Shaping the Default Activity Pattern of the Cortical Network

Slow oscillations have been suggested as the default emergent activity of the cortical network. This is a low complexity state that integrates neuronal, synaptic, and connectivity properties of the cortex. Shaped by variations of physiological parameters, slow oscillations provide information about the underlying healthy or pathological network. We review how this default activity is shaped, how it acts as a powerful attractor, and how getting out of it is necessary for the brain to recover the levels of complexity associated with conscious states. We propose that slow oscillations provide a robust unifying paradigm for the study of cortical function.

[1]  G. Tononi,et al.  Stratification of unresponsive patients by an independently validated index of brain complexity , 2016, Annals of neurology.

[2]  D. McCormick,et al.  Neocortical Network Activity In Vivo Is Generated through a Dynamic Balance of Excitation and Inhibition , 2006, The Journal of Neuroscience.

[3]  G. Tononi,et al.  Triggering sleep slow waves by transcranial magnetic stimulation , 2007, Proceedings of the National Academy of Sciences.

[4]  W. Wadman,et al.  Homeostatic scaling of neuronal excitability by synaptic modulation of somatic hyperpolarization-activated Ih channels. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[5]  M. Steriade,et al.  A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[6]  Hans Förstl,et al.  Rescue of long-range circuit dysfunction in Alzheimer's disease models , 2015, Nature Neuroscience.

[7]  J. Gibson,et al.  Altered Neocortical Rhythmic Activity States in Fmr1 KO Mice Are Due to Enhanced mGluR5 Signaling and Involve Changes in Excitatory Circuitry , 2011, The Journal of Neuroscience.

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

[9]  B. Richmond,et al.  Intrinsic dynamics in neuronal networks. I. Theory. , 2000, Journal of neurophysiology.

[10]  Alain Destexhe,et al.  Self-sustained Asynchronous Irregular States and Up–down States in Thalamic, Cortical and Thalamocortical Networks of Nonlinear Integrate-and-fire Neurons , 2022 .

[11]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

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

[13]  Maxim Volgushev,et al.  Properties of Slow Oscillation during Slow-Wave Sleep and Anesthesia in Cats , 2011, The Journal of Neuroscience.

[14]  Joachim Gross,et al.  Perilesional pathological oscillatory activity in the magnetoencephalogram of patients with cortical brain lesions , 2004, Neuroscience Letters.

[15]  Maria V. Sanchez-Vives,et al.  Slow and Fast Neocortical Oscillations in the Senescence-Accelerated Mouse Model SAMP8 , 2017, Front. Aging Neurosci..

[16]  Laura D. Lewis,et al.  Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness , 2012, Proceedings of the National Academy of Sciences.

[17]  P Gloor,et al.  Brain lesions that produce delta waves in the EEG , 1977, Neurology.

[18]  Maria V. Sanchez-Vives,et al.  Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. , 2003, Journal of neurophysiology.

[19]  R. Yuste,et al.  Attractor dynamics of network UP states in the neocortex , 2003, Nature.

[20]  Marcello Massimini,et al.  Sleep homeostasis and cortical synchronization: III. A high-density EEG study of sleep slow waves in humans. , 2007, Sleep.

[21]  G. Tononi,et al.  Sleep and the Price of Plasticity: From Synaptic and Cellular Homeostasis to Memory Consolidation and Integration , 2014, Neuron.

[22]  J. Born,et al.  Slow-wave sleep and the consolidation of long-term memory , 2010, The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry.

[23]  K. Harris,et al.  Laminar Structure of Spontaneous and Sensory-Evoked Population Activity in Auditory Cortex , 2009, Neuron.

[24]  Alain Destexhe,et al.  Neuronal Computations with Stochastic Network States , 2006, Science.

[25]  Maria V. Sanchez-Vives,et al.  Overexpression of Dyrk1A, a Down Syndrome Candidate, Decreases Excitability and Impairs Gamma Oscillations in the Prefrontal Cortex , 2016, The Journal of Neuroscience.

[26]  M. Steriade,et al.  Natural waking and sleep states: a view from inside neocortical neurons. , 2001, Journal of neurophysiology.

[27]  Maria V. Sanchez-Vives,et al.  Exploring the spectrum of dynamical regimes and timescales in spontaneous cortical activity , 2012, Cognitive Neurodynamics.

[28]  D. Prince,et al.  Extracellular potassium activity during epileptogenesis. , 1974, Experimental neurology.

[29]  L. Parra,et al.  Low-Intensity Electrical Stimulation Affects Network Dynamics by Modulating Population Rate and Spike Timing , 2010, The Journal of Neuroscience.

[30]  Andrea Pigorini,et al.  Time–frequency spectral analysis of TMS-evoked EEG oscillations by means of Hilbert–Huang transform , 2011, Journal of Neuroscience Methods.

[31]  Gabriele Arnulfo,et al.  Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep , 2015, NeuroImage.

[32]  Marcello Massimini,et al.  Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients , 2012, Brain : a journal of neurology.

[33]  T. Sejnowski,et al.  Origin of slow cortical oscillations in deafferented cortical slabs. , 2000, Cerebral cortex.

[34]  M. Mattia,et al.  Slow wave activity as the default mode of the cerebral cortex. , 2014, Archives italiennes de biologie.

[35]  Giulio Tononi,et al.  Modeling sleep and wakefulness in the thalamocortical system. , 2005, Journal of neurophysiology.

[36]  G. Tononi,et al.  Source modeling sleep slow waves , 2009, Proceedings of the National Academy of Sciences.

[37]  Maria V. Sanchez-Vives,et al.  Impact of cortical network activity on short-term synaptic depression. , 2006, Cerebral cortex.

[38]  Maria V. Sanchez-Vives,et al.  Cellular and network mechanisms of rhythmic recurrent activity in neocortex , 2000, Nature Neuroscience.

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

[40]  E. Stern,et al.  Pathological Tau Disrupts Ongoing Network Activity , 2015, Neuron.

[41]  T R Vidyasagar,et al.  Membrane properties and spike generation in rat visual cortical cells during reversible cooling , 2000, The Journal of physiology.

[42]  A. Grinvald,et al.  Linking spontaneous activity of single cortical neurons and the underlying functional architecture. , 1999, Science.

[43]  M Giugliano,et al.  Single-neuron discharge properties and network activity in dissociated cultures of neocortex. , 2004, Journal of neurophysiology.

[44]  Albert Compte,et al.  Inhibitory modulation of cortical up states. , 2010, Journal of neurophysiology.

[45]  S. Nelson,et al.  Homeostatic plasticity in the developing nervous system , 2004, Nature Reviews Neuroscience.

[46]  Maurizio Mattia,et al.  Diverse population-bursting modes of adapting spiking neurons. , 2007, Physical review letters.

[47]  Albert Compte,et al.  Spontaneous High-Frequency (10–80 Hz) Oscillations during Up States in the Cerebral Cortex In Vitro , 2008, The Journal of Neuroscience.

[48]  Shimon Marom,et al.  Development, learning and memory in large random networks of cortical neurons: lessons beyond anatomy , 2002, Quarterly Reviews of Biophysics.

[49]  E. Brown,et al.  General anesthesia, sleep, and coma. , 2010, The New England journal of medicine.

[50]  Michael Okun,et al.  Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities , 2008, Nature Neuroscience.

[51]  Maria V. Sanchez-Vives,et al.  Temperature modulation of slow and fast cortical rhythms. , 2010, Journal of neurophysiology.

[52]  Maria V. Sanchez-Vives,et al.  Slow and fast rhythms generated in the cerebral cortex of the anesthetized mouse. , 2011, Journal of neurophysiology.

[53]  G. Tononi,et al.  Consciousness and Complexity during Unresponsiveness Induced by Propofol, Xenon, and Ketamine , 2015, Current Biology.

[54]  D. McCormick,et al.  Inhibitory Postsynaptic Potentials Carry Synchronized Frequency Information in Active Cortical Networks , 2005, Neuron.

[55]  S. Hughes,et al.  The slow (<1 Hz) rhythm of non-REM sleep: a dialogue between three cardinal oscillators , 2010, Nature Neuroscience.

[56]  G. Tononi,et al.  A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior , 2013, Science Translational Medicine.

[57]  Jochen Braun,et al.  Attractors and noise: Twin drivers of decisions and multistability , 2010, NeuroImage.

[58]  S. Andersson,et al.  Physiological basis of the alpha rhythm , 1968 .

[59]  Paul Antoine Salin,et al.  Highly Dynamic Spatiotemporal Organization of Low‐Frequency Activities During Behavioral States in the Mouse Cerebral Cortex , 2016, Cerebral cortex.

[60]  J. Gibson,et al.  Imbalance of neocortical excitation and inhibition and altered UP states reflect network hyperexcitability in the mouse model of fragile X syndrome. , 2008, Journal of neurophysiology.

[61]  D. McCormick,et al.  Endogenous Electric Fields May Guide Neocortical Network Activity , 2010, Neuron.

[62]  Mayank R Mehta,et al.  The Upshot of Up States in the Neocortex: From Slow Oscillations to Memory Formation , 2007, The Journal of Neuroscience.

[63]  Sean L. Hill,et al.  The Sleep Slow Oscillation as a Traveling Wave , 2004, The Journal of Neuroscience.

[64]  G. Tononi,et al.  *Both authors contributed equally to this manuscript. , 2022 .

[65]  James G. King,et al.  Reconstruction and Simulation of Neocortical Microcircuitry , 2015, Cell.

[66]  Maria V. Sanchez-Vives,et al.  Bistability, Causality, and Complexity in Cortical Networks: An In Vitro Perturbational Study , 2017, Cerebral cortex.

[67]  M Steriade,et al.  Low-frequency rhythms in the thalamus of intact-cortex and decorticated cats. , 1996, Journal of neurophysiology.

[68]  Alain Destexhe,et al.  Gain Modulation of Synaptic Inputs by Network State in Auditory Cortex In Vivo , 2015, The Journal of Neuroscience.

[69]  Andrea Hasenstaub,et al.  Persistent cortical activity: mechanisms of generation and effects on neuronal excitability. , 2003, Cerebral cortex.

[70]  G. Tononi,et al.  Breakdown of Cortical Effective Connectivity During Sleep , 2005, Science.

[71]  A. Destexhe,et al.  Are corticothalamic ‘up’ states fragments of wakefulness? , 2007, Trends in Neurosciences.

[72]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[73]  T. Sejnowski,et al.  Model of Thalamocortical Slow-Wave Sleep Oscillations and Transitions to Activated States , 2002, The Journal of Neuroscience.

[74]  Gustavo Deco,et al.  Effective Reduced Diffusion-Models: A Data Driven Approach to the Analysis of Neuronal Dynamics , 2009, PLoS Comput. Biol..

[75]  C. Koch,et al.  Integrated information theory: from consciousness to its physical substrate , 2016, Nature Reviews Neuroscience.

[76]  D. Hovda,et al.  Massive increases in extracellular potassium and the indiscriminate release of glutamate following concussive brain injury. , 1990, Journal of neurosurgery.

[77]  Maria V. Sanchez-Vives,et al.  Collective stochastic coherence in recurrent neuronal networks , 2016, Nature Physics.

[78]  Gustavo Deco,et al.  Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials , 2015, NeuroImage.

[79]  Anthony G Hudetz,et al.  General Anesthesia and Human Brain Connectivity , 2012, Brain Connect..

[80]  Misha Tsodyks,et al.  The Emergence of Up and Down States in Cortical Networks , 2006, PLoS Comput. Biol..

[81]  J. Born,et al.  Boosting slow oscillations during sleep potentiates memory , 2006, Nature.