Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches

By Woodrow L. Shew, Hongdian Yang, Shan Yu, Rajarshi Roy, Dietmar Plenz. Journal of Neuroscience, 2010

565 citations recorded by the source corpus.

The repertoire of neural activity patterns that a cortical network can produce constrains the ability of the network to transfer and process information. Here, we measured activity patterns obtained from multisite local field potential recordings in cortex cultures, urethane-anesthetized rats, and awake macaque monkeys. First, we quantified the information capacity of the pattern repertoire of ongoing and stimulus-evoked activity using Shannon entropy. Next, we quantified the efficacy of information transmission between stimulus and response using mutual information. By systematically changing the ratio of excitation/inhibition (E/I) in vitro and in a network model, we discovered that both information capacity and information transmission are maximized at a particular intermediate E/I, at which ongoing activity emerges as neuronal avalanches. Next, we used our in vitro and model results to correctly predict in vivo information capacity and interactions between neuronal groups during ongoing activity. Close agreement between our experiments and model suggest that neuronal avalanches and peak information capacity arise because of criticality and are general properties of cortical networks with balanced E/I.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/85e73529b4ca92b5c9c8b9e4a5b7e522b73cd787

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Citations in the corpus

A free energy principle for a particular physics (2019, background): “This manifests as 1/f noise and the scalefree statistics of sudden (instantonic) processes that conform to Zipf's law; e.g., earthquakes, neuronal avalanches, solar flare etc., (Beggs and Plenz, 2003; Kauffman and Johnsen, 1991; Newman, 2005; Plenz and Thiagarajan, 2007; Shew et al., 2011).”
Self-organized criticality as a fundamental property of neural systems (2014, background): “…such as activity-dependent rewiring (Bornholdt and Beggs and Plenz, 2003; Mazzoni et al., 2007; Gireesh and Plenz, 2008; Pasquale et al., 2008; Shew et al., 2009, 2011; Yang et al., 2012, intact leech ganglia, Mazzoni et al., 2007, and anesthetized rats, Osorio et al., 2010), with enhanced…”
Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems (2014, unknown): “[149] W.”
Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “mation between sender and receiver) at criticality (Beggs and Plenz, 2003; Greenfield and Lecar, 2001): This prediction was also later observed in vitro (Shew et al., 2011) and more recently in awake, behaving mice (Fagerholm et al.”
Consciousness as a phenomenon in the operational architectonics of brain organization: Criticality and self-organization considerations (2013, background): “Recently it has been confirmed that neuronal avalanches do indeed provide optimal conditions for mutual information transfer between stimulus and response [226] and allow the realization of a large diversity of activity patterns [201,227].”
Being Critical of Criticality in the Brain (2012, background): “just communication that would be optimized at the critical point (Beggs and Plenz, 2003; Bertschinger and Natschlager, 2004; Maass et al., 2004; Ramo et al., 2007; Tanaka et al., 2009; Chialvo, 2010; Shew et al., 2011).”
Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis (2012, background): “…avalanches of activity raises the question of the physiologically relevance encoded in the timing of these largescale events, already suggested by observations at smaller scales and computational models (Kinouchi and Copelli, 2006; Shew et al., 2009, 2011; de Arcangelis and Herrmann, 2010).”