  Correlated neuronal discharge rate and its implications for psychophysical performance , 1994, Nature.

[7]  C. Brody.  Slow covariations in neuronal resting potentials can lead to artefactually fast cross-correlations in their spike trains. , 1998, Journal of neurophysiology.

[8]  Peter Dayan,et al.  The Effect of Correlated Variability on the Accuracy of a Population Code , 1999, Neural Computation.

[9]  H. Sompolinsky,et al.  Population coding in neuronal systems with correlated noise. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  W. Bair,et al.  Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior , 2001, The Journal of Neuroscience.

[11]  Christian W. Eurich,et al.  Representational Accuracy of Stochastic Neural Populations , 2002, Neural Computation.

[12]  C. Stosiek,et al.  In vivo two-photon calcium imaging of neuronal networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[14]  R. Douglas,et al.  Neuronal circuits of the neocortex. , 2004, Annual review of neuroscience.

[15]  Haim Sompolinsky,et al.  Nonlinear Population Codes , 2004, Neural Computation.

[16]  W. Denk,et al.  Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure , 2004, PLoS biology.

[17]  Daeyeol Lee,et al.  Coding and transmission of information by neural ensembles , 2004, Trends in Neurosciences.

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

[19]  E. Callaway,et al.  Excitatory cortical neurons form fine-scale functional networks , 2005, Nature.

[20]  P. Saggau,et al.  Fast three-dimensional laser scanning scheme using acousto-optic deflectors. , 2005, Journal of biomedical optics.

[21]  M. A. Smith,et al.  Stimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque , 2005, The Journal of Neuroscience.

[22]  O. Garaschuk,et al.  Targeted bulk-loading of fluorescent indicators for two-photon brain imaging in vivo , 2006, Nature Protocols.

[23]  Haim Sompolinsky,et al.  Implications of Neuronal Diversity on Population Coding , 2006, Neural Computation.

[24]  W. Denk,et al.  Two-photon targeted patching (TPTP) in vivo , 2006, Nature Protocols.

[25]  A. Thomson,et al.  Functional Maps of Neocortical Local Circuitry , 2007, Front. Neurosci..

[26]  Ian R. Wickersham,et al.  Monosynaptic Restriction of Transsynaptic Tracing from Single, Genetically Targeted Neurons , 2007, Neuron.

[27]  R. W. Draft,et al.  Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system , 2007, Nature.

[28]  F. Helmchen,et al.  Imaging cellular network dynamics in three dimensions using fast 3D laser scanning , 2007, Nature Methods.

[29]  F. Helmchen,et al.  In vivo calcium imaging of neural network function. , 2007, Physiology.

[30]  Brendon O. Watson,et al.  SLM Microscopy: Scanless Two-Photon Imaging and Photostimulation with Spatial Light Modulators , 2008, Frontiers in neural circuits.

[31]  Keith J. Kelleher,et al.  Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity , 2008, Nature Neuroscience.

[32]  M. A. Smith,et al.  Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex , 2008, The Journal of Neuroscience.

[33]  Y. Kawaguchi,et al.  Cortical Inhibitory Cell Types Differentially Form Intralaminar and Interlaminar Subnetworks withExcitatory Neurons , 2009, The Journal of Neuroscience.

[34]  Mark T. Waters,et al.  This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits distribution,andreproductioninanymedium,providedtheoriginalauthorandsourcearecredited.Thislicensedoesnot permit commercial exploitation or the creation of derivative works without sp , 2009 .

[35]  S. Shi,et al.  Specific synapses develop preferentially among sister excitatory neurons in the neocortex , 2009, Nature.

[36]  Eric Shea-Brown,et al.  Stimulus-Dependent Correlations and Population Codes , 2008, Neural Computation.

[37]  Rafael Yuste,et al.  Fast nonnegative deconvolution for spike train inference from population calcium imaging. , 2009, Journal of neurophysiology.

[38]  Kristina J. Nielsen,et al.  Targeting Single Neuronal Networks for Gene Expression and Cell Labeling In Vivo , 2010, Neuron.

[39]  Alexander S. Ecker,et al.  Decorrelated Neuronal Firing in Cortical Microcircuits , 2010, Science.

[40]  Benjamin F. Grewe,et al.  High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision , 2010, Nature Methods.

[41]  Alexander S. Ecker,et al.  The Effect of Noise Correlations in Populations of Diversely Tuned Neurons , 2011, The Journal of Neuroscience.

[42]  P. J. Sjöström,et al.  Functional specificity of local synaptic connections in neocortical networks , 2011, Nature.

[43]  Arthur W. Wetzel,et al.  Network anatomy and in vivo physiology of visual cortical neurons , 2011, Nature.

[44]  Arnulf B. A. Graf,et al.  Decoding the activity of neuronal populations in macaque primary visual cortex , 2011, Nature Neuroscience.

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

[46]  R. Reid,et al.  Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex , 2011, The Journal of Neuroscience.

[47]  Balázs Rózsa,et al.  Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes , 2012, Nature Methods.

[48]  Wei Ji Ma,et al.  A Fast and Simple Population Code for Orientation in Primate V1 , 2012, The Journal of Neuroscience.

[49]  C. Clopath,et al.  The emergence of functional microcircuits in visual cortex , 2013, Nature.

[50]  James E. Fitzgerald,et al.  Photon shot noise limits on optical detection of neuronal spikes and estimation of spike timing. , 2013, Biophysical journal.

[51]  Srinivas C. Turaga,et al.  Connectomic reconstruction of the inner plexiform layer in the mouse retina , 2013, Nature.

[52]  Stefan Rotter,et al.  The relevance of network micro-structure for neural dynamics , 2013, Front. Comput. Neurosci..

[53]  Diego Contreras,et al.  The structure of pairwise correlation in mouse primary visual cortex reveals functional organization in the absence of an orientation map. , 2014, Cerebral cortex.