Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex

Abstract

Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state. In this work, we examine two potential scenarios of seizure generation: (i) epileptic cortical areas might generally operate closer to instability, which would make epilepsy patients generally more susceptible to seizures, or (ii) epileptic cortical areas might drift systematically towards instability before seizure onset. We analyzed single-unit spike recordings from both the epileptogenic (focal) and the nonfocal cortical hemispheres of 20 epilepsy patients. We quantified the distance to instability in the framework of criticality, using a novel estimator, which enables an unbiased inference from a small set of recorded neurons. Surprisingly, we found no evidence for either scenario: Neither did focal areas generally operate closer to instability, nor were seizures preceded by a drift towards instability. In fact, our results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians.

arXiv comment19 pages, 8 Figures

References in corpus (16)

• Optimal Dynamical Range of Excitable Networks at Criticality
• Colloquium: Criticality and dynamical scaling in living systems
• Criticality in the brain: A synthesis of neurobiology, models and cognition
• Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle
• Failure of adaptive self-organized criticality during epileptic seizure attacks
• Room-Temperature Terahertz Anomalous Hall Effect in Weyl Antiferromagnet Mn${}_3$Sn Thin Films
• Distributions of covariances as a window into the operational regime of neuronal networks
• Two types of criticality in the brain
• Inferring collective dynamical states from widely unobserved systems
• Subsampling scaling: a theory about inference from partly observed systems
• Between perfectly critical and fully irregular: a reverberating model captures and predicts cortical spike propagation
• No evidence for critical slowing down prior to human epileptic seizures
• Homeostatic plasticity and external input shape neural network dynamics
• Antiepileptic drugs induce subcritical dynamics in human cortical networks
• Dynamic Adaptive Computation: Tuning network states to task requirements
• MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity

Cited by in corpus (2)

• Self-organization toward criticality by synaptic plasticity
• MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity