Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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Tuesday, 30.09.2014 16 s.t.

Monitoring the Balance of Excitation and Inhibition in the Human Brain using Neuronal Avalanches

by Dr. Oren Shriki
from Ben-Gurion University of the Negev, Dept. of Brain and Cognitive Sciences, Computational Psychiatry Lab, Israel

Contact person: Viola Priesemann


MPI DS seminar room (0.77/0.79)


What constitutes normal cortical dynamics in healthy human subjects is a major question in systems neuroscience. Numerous in vitro and in vivo animal studies have shown that ongoing cortical dynamics are characterized by cascades of activity across many spatial scales, termed neuronal avalanches. Avalanche dynamics are identified by (1) a power law in the size distribution of activity cascades, with an exponent of –3/2 and (2) a branching parameter of the critical value of 1, reflecting balanced propagation of activity at the border of premature termination and potential blow up. We analyzed resting-state human brain activity recorded using MEG and EEG. We identified large signal deflections at single sensors and combined them into spatiotemporal cascades on the sensor array, using multiple timescales. Cascade-size distributions obeyed power laws. For the timescale at which the branching parameter was close to 1, the power law exponent was –3/2. This relationship was robust to scaling of the sensor array and was absent in phase-shuffled or empty-scanner data. Using EEG data from sleep deprived subjects we found that the branching parameter and avalanche exponent increase with time awake, reflecting increased dominance of excitation in the underlying network dynamics. We also found strong correlation between avalanche metrics and behavior as measured through reaction times in a psychomotor vigilance task. Similarly, analysis of EEG data from epileptic patients shows deviations in the neuronal avalanche metrics compared to healthy subjects. Our results demonstrate that cortical activity in healthy human subjects at rest organizes as neuronal avalanches and is well described by a critical branching process. Such critical, scale-free dynamics have been shown to optimize information processing, implying that the human brain attains an optimal dynamical regime for information processing. Deviations from the critical balanced state, such as during sleep deprivation or in epilepsy, can be captured by the avalanche metrics and are correlated with behavioral changes.



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