Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice

Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics.

[1]  D. Plenz,et al.  The organizing principles of neuronal avalanches: cell assemblies in the cortex? , 2007, Trends in Neurosciences.

[2]  K. Harris,et al.  Cortical state and attention , 2011, Nature Reviews Neuroscience.

[3]  Karel Svoboda,et al.  Neural coding in barrel cortex during whisker-guided locomotion , 2015, eLife.

[4]  Changsong Zhou,et al.  Hierarchical modular structure enhances the robustness of self-organized criticality in neural networks , 2012 .

[5]  D. Chialvo Emergent complex neural dynamics , 2010, 1010.2530.

[6]  John M. Beggs,et al.  Being Critical of Criticality in the Brain , 2012, Front. Physio..

[7]  M. Nicolelis,et al.  Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle , 2010, PloS one.

[8]  Pablo Balenzuela,et al.  Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis , 2012, Front. Physio..

[9]  G. Tononi,et al.  Consciousness and Anesthesia , 2008, Science.

[10]  Nathan C. Klapoetke,et al.  Transgenic Mice for Intersectional Targeting of Neural Sensors and Effectors with High Specificity and Performance , 2015, Neuron.

[11]  David Kleinfeld,et al.  Chronic optical access through a polished and reinforced thinned skull. , 2010, Nature methods.

[12]  C. Koch,et al.  Consciousness: here, there and everywhere? , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[13]  D. Katz,et al.  Behavioral states, network states, and sensory response variability. , 2008, Journal of neurophysiology.

[14]  G. Edelman,et al.  Complexity and coherency: integrating information in the brain , 1998, Trends in Cognitive Sciences.

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

[16]  Walther Akemann,et al.  Imaging brain electric signals with genetically targeted voltage-sensitive fluorescent proteins , 2010, Nature Methods.

[17]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[18]  Woodrow L. Shew,et al.  Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches , 2010, The Journal of Neuroscience.

[19]  William Bialek,et al.  Spikes: Exploring the Neural Code , 1996 .

[20]  Amiram Grinvald,et al.  Arousal increases the representational capacity of cortical tissue , 2009, Journal of Computational Neuroscience.

[21]  Zach D. Haga,et al.  Avalanche Analysis from Multielectrode Ensemble Recordings in Cat, Monkey, and Human Cerebral Cortex during Wakefulness and Sleep , 2012, Front. Physio..

[22]  Walther Akemann,et al.  Imaging neural circuit dynamics with a voltage-sensitive fluorescent protein. , 2012, Journal of neurophysiology.

[23]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[24]  Toru Yanagawa,et al.  Loss of Consciousness Is Associated with Stabilization of Cortical Activity , 2015, The Journal of Neuroscience.

[25]  O. Shriki,et al.  Fading Signatures of Critical Brain Dynamics during Sustained Wakefulness in Humans , 2013, The Journal of Neuroscience.

[26]  Woodrow L. Shew,et al.  Neuronal Avalanches Imply Maximum Dynamic Range in Cortical Networks at Criticality , 2009, The Journal of Neuroscience.

[27]  N. Honkura,et al.  Two-photon voltage imaging using a genetically encoded voltage indicator , 2013, Scientific Reports.

[28]  E. Ott,et al.  Statistical properties of avalanches in networks. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Andreas Klaus,et al.  Irregular spiking of pyramidal neurons organizes as scale-invariant neuronal avalanches in the awake state , 2015, eLife.

[30]  Chris Wiggins,et al.  ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context , 2004, BMC Bioinformatics.

[31]  Woodrow L. Shew,et al.  Predicting criticality and dynamic range in complex networks: effects of topology. , 2010, Physical review letters.

[32]  Woodrow L. Shew,et al.  State-dependent intrinsic predictability of cortical network dynamics , 2015, PLoS Comput. Biol..

[33]  M. Porter,et al.  Critical Truths About Power Laws , 2012, Science.

[34]  Changsong Zhou,et al.  Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations , 2010, Front. Comput. Neurosci..

[35]  James Bailey,et al.  Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance , 2010, J. Mach. Learn. Res..

[36]  Woodrow L. Shew,et al.  Adaptation to sensory input tunes visual cortex to criticality , 2015, Nature Physics.

[37]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[38]  Woodrow L. Shew,et al.  Maximal Variability of Phase Synchrony in Cortical Networks with Neuronal Avalanches , 2012, The Journal of Neuroscience.

[39]  Woodrow L. Shew,et al.  Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics , 2014, The Journal of Neuroscience.

[40]  John M. Beggs,et al.  Neuronal Avalanches in Neocortical Circuits , 2003, The Journal of Neuroscience.