Neuronal Ensemble Synchrony during Human Focal Seizures

Abstract

Seizures are classically characterized as the expression of hypersynchronous neural activity, yet the true degree of synchrony in neuronal spiking (action potentials) during human seizures remains a fundamental question. We quantified the temporal precision of spike synchrony in ensembles of neocortical neurons during seizures in people with pharmacologically intractable epilepsy. Two seizure types were analyzed: those characterized by sustained gamma (ϳ40 -60 Hz) local field potential (LFP) oscillations or by spike-wave complexes (SWCs; ϳ3 Hz). Fine (Ͻ10 ms) temporal synchrony was rarely present during gamma-band seizures, where neuronal spiking remained highly irregular and asynchronous. In SWC seizures, phase locking of neuronal spiking to the SWC spike phase induced synchrony at a coarse 50 -100 ms level. In addition, transient fine synchrony occurred primarily during the initial ϳ20 ms period of the SWC spike phase and varied across subjects and seizures. Sporadic coherence events between neuronal population spike counts and LFPs were observed during SWC seizures in high (ϳ80 Hz) gamma-band and during high-frequency oscillations (ϳ130 Hz). Maximum entropy models of the joint neuronal spiking probability, constrained only on single neurons' nonstationary coarse spiking rates and local network activation, explained most of the fine synchrony in both seizure types. Our findings indicate that fine neuronal ensemble synchrony occurs mostly during SWC, not gamma-band, seizures, and primarily during the initial phase of SWC spikes. Furthermore, these fine synchrony events result mostly from transient increases in overall neuronal network spiking rates, rather than changes in precise spiking correlations between specific pairs of neurons.

Ambiguity and nonidentifiability in the statistical analysis of neural codes

“…This modeling approach leads to permutationbased and other inference procedures that are, in some cases, exact (i.e., approximation-free) and thus, sidestep nonidentifiability. Variations on the jitter principle are one example (8,26,(30)(31)(32) that have been applied to a variety of neurophysiological problems (26,(33)(34)(35)(36)(37)(38). Thus, conditional modeling provides an example of a practical and explicit way to model trial-to-trial variability robustly when the scientific goal is to separate neuronal interactions across timescales.…”

Towards Large-Scale, Human-Based, Mesoscopic Neurotechnologies

“…Despite the relatively coarse nature of these recordings compared to single unit data, the achievements have been equally tremendous as those obtained with single cell recordings, and have added significant knowledge to our understanding of human brain function in such critical areas as movement, language, and memory (Engel et al, 2005; Jacobs and Kahana, 2010; Lachaux et al, 2012). Outside of their contribution to basic neuroscience research, both approaches have provided unexpected, but important information about the basic pathophysiological processes underlying human neurological diseases that could not have been observed from recordings carried out outside of the cranium (de Hemptinne et al, 2013; Schevon et al, 2012; Truccolo et al, 2014; Worrell et al, 2012). …”

“…Fully configured surface-penetrating silicon microelectrode arrays have also been used in clinical settings (Chan et al, 2013; Truccolo et al, 2014). However, scaling up microelectrode recordings to cover more than a relatively small area, currently about 1 cm 2 , poses a real challenge.…”

Seizure Prediction: Science Fiction or Soon to Become Reality?

“…Ideally for seizure prediction, we would be able to track micro-scale activity within the cellular networks that are directly implicated in the emergence of a seizure [9,[28][29][30][31][32]. However, we cannot yet implant a sufficiently large number of micro-electrodes to track the coalescence of preseizure, micro-scale events across large regions of the brain; so other strategies are needed.…”

“…In particular, the apparent selftermination of seizures via critical transition [56]; the heterogeneity of single unit activity involved in focal seizures, and synchrony of single unit activity during spike and wave seizures [9,32]; and evidence of an ictal penumbra involved in inhibitory restraint of seizure spread [57]. It is also worth noting briefly that optogenetics studies [33,58] combined with high-resolution recordings may provide a way to disentangle excitatory and inhibitory population activity and develop improved seizure prediction, detection and control [59].…”