Identification of the Cognitive Interference Effect Related to Stroop Stimulation: Using Dynamic Causal Modeling of Effective Connectivity in Functional Near-Infrared Spectroscopy (Fnirs) Publisher



Yousef Pour M¹ ; Masjoodi S¹ ; Fooladi M² ; Jalalvandi M² ; Vosoughi R² ; Vejdani Afkham B² ; Khabiri H² Show Affiliations
Source: Journal of Biomedical Physics and Engineering Published:2020

Abstract

Background: The Stroop test is a well-known model to denote the decline in performance under the incongruent condition, which requires selective attention and control of competitive responses. Functional near-infrared spectroscopy can identify activated brain regions associated with the Stroop interference effect. Objective: This research aims to identify the neural correlates associated with the Stroop tasks within the brain activated regions. Materials and Methods: In this cross sectional study, twelve right-handed healthy controls were investigated by means of a multi-channels fNIRS unit during the execution of the Stroop test. Effective connectivity changes in the prefrontal cortex between Stroop attentional conflict and rest states were calculated using DCM approach to investigate (1) areas known for selective attention and (2) analyze internetwork functional connectivity strength (FCS) by selecting several brain functional networks. Results: The results indicated that an increased activity was recorded in the LDLPFC during incongruent condition, while under neutral condition, the increase in activity was even more pronounced in those areas. Effect of Stroop interference associated with significant consistent causes an increase in the RDLPFC to DMPFC, LDLPFC to DMPFC and LDLPFC to RPFC effective connectivity strengths. Conclusion: This study showed the use of DCM algorithm for fNIRS data with respect to fMRI has provided additional information about the directional connectivity and causal interactions in LPFC networks during a conflict processing. Eventually, high temporal resolution fNIRS can be a promising tool for monitoring functional brain activation under the cognitive paradigms in neurological research and psychotherapy applications. © 2020, Shiraz University of Medical Sciences. All rights reserved.