1. We identified for the first time that neuronal avalanches form the organization of the normal human brain at rest. This study involved magentoencephalography recordings from more than 100 normal human subjects collected at 2 different MEG centers (NIH and Cambridge, UK) using two different MEG systems. This comparative study establishes the platform to link deviations from neuronal avalanches to brain dysfunction as found in e.g. in patients suffering from schizophrenia or Alzheimers disease (Shriki et al., 2013). Abstract: Neuronal Avalanches in the Resting MEG of the Human Brain 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 or resting cortical dynamics are characterized by cascades of activity across many spatial scales, termed neuronal avalanches. In experiment and theory, avalanche dynamics are identified by two measures (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. Here we analyzed resting-state brain activity recorded using non-invasive magnetoencephalography (MEG) from 124 healthy human subjects and two different MEG facilities using different sensor technologies. We identified large deflections at single MEG 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 and coarse-graining of the sensor array. It was absent in phase-shuffled controls with the same power spectrum or empty-scanner data. Our results demonstrate that normal cortical activity in healthy human subjects at rest organizes as neuronal avalanches and is well described by a critical branching process. Theory and experiment have shown that such critical, scale-free dynamics optimize information processing. Thus, our findings imply that the human brain attains an optimal dynamical regime for information processing. 2. Neuronal avalanches identify critical brain dynamics at which several aspects of information processing are optimized as demonstrated in our previous work. Several classes of critical systems have been identified based on the precise critical exponents that control a systems performance at criticality. We identified the critical exponents for the mammalian brain for the first time and suggest that the brain resides in its own universality class. This comparative study was performed on resting activity in the awake macaque monkey using local field potentials and resting activity in normal human subjects using magnetoencephalography (Yu et al., 2013). Abstract: Universal Organization of Resting Brain Activity at the Thermodynamic Critical Point Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian cortex, one type of complex dynamics that spontaneously emerges from neuronal interactions has been characterized as neuronal avalanches. Several aspects of neuronal avalanches such as their size and life time distributions are described by power laws with unique exponents indicative of an underlying critical branching process that governs avalanche formation. Here, we show that neuronal avalanches also reflect an organization of brain dynamics close to a thermodynamic critical point. We recorded spontaneous cortical activity in monkeys and humans at rest using high-density intracranial microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter equivalent to thermodynamic temperature, we observed typical critical behavior in cortical activities near the actual physiological condition, including the phase transition of an order parameter, as well as the divergence of susceptibility and specific heat. Finite-size scaling of these quantities allowed us to derive robust critical exponents highly consistent across monkey and humans that uncover a distinct, yet universal organization of brain dynamics. Our results demonstrate that normal brain dynamics at rest resides near or at criticality which maximizes several aspects of information processing such as input sensitivity and dynamic range. 3. Neuronal avalanches are increasingly recognized to be important for cortex function. My Section took the lead in organizing the first conference on Criticality in Neural Systems in collaboration with Ernst Niebur, Johns Hopkins University. In April 2012, the 2-day conference took place on the NIH campus in Bethesda at the Natcher Conference center with about 100 attendees and featured 19 international and national speakers and posters. Since then, a book with about 22 chapters and international authors, most of who presented at the conference, has been assembled and recently sent to the Publisher Wiley-VCH where it will be published in autumn 2013/spring 2014. The book covers all major aspects of criticality in the brain and is on track to become a standard text book for a rapidly increasing field of critical phenomena in the brain. Besides being the main editor, my Section has contributed 4 chapters covering our major accomplishments demonstrating criticality in the brain from in vitro preparations to the awake animals and normal human subjects. 4. Our work on criticality in the brain is increasingly recognized and results in numerous invited comments on other groups working on criticality in the brain. This is demonstrated by a recent invited Commentary in Physics Highlights, the highest commentary level of the American Physics Society, on critical phenomenal demonstrated in the human brain using fMRI (Plenz 2013).

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Project End
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Budget End
Support Year
12
Fiscal Year
2013
Total Cost
$1,538,458
Indirect Cost
Name
U.S. National Institute of Mental Health
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Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar (2014) Powerlaw: a Python package for analysis of heavy-tailed distributions. PLoS One 9:e85777
Yu, Shan; Klaus, Andreas; Yang, Hongdian et al. (2014) Scale-invariant neuronal avalanche dynamics and the cut-off in size distributions. PLoS One 9:e99761
Shriki, Oren; Alstott, Jeff; Carver, Frederick et al. (2013) Neuronal avalanches in the resting MEG of the human brain. J Neurosci 33:7079-90
Petermann, Thomas; Thiagarajan, Tara C; Lebedev, Mikhail A et al. (2009) Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc Natl Acad Sci U S A 106:15921-6
Pajevic, Sinisa; Plenz, Dietmar (2009) Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches. PLoS Comput Biol 5:e1000271