Altered spreading of neuronal avalanches in temporal lobe epilepsy relates to cognitive performance: A resting‐state hdEEG study

Abstract

Objective: Large aperiodic bursts of activations named neuronal avalanches have been used to characterize whole-brain activity, as their presence typically relates to optimal dynamics. Epilepsy is characterized by alterations in large-scale brain network dynamics. Here we exploited neuronal avalanches to characterize differences in electroencephalography (EEG) basal activity, free from seizures and/or interictal spikes, between patients with temporal lobe epilepsy (TLE) and matched controls. Method:We defined neuronal avalanches as starting when the z-scored sourcereconstructed EEG signals crossed a specific threshold in any region and ending when all regions returned to baseline. This technique avoids data manipulation or assumptions of signal stationarity, focusing on the aperiodic, scale-free components of the signals. We computed individual avalanche transition matrices to track the probability of avalanche spreading across any two regions, compared them between patients and controls, and related them to memory performance in patients. Results:We observed a robust topography of significant edges clustering in regions functionally and structurally relevant for the TLE, such as the entorhinal cortex, the inferior parietal and fusiform area, the inferior temporal gyrus, and the anterior cingulate cortex. We detected a significant correlation between the centrality of the entorhinal cortex in the transition matrix and the long-term memory performance (delay recall Rey-Osterrieth Complex Figure Test). Significance: Our results show that the propagation patterns of large-scale neuronal avalanches are altered in TLE during the resting state, suggesting a potential diagnostic application in epilepsy. Furthermore, the relationship between specific patterns of propagation and memory performance support the neurophysiological relevance of neuronal avalanches.

Electroencephalographic microstates as a potential neurophysiological marker differentiating bilateral from unilateral temporal lobe epilepsy

“…We observed differences in the temporal dynamic of microstates in most of the classes between patients and controls. This result corroborates the alteration of the intrinsic functional organization in TLE already demonstrated by several studies 12,13,36,37 . Importantly, we detected different patterns of microstate maps in BTLE versus UTLE.…”

“…This result corroborates the alteration of the intrinsic functional organization in TLE already demonstrated by several studies. 12,13,36,37 Importantly, we detected different patterns of microstate maps in BTLE versus UTLE. First, we found an increase in all the components of the microstate Map-A (GEV, MD, TC, FO).…”

“…Converging evidence from magnetoencephalographic and electroencephalographic (EEG) studies has shown how TLE affects the RSNs' dynamic reconfiguration and how the altered functioning was implicated in the pathophysiology of the cognitive impairment. [11][12][13][14] Despite these results and rapid growth in this research field, network behavior discriminating between UTLE and BTLE has been poorly investigated. Microstate analysis based on high-density EEG (hdEEG) recordings may contribute to a better understanding of the temporal dynamics of the physiological large-scale networks.…”

“…The significant advances in noninvasive neuroimaging (e.g., EEG) have improved the characterization of several brain networks with distinct functional signatures in the resting brain, also known as “resting state networks” (RSNs). Converging evidence from magnetoencephalographic and electroencephalographic (EEG) studies has shown how TLE affects the RSNs' dynamic reconfiguration and how the altered functioning was implicated in the pathophysiology of the cognitive impairment 11–14 . Despite these results and rapid growth in this research field, network behavior discriminating between UTLE and BTLE has been poorly investigated.…”

Neuronal Avalanches in Naturalistic Speech and Music Listening

“…In order to further investigate the speech, music and rest conditions, we analyzed the spatiotemporal propagation of neuronal avalanches through the brain. We computed the avalanche transition matrices (ATMs) (22,40), which measure the probability that the activation of channel i results in the activation of channel j at the successive time step (Fig.3.A; see Methods). Hence, for each participant, the ATMs estimate the characteristic pathways through which neuronal avalanches propagate.…”