Functional Source Separation-Identified Epileptic Network: Analysis Pipeline

Brain Sci. 2022 Sep 1;12(9):1179. doi: 10.3390/brainsci12091179.

Abstract

This proof-of-concept (PoC) study presents a pipeline made by two blocks: 1. the identification of the network that generates interictal epileptic activity; and 2. the study of the time course of the electrical activity that it generates, called neurodynamics, and the study of its functional connectivity to the other parts of the brain. Network identification is achieved with the Functional Source Separation (FSS) algorithm applied to electroencephalographic (EEG) recordings, the neurodynamics quantified through signal complexity with the Higuchi Fractal Dimension (HFD), and functional connectivity with the Directed Transfer Function (DTF). This PoC is enhanced by the data collected before and after neuromodulation via transcranial Direct Current Stimulation (tDCS, both Real and Sham) in a single drug-resistant epileptic person. We observed that the signal complexity of the epileptogenic network, reduced in the pre-Real, pre-Sham, and post-Sham, reached the level of the rest of the brain post-Real tDCS. DTF changes post-Real tDCS were maintained after one month. The proposed approach can represent a valuable tool to enhance understanding of the relationship between brain neurodynamics characteristics, the effects of non-invasive brain stimulation, and epileptic symptoms.

Keywords: Directed Transfer Function (DTF); EEG; Functional Source Separation (FSS); Higuchi Fractal Dimension (HFD); focal epilepsy; transcranial Direct Current Stimulation (tDCS).

Publication types

  • Case Reports

Grants and funding

This research received no external funding.