Deviations from Critical Dynamics in Interictal Epileptiform Activity

Arviv, Oshrit; Medvedovsky, Mordekhay; Sheintuch, Liron; Goldstein, Abraham; Shriki, Oren

doi:10.1523/jneurosci.0809-16.2016

Cited by 45 publications

(47 citation statements)

References 55 publications

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“…Rapidly accumulating evidence supports the hypothesis that cortical dynamics in humans exhibit scale-invariant features that change with altered states such as sleep deprivation (Meisel et al 2013(Meisel et al , 2017a and epilepsy (Arviv et al 2016). In infants, scale-invariant neuronal activity has been observed in the single-electrode EEG of preterm infants as early as 12 h after birth (Iyer et al 2015).…”

Section: Introductionmentioning

confidence: 93%

Stability of neuronal avalanches and long-range temporal correlations during the first year of life in human infants

et al. 2020

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During infancy, the human brain rapidly expands in size and complexity as neural networks mature and new information is incorporated at an accelerating pace. Recently, it was shown that single-electrode EEG in preterms at birth exhibits scaleinvariant intermittent bursts. Yet, it is currently not known whether the normal infant brain, in particular, the cortex, maintains a distinct dynamical state during development that is characterized by scale-invariant spatial as well as temporal aspects. Here we employ dense-array EEG recordings acquired from the same infants at 6 and 12 months of age to characterize brain activity during an auditory odd-ball task. We show that suprathreshold events organize as spatiotemporal clusters whose size and duration are power-law distributed, the hallmark of neuronal avalanches. Time series of local suprathreshold EEG events display significant long-range temporal correlations (LRTCs). No differences were found between 6 and 12 months, demonstrating stability of avalanche dynamics and LRTCs during the first year after birth. These findings demonstrate that the infant brain is characterized by distinct spatiotemporal dynamical aspects that are in line with expectations of a critical cortical state. We suggest that critical state dynamics, which theory and experiments have shown to be beneficial for numerous aspects of information processing, are maintained by the infant brain to process an increasingly complex environment during development.

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Section: Introductionmentioning

confidence: 93%

Stability of neuronal avalanches and long-range temporal correlations during the first year of life in human infants

et al. 2020

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“…Theory and simulations [31][32][33][34] predict that cascade profiles follow an inverted parabola in critical systems, but it is currently not known whether such a unique avalanche profile guides brain activity. Variable and asymmetric profiles have been reported for neuronal cultures 35,36 , and profiles seem to depend on avalanche duration in humans 18 . Identifying the correct profile of neuronal avalanches will provide insights into the temporal evolution of brain activity, will distinguish between different models of avalanche generation [37][38][39][40] and, importantly, might provide a biomarker given recent findings that profiles predict recovery from brain insults 41,42 .…”

Section: Introductionmentioning

confidence: 95%

“…Equally challenging are recent reports that χ ranges between 1-1. 5 for rodent tissue in vitro 35,36 and in vivo 43 as well as in human MEG 17 , suggestive of non-critical dynamics 38 . A scaling collapse with χ ≅ 2 was recently found in zebrafish whole brain activity 10 , yet it is unknown whether this is the case for mammalian cortex.…”

Section: Introductionmentioning

confidence: 97%

“…The scale-invariant nature of neuronal avalanches describes the firing of nerve cells 8,9 and, at larger scales, captures neuronal population dynamics in zebrafish 10 , nonhuman primates 7,11,12 , and humans [13][14][15][16][17][18] . This supports the idea that the brain might operate close to a critical state [19][20][21][22] where numerous aspects of information processing are optimized [23][24][25][26][27][28][29][30] .…”

Section: Introductionmentioning

confidence: 99%

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The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ–oscillations

Miller

Plenz

2019

Preprint

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Miller et al.The temporal profile of neuronal avalanches 2 ABSTRACT Activity cascades are found in many complex systems. In the cortex, they arise in the form of neuronal avalanches which capture ongoing and evoked neuronal activities at many spatial and temporal scales. The scale-invariant nature of avalanches suggests that the brain is in a critical state, yet predictions from critical theory on the temporal unfolding of avalanches have yet to be confirmed in vivo. Here we show in awake nonhuman primates that the temporal profile of avalanches, which describes how avalanches initiate locally, extend spatially and shrink as they evolve in time, follows a symmetrical, inverted parabola spanning up to hundreds of milliseconds. Parabolas of different durations can be collapsed with a scaling exponent close to 2 supporting critical generational models of neuronal avalanches. Spontaneously emerging, transient γ-oscillations coexist with and modulate these avalanche parabolas thereby providing a temporal segmentation to inherently scale-invariant, critical dynamics. Our results identify avalanches and oscillations as dual principles in the temporal organization of brain activity. Significance StatementThe most common framework for understanding the temporal organization of brain activity is that of oscillations, or "brain waves". In oscillations, distinct physiological frequencies emerge at well-defined temporal scales, dividing brain activity into time segments underlying cortex function. Here, we identify a fundamentally different temporal parsing of activity in cortex. In awake Macaque monkeys, we demonstrate the motif of an inverted parabola that governs the temporal unfolding of brain activity in the form of neuronal avalanches. This symmetrical motif is scale-invariant, that is, it is not tied to time segments, and exhibits a scaling exponent close to 2 in line with prediction from theory of critical systems. We suggest that oscillations provide a Miller et al.The temporal profile of neuronal avalanches 3 transient "wrinkle" of regularity in an otherwise scale-invariant temporal organization pervading cortical activity at numerous scales.

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“…Hence, we hypothesized that the resting epileptic brain deviates from the healthy critical state. In particular, epileptogenic areas tend to exhibit higher excitability compared with "healthy" regions (Beggs and Plenz, 2003;Monto et al, 2007;Arviv et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy

Courtiol¹,

Guye²,

Bartolomei³

et al. 2020

J. Neurosci.

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Drug-resistant focal epilepsy is a large-scale brain networks disorder characterized by altered spatiotemporal patterns of functional connectivity (FC), even during interictal resting state (RS). Although RS-FC-based metrics can detect these changes, results from RS functional magnetic resonance imaging (RS-fMRI) studies are unclear and difficult to interpret, and the underlying dynamical mechanisms are still largely unknown. To better capture the RS dynamics, we phenomenologically extended the neural mass model of partial seizures, the Epileptor, by including two neuron subpopulations of epileptogenic and nonepileptogenic type, making it capable of producing physiological oscillations in addition to the epileptiform activity. Using the neuroinformatics platform The Virtual Brain, we reconstructed 14 epileptic and 5 healthy human (of either sex) brain network models (BNMs), based on individual anatomical connectivity and clinically defined epileptogenic heatmaps. Through systematic parameter exploration and fitting to neuroimaging data, we demonstrated that epileptic brains during interictal RS are associated with lower global excitability induced by a shift in the working point of the model, indicating that epileptic brains operate closer to a stable equilibrium point than healthy brains. Moreover, we showed that functional networks are unaffected by interictal spikes, corroborating previous experimental findings; additionally, we observed higher excitability in epileptogenic regions, in agreement with the data. We shed light on new dynamical mechanisms responsible for altered RS-FC in epilepsy, involving the following two key factors: (1) a shift of excitability of the whole brain leading to increased stability; and (2) a locally increased excitability in the epileptogenic regions supporting the mixture of hyperconnectivity and hypoconnectivity in these areas.

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Deviations from Critical Dynamics in Interictal Epileptiform Activity

Cited by 45 publications

References 55 publications

Stability of neuronal avalanches and long-range temporal correlations during the first year of life in human infants

Stability of neuronal avalanches and long-range temporal correlations during the first year of life in human infants

The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ–oscillations

Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy

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