Abstract
This study introduces a framework for the information-theoretic analysis of brain functional connectivity performed at the level of electroencephalogram (EEG) sources. The framework combines the use of common spatial patterns to select the EEG components which maximize the variance between two experimental conditions, simultaneous implementation of vector autoregressive modeling (VAR) with independent component analysis to describe the joint source dynamics and their projection to the scalp, and computation of information dynamics measures (information storage, information transfer, statistically significant network links) from the source VAR parameters. The proposed framework was tested on simulated EEGs obtained mixing source signals generated under different coupling conditions, showing its ability to retrieve source information dynamics from the scalp signals. Then, it was applied to investigate scalp and source brain connectivity in a group of children manifesting episodes of focal and generalized epilepsy; the analysis was performed on EEG signals lasting 5 s, collected in two consecutive windows preceding and one window following each ictal episode. Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics. On the contrary, in the case of focal seizures the scalp EEG activity was not discriminated across conditions by any information measure, while source analysis revealed a tendency of the measures of information transfer to increase just before seizures and to decrease just after seizures. These results suggest that focal epileptic seizures are associated with a reorganization of the topology of EEG brain networks which is only visible analyzing connectivity among the brain sources. Our findings emphasize the importance of EEG modeling approaches able to deal with the adverse effects of volume conduction on brain connectivity analysis, and their potential relevance to the development of strategies for prediction and clinical treatment of epilepsy.
Highlights
The human brain is an extremely large-scale network of neurons, whose function depends on mutual interactions continuously occurring between different sources of neuronal activity
Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics
The scalp analysis remains confounding as the values of information transfer are scattered across the connectivity matrix (Figure 2b), while the source analysis reveals the ability of the proposed framework to elicit the directional interactions that are imposed between the sources
Summary
The human brain is an extremely large-scale network of neurons, whose function depends on mutual interactions continuously occurring between different sources of neuronal activity. Characterization of the brain function is often conducted through the analysis of functional connectivity, which reflects temporal correlations between the brain dynamics of spatially separated regions, and effective connectivity, which describes networks of directional effects of one neural element over another [1] This analysis is applied in particular through processing of electroencephalogram (EEG) signals, which record voltage differences between various locations on the head surface, through measuring the strength of interactions between close or remote brain areas. Estimating connectivity in the epileptic brain may lead to a better understanding of the occurrence and spreading of epileptiform activity, and is of relevance for different research and clinical applications [3,6,7] The importance of such approach is even more strengthened by recent increased evidence of seizure onset not in the entire brain (generalized seizures) or in a circumscribed region of the brain (focal seizures), but within a network of brain regions (the so-called “epileptic network” composed of several functionally connected cortical and subcortical brain structures and regions) [8]
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