A Comparison of Evoked and Non-evoked Functional Networks

Abstract

The growing interest in brain networks to study the brain’s function in cognition and diseases has produced an increase in methods to extract these networks. Typically, each method yields a different network. Therefore, one may ask what the resulting networks represent. To address this issue we consider electrocorticography (ECoG) data where we compare three methods. We derive networks from on-going ECoG data using two traditional methods: cross-correlation (CC) and Granger causality (GC). Next, connectivity is probed actively using single pulse electrical stimulation (SPES). We compare the overlap in connectivity between these three methods as well as their ability to reveal well-known anatomical connections in the language circuit. We find that strong connections in the CC network form more or less a subset of the SPES network. GC and SPES are related more weakly, although GC connections coincide more frequently with SPES connections compared to non-existing SPES connections. Connectivity between the two major hubs in the language circuit, Broca’s and Wernicke’s area, is only found in SPES networks. Our results are of interest for the use of patient-specific networks obtained from ECoG. In epilepsy research, such networks form the basis for methods that predict the effect of epilepsy surgery. For this application SPES networks are interesting as they disclose more physiological connections compared to CC and GC networks. Electronic supplementary material The online version of this article (10.1007/s10548-018-0692-1) contains supplementary material, which is available to authorized users.

Pathological responses to single‐pulse electrical stimuli in epilepsy: The role of feedforward inhibition

“…Next, based on connectivity analysis of ER networks (Hebbink et al, 2019;van Blooijs et al, 2018), we concluded that DRs are indirect responses to the stimulation. Model simulations show that they may arise from feedforward propagation of ER activity and notably projections to inhibitory populations that normally restrain neural activity.…”

“…We use the detected ERs to construct a network representing effective connectivity (Entz et al., ; Hebbink et al., ; Keller et al., ; van Blooijs et al., ). Each electrode represents a node in this network.…”

“…To systematically detect ERs in our SPES data, we use an automatic detector. This detector is described in detail in the Appendix S1 of Hebbink et al (2019) and has been validated using visually annotated ERs. In short, the responses of an electrode over all ten trials of a stimulation pair are averaged.…”

“…() for an overview). From ERs, directional networks can be constructed (Hebbink et al., ). These networks (partly) explain ipsilateral seizure propagation (Enatsu et al., ; Mouthaan et al., ) in contrast to contralateral seizure spread (Jiménez‐Jiménez et al., ).…”

“…ERs have, therefore, been used to investigate connectivity in several functional regions such as the language area and motor cortex (see Matsumoto et al (2017) for an overview). From ERs, directional networks can be constructed (Hebbink et al, 2019). These networks (partly) explain ipsilateral seizure propagation (Enatsu et al, 2012;Mouthaan et al, 2016) in contrast to contralateral seizure spread (Jiménez-Jiménez et al, 2015).…”