Entropy Analysis of High-Definition Transcranial Electric Stimulation Effects on EEG Dynamics

Abstract

A foundation of medical research is time series analysis—the behavior of variables of interest with respect to time. Time series data are often analyzed using the mean, with statistical tests applied to mean differences, and has the assumption that data are stationary. Although widely practiced, this method has limitations. Here we present an alternative statistical approach with sample analysis that provides a summary statistic accounting for the non-stationary nature of time series data. This work discusses the use of entropy as a measurement of the complexity of time series, in the context of Neuroscience, due to the non-stationary characteristic of the data. To elucidate our argument, we conducted entropy analysis on a sample of electroencephalographic (EEG) data from an interventional study using non-invasive electrical brain stimulation. We demonstrated that entropy analysis could identify intervention-related change in EEG data, supporting that entropy can be a useful “summary” statistic in non-linear dynamical systems.

BrainWave Nets: Are Sparse Dynamic Models Susceptible to Brain Manipulation Experimentation?

“…Our data thus indicate that the proposed approach may be a promising tool for methodological-analysis toward the treatment of verticality error in stroke patients (Santos-Pontelli et al, 2016;Santos et al, 2018). In previous studies, Nascimento et al (2019) compared HD-tDCS dose-response, adopting the FIGURE 7 | Multiplex EEG signals, per bandpower, (top panels) resting state and (bottom panels) after unilateral HD-tDCS-Anodal Center 2 mA-stimulation. Comparing the resting state vs. post-stimulation, we obtained additional links within the gamma and theta bands during post-stimulus, which suggests an outgrowth in the electrical brain dynamic.…”

“…Thus, this dynamic may be translated/associated with the electrical transferred activity (energetic dissipation). This activity is expected given the rise of entropy through electrical synergy in this area (Nascimento et al, 2019).…”

“…The full trial experimentation lasted ∼120 min. Previously, we discussed (Nascimento et al, 2019) some variations toward the Cathodal against the Active Control (Anodal) at the 2 mA condition; in this work we aimed to discuss an innovative statistical analyses of only one sample of the protocol experimentation compared to its reference (baseline). Thus, in the present study, we analyzed and discussed the data set of a single healthy adult male participant during the resting state (baseline condition) and 45 s after an electrical stimulation.…”

High Definition tDCS Effect on Postural Control in Healthy Individuals: Entropy Analysis of a Crossover Clinical Trial

“…We found the effect was dependent on the cathode center condition with induction of WBA towards the side of brain stimulation [12] with no dependency on the electrical current intensity. Other studies evaluated electroencephalography (EEG) after our HD-tDCS protocol in healthy subjects and suggested entropy (nonlinear outcome) of EEG as a robust alternative for temporal data analysis complementing linear analysis [14].…”

A Novel Recognition Strategy for Epilepsy EEG Signals Based on Conditional Entropy of Ordinal Patterns

“…Seo and Tsuda proposed a new method that was based on the dynamic mode decomposition (DMD) in order to find a distinctive contrast between the ictal and inter-ictal patterns [ 16 ]. When compared with previous time-domain analysis, frequency-domain analysis, and time-frequency analysis [ 17 , 18 ], the entropy based nonlinear analysis method has been applied to characterize brain activities to research the pathophysiological mechanisms underlying the neurological conditions [ 19 , 20 ]. Entropy is a metrics which is different from fractal dimension, and it is a kind of index to measure the probability of new pattern in nonlinear time series.…”