Effective Brain Connectivity for fNIRS With Fuzzy Cognitive Maps in Neuroergonomics

Effective connectivity (EC) among functional near-infrared spectroscopy (fNIRS) signals is a quantitative measure of the strength influence between brain activity associated with different regions brain. Evidently, accurate deciphering EC gives further insight into understanding intricately complex nature neuronal interactions in human This article presents novel approach to estimate using enhanced fuzzy cognitive maps (FCMs). The proposed method regularized methodology FCMs, called effective FCMs (E-FCMs), improved accuracy for predicting real and synthetic fNIRS signals. Essentially, revisions made FCM include more powerful prediction formula combined independent tuning transformation function parameter. A comparison obtained from E-FCM that standard FCM, general linear model (GLM) parameters power dynamic causal modeling (DCM), Granger causality (GC) manifests greater prowess over aforementioned methods. For data, an empirical investigation also gain role oxyhemoglobin deoxy-hemoglobin (oxy-Hb, deoxy-Hb) representing activity. We believe this has profound implications neuroergonomics research communities.