Avalanche Analysis from Multielectrode Ensemble Recordings in Cat, Monkey, and Human Cerebral Cortex during Wakefulness and Sleep

Abstract

Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep, and REM sleep, using high density electrode arrays in cat motor cortex (96 electrodes), monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 160 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs) and in particular LFP negative peaks (nLFPs) among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and premotor cortices). In this case, the avalanches defined from nLFPs displayed power-law scaling in double logarithmic representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using the more reliable cumulative distribution function (CDF) and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey, and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man.

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

“…Moreover, it was shown that power-laws naturally emerge from the random nature of the signal and the thresholding procedure used in this analysis, and moreover these power-laws may not be statistically significant [21]. Indeed, no power-law scaling could be found from unit activity, which were better fit by double-exponential distributions [24]. These analyses rather suggest that the power-law statistics of LFP peaks does not reflect scaleinvariant neural activity.…”

“…It was further shown in that both in data and surrogate models, statistical significance of these power-laws of LFP peak was poor, and depended on the threshold chosen. In [24], Dehghani and collaborators have made a statistical analysis combining multielectrode in vivo recordings from the cerebral cortex of cat, monkey and human, and did not confirm the presence of power-laws. The data rather showed an optimal fit with two independent exponential processes.…”

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

“…Previous in vitro experiments (small scale: Beggs and Plenz, 2003;Shew et al, 2009Shew et al, , 2011Tetzlaff et al, 2010;Friedman et al, 2012) and brain imaging studies (large scale: Tagliazucchi et al, 2012;Haimovici et al, 2013;Yu et al, 2013) provide evidence for other aspects of criticality, including experimentally confirmed predictions of optimal information processing (Shew and Plenz, 2013). These studies suggest that the intact, awake cortex might operate at criticality to take advantage of the associated optimized processing capabilities.…”

Ecological Econophysics for Degrowth

“…Reference [60] gives much evidence in support of this point, but also mentions the results in [62], which might seem to contradict it. However, these results are based on plots of cumulative probabilities, P (X > x).…”

“…max ), which, for finite x max , does not correspond to a straight line in a log-log plot, as assumed in [62]). There also other pieces of evidence that brains are fine-tuned to the critical point of a phase transition [60,63].…”