Similarity and consistency analysis of functional connectivity maps

Abstract

Functional connectivity (FC) refers to statistical relations of activations of distinct neuronal populations without any reference to causal or anatomic connections. One of the problems in FC studies is, to interpret the resultant FC matrix and only few studies in the literature have focused on consistency and temporal variability of FC networks. In this study functional near infrared spectroscopy (fNIRS) signals were recorded from prefrontal cortex (PFC) of 12 healthy subjects during a stroop test. Mutual information was used as a metric to determine functional connectivity between PFC regions. 2D correlation based similarity measure was used as a method to analyze within-subject and inter-subject consistency of FC maps, and how they change in time. How functional integration changes during to stroop test session was also investigated, using a graph-theoretical metric "global efficiency". It was found that within-subject consistency (0:61 0:09) is significantly higher (p < 0:001) than inter-subject consistency (0:28 0:13). Within-subject consistency was not found to be task-specific. Results also revealed that there is a gradual change in FC patterns during stroop session for congruent and neutral tasks, where there is no such trend in the presence of an interference effect (incongruent task). Finally it was found that, the changes in global efficiency of the FC networks during the stroop test session exhibit a parallel trend. One of the results of these findings is that it is feasible to study consistency, intersubject variability and temporal changes in functional connectivity during a cognitive task with fNIRS.|Keywords : Functional Connectivity, fNIRS, Stroop Task, Mutual Information, Interference, Graph Theory.