Spontaneous cortical activity in awake monkeys composed of neuronal avalanches

Abstract

Spontaneous neuronal activity is an important property of the cerebral cortex but its spatiotemporal organization and dynamical framework remain poorly understood. Studies in reduced systems-tissue cultures, acute slices, and anesthetized ratsshow that spontaneous activity forms characteristic clusters in space and time, called neuronal avalanches. Modeling studies suggest that networks with this property are poised at a critical state that optimizes input processing, information storage, and transfer, but the relevance of avalanches for fully functional cerebral systems has been controversial. Here we show that ongoing cortical synchronization in awake rhesus monkeys carries the signature of neuronal avalanches. Negative LFP deflections (nLFPs) correlate with neuronal spiking and increase in amplitude with increases in local population spike rate and synchrony. These nLFPs form neuronal avalanches that are scale-invariant in space and time and with respect to the threshold of nLFP detection. This dimension, threshold invariance, describes a fractal organization: smaller nLFPs are embedded in clusters of larger ones without destroying the spatial and temporal scale-invariance of the dynamics. These findings suggest an organization of ongoing cortical synchronization that is scale-invariant in its three fundamental dimensions-time, space, and local neuronal group size. Such scale-invariance has ontogenetic and phylogenetic implications because it allows large increases in network capacity without a fundamental reorganization of the system. neuronal synchronization ͉ resting state ͉ rhesus monkey ͉ spontaneous activity ͉ ongoing activity T he cerebral cortex displays spontaneous activity, also known as 'ongoing' or 'resting state' activity, which persists in the absence of sensory stimuli or motor outputs. The ongoing activity is a robust feature of cortical dynamics as it is only modulated to a small extent by stimulus presentation (1), but contributes significantly to the large variability observed in stimulus responses (2-5). In fact, ongoing activity has been found to reflect multiple aspects of neuronal processing. The activity is similar to that observed during stimulus presentation (1, 6-8), incorporates previously acquired information (9), and carries information about the underlying neuronal network [for review see (10)]. Indeed, correlations during resting state activity are altered in disease states such as schizophrenia or chronic pain (11, 12), which raises the question whether there is a general framework that describes the statistics in the spatiotemporal organization of this dynamics.Recently, we found that spontaneous cortical activity in slice cultures, acute slices, and in the anesthetized rat in vivo has a scale-invariant dynamics called neuronal avalanches (13)(14)(15). These spontaneous bursts of synchronized activity occur in clusters of sizes s (where s is the number of active sites in an electrode array) that distribute according to a power law with exponent ␣:where ␣ usually lies between ...

Power-law statistics and universal scaling in the absence of criticality

“…These in vitro findings were based on indirect evidences of spiking derived from local field potentials, extracellular signals associated with the summation of postsynaptic potentials (bursts produce negative peaks in the LFP signals) and affected by a number of events unrelated with spiking activity. Similar LFP statistics were later found in vivo in the awake monkey [17] and in the anesthetized rat [18]. These empirical evidences were used to draw strong conclusions on neural coding: the presence such power-laws would ensure maximized information capacity, dynamic range and information transmission [19,20].…”

“…This regime differs from the awake activity where neurons fire in an AI manner. In these regimes, power-laws and criticality were reported based on LFP recordings [17]. We will come back to experimental evidences of power-laws in local-field potentials recordings of the activity in section V.…”

Cerebral Energy Metabolism and the Brain’s Functional Network Architecture: An Integrative Review

“…41 An emerging view that has been extensively adopted in experimental work at the micro-, meso-, and macro-scales expands on biophysical models of synchronous brain function to further state that neural activity is of fractal nature, and that the brain is a self-organized critical system (SOC). [42][43][44] Systems in a critical state are poised on the cusp of a transition between ordered and random behavior, and show complex patterning of fluctuations at all scales of space and time.…”

Mean-field behavior as a result of noisy local dynamics in self-organized criticality: Neuroscience implications

“…Our main motivation is due to the recent observation of neuronal avalanches and their presumed relation to SOC. In a wide range of recent experiments [14][15][16][17][18][19][20][21] , neuronal avalanches have been shown to exhibit power law behavior with mean-field exponents. Whether neural dynamics [22] is dissipative or not is still debated, but their noisy dynamics [23] is a certainty, as the post-synaptic neurons receive more or less than their fair share of the ion distributed by the pre-synaptic neuron in the ionic plasma, which permeates the space between synapses.…”