Random Recurrent Networks Near Criticality Capture the Broadband Power Distribution of Human ECoG Dynamics

Cerebral Cortex
Rishidev ChaudhuriXiao-Jing Wang

Abstract

Brain electric field potentials are dominated by an arrhythmic broadband signal, but the underlying mechanism is poorly understood. Here we propose that broadband power spectra characterize recurrent neural networks of nodes (neurons or clusters of neurons), endowed with an effective balance between excitation and inhibition tuned to keep the network on the edge of dynamical instability. These networks show a fast mode reflecting local dynamics and a slow mode emerging from distributed recurrent connections. Together, the 2 modes produce power spectra similar to those observed in human intracranial EEG (i.e., electrocorticography, ECoG) recordings. Moreover, such networks convert spatial input correlations across nodes into temporal autocorrelation of network activity. Consequently, increased independence between nodes reduces low-frequency power, which may explain changes observed during behavioral tasks. Lastly, varying network coupling causes activity changes that resemble those observed in human ECoG across different arousal states. The model links macroscopic features of empirical ECoG power to a parsimonious underlying network structure, and suggests mechanisms for changes observed across behavioral and arousal states. Th...Continue Reading

References

Aug 18, 2018·The European Journal of Neuroscience·Efstratios K KosmidisFotios K Diakonos
Feb 24, 2019·Cerebral Cortex·Michael OkunKenneth D Harris
Jul 29, 2020·ELife·Janna D LendnerRobert T Knight
May 3, 2020·Proceedings of the National Academy of Sciences of the United States of America·Christian Meisel
Aug 21, 2020·Proceedings of the National Academy of Sciences of the United States of America·Ryan V RautMarcus E Raichle

Citations

Jan 1, 1990·Physiological Reviews·N BirbaumerB Rockstroh
Nov 1, 1973·Electroencephalography and Clinical Neurophysiology·C S Rebert
Mar 1, 1996·Cerebral Cortex·C KochI Segev
Sep 23, 1998·Neural Computation·B Ermentrout
Jul 27, 1987·Physical Review Letters·P BakK Wiesenfeld
Dec 5, 2000·International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology·A von Stein, J Sarnthein
Aug 27, 2002·Neuron·Frances S ChanceAlex D Reyes
Dec 6, 2002·Cerebral Cortex·Vernon B Mountcastle
Sep 3, 2003·Nature Reviews. Neuroscience·Alain DestexheDenis Paré
Sep 27, 2003·Neural Computation·Oren ShrikiHaim Sompolinsky
Dec 8, 2004·Psychonomic Bulletin & Review·Eric-Jan WagenmakersRoger Ratcliff
Feb 25, 2005·Nature·Yumiko YoshimuraEdward M Callaway
Mar 2, 2005·PLoS Biology·Sen SongDmitri B Chklovskii
Jul 19, 2005·Annual Review of Neuroscience·Tim P VogelsL F Abbott
Oct 1, 2005·Science·Marcello MassiminiGiulio Tononi
Apr 6, 2006·Quality & Safety in Health Care·S NuñezA Aguirre-Jaime
Jul 14, 2006·Nature·Leigh R HochbergJohn P Donoghue
Oct 10, 2006·Physical Review Letters·Claude BédardAlain Destexhe
Dec 13, 2006·Physical Review Letters·Kanaka Rajan, L F Abbott
Feb 6, 2007·Trends in Neurosciences·Dietmar Plenz, Tara C Thiagarajan
Oct 13, 2007·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Sveinung Erland, Priscilla E Greenwood
Apr 11, 2008·Neuron·Surya GanguliKenneth D Miller
Oct 10, 2008·Proceedings of the National Academy of Sciences of the United States of America·Biyu J HeMarcus E Raichle
Oct 17, 2008·Proceedings of the National Academy of Sciences of the United States of America·Huaixing WangWen-Jun Gao
Nov 13, 2008·Cognitive Neurodynamics·Walter J Freeman, Jian Zhai
Feb 5, 2009·PloS One·Joshua MilsteinChristof Koch
Mar 13, 2009·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Kai J MillerJeffrey G Ojemann
Apr 8, 2009·Biophysical Journal·Claude Bédard, Alain Destexhe
Apr 30, 2009·Annual Review of Neuroscience·Pascal Fries
Jun 19, 2009·Trends in Cognitive Sciences·Biyu J He, Marcus E Raichle
Aug 8, 2009·Physical Review Letters·Marcelo O MagnascoGuillermo A Cecchi
Oct 30, 2009·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Jeremy R ManningMichael J Kahana
Oct 31, 2009·Neuron·Kevin Whittingstall, Nikos K Logothetis
Nov 17, 2009·Nature Neuroscience·Marlene R Cohen, John H R Maunsell
Dec 19, 2009·PLoS Computational Biology·Kai J MillerMarcel den Nijs
Jan 16, 2010·Frontiers in Human Neuroscience·Julie Onton, Scott Makeig
Mar 30, 2010·Cerebral Cortex·Zizhen Zhang, Philippe Séguéla
May 5, 2010·Proceedings of the National Academy of Sciences of the United States of America·Marieke L SchölvinckDavid A Leopold
May 27, 2010·Journal of Computational Neuroscience·Henrik LindénGaute T Einevoll

Related Concepts

Brain Diseases
Electroencephalography
Electrocochleography
Neurons
Spatial Distribution
Brain
Arousal
Anti-Arrhythmia Agents
Neural Network Simulation
Intracranial

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