Dietmar Plenz, Ph.D.
Section on Critical Brain Dynamics, Laboratory of Systems Neuroscience
Complex systems, when poised at the transition between order and disorder, exhibit scale-free, power law dynamics. These critical systems are highly adaptive and flexibly process and store information, which for decades prompted the conjecture that the brain might operate at criticality. Our discovery of neuronal avalanches in superficial layers of cortex in 2001 provided solid experimental evidence that indeed the brain might be critical. The spatio-temporal, synchronized activity patterns of avalanches form a scale-free organization that spontaneously emerges in vitro in slice cultures and acute slices and in vivo in the anesthetized rat. We recently demonstrated that ongoing activity in awake monkeys is composed of neuronal avalanches. This introduces criticality as a precise, quantitative framework of the awake state that allows cortex to expand during development and evolution without fundamental changes in its architecture.
Avalanches are established at the time of superficial cortex layer differentiation, require balanced fast excitation and inhibition, and are regulated via an inverted-U profile of NMDA/dopamine-D1 interaction, well known from cognitive task paradigms, e.g. working memory. Their internal organization forms a small-world topology that combines local diversity with efficient global communication. Neuronal synchronization in the form of avalanches naturally incorporates gamma-oscillations and cascades, e.g., synfire chains. The size and timing of a single avalanche is governed by two fundamental power laws, which are equivalent to those found for other critical systems, e.g. the Gutenberg-Richter law for earthquake sizes and the Omori-law, which describes the occurrences of aftershocks following a main earthquake.
Overall, our results suggest that neuronal avalanches indicate a critical network dynamic at which the cortex gains universal properties found at criticality. These properties constitute a novel framework that allows for a precise quantification of cortex function such as the absolute discrimination of pathological from non-pathological synchronization, and the identification of maximal dynamic range for input-output processing.
Dr. Plenz is Chief of the Section on Critical Brain Dynamics in the Intramural Research Program at the NIMH. He attended college at the Universities of Mainz and Tuebingen, Germany. Under the supervision of Prof. Valentino Braitenberg and Ad Aertsen, he received his Ph.D. in 1993 at the Max-Planck Institute of Biological Cybernetics/University Tuebingen, where he pioneered the development of in vitro cortex networks to study the emergence of neuronal population dynamics. During his 3 year postdoctoral fellowship with Stephen T. Kitai at the University of Tennessee, Memphis, he developed advanced cortex-forebrain neuronal cultures that allowed him to identify the mechanisms of distinct activity patterns that characterize normal and abnormal population dynamics in cortex and basal ganglia. Dr. Plenz joined the NIMH as a Tenure-track Investigator in 1999 and was promoted to Senior Investigator with tenure in 2006. His laboratory combines electrophysiological and imaging techniques and neural modeling to study the self-organization of neuronal networks.
- Bellay T, Shew WL, Yu S, Falco-Walter JJ, Plenz D. Selective Participation of Single Cortical Neurons in Neuronal Avalanches. Front Neural Circuits. 2020;14:620052.
- Ribeiro TL, Chialvo DR, Plenz D. Scale-Free Dynamics in Animal Groups and Brain Networks. Front Syst Neurosci. 2020;14:591210.
- Bowen Z, Winkowski DE, Seshadri S, Plenz D, Kanold PO. Neuronal Avalanches in Input and Associative Layers of Auditory Cortex. Front Syst Neurosci. 2019;13:45.
- Martin DA, Ribeiro TL, Cannas SA, Grigera TS, Plenz D, Chialvo DR. Box scaling as a proxy of finite size correlations. Sci Rep. 2021;11(1):15937.
- Chialvo DR, Cannas SA, Grigera TS, Martin DA, Plenz D. Controlling a complex system near its critical point via temporal correlations. Sci Rep. 2020;10(1):12145.
Related Scientific Focus Areas
Biomedical Engineering and Biophysics
This page was last updated on Sunday, September 5, 2021