内表型
双相情感障碍
心理学
相关性
内科学
听力学
混淆
前额叶皮质
人口统计学的
临床心理学
医学
精神科
认知
几何学
社会学
人口学
数学
作者
Ramkumar Segar,Harleen Chhabra,Vanteemar S. Sreeraj,Rujuta Parlikar,Vijay Kumar,Ganesan Venkatasubramanian,Kesavan Muralidharan
标识
DOI:10.1016/j.jad.2020.12.153
摘要
Facial emotion recognition (FER) deficit is documented in many psychiatric disorders, including bipolar disorder (BD). However, its role as a risk-marker in BD is not well researched. In the present study, we investigated the role of FER and the corresponding prefrontal neurohemodynamic changes (PNHC) with functional near infra-red spectroscopy (fNIRS) in patients with BD and subjects at high risk for BD compared to healthy subject. Using a cross-sectional case-control design we compared 14 patients with first episode mania (FEM) in remission (BD group), 14 healthy siblings of BD patients (HR group), and 13 matched healthy subjects (HC group). FER was assessed using a computer-based task called Tool for Recognition of Emotions in Neuropsychiatric Disorders (TRENDS). Simultaneously, the corresponding PNHC was recorded with fNIRS. Kruskal Wallis H test was used to analyze between-group differences and Spearman's rho for correlation analysis. The three groups were comparable on socio-demographics (all p>0.09) except education (p = 0.03). HR group had the most hyper-activation in the bilateral DLPFC during the TRENDS task (all p<0.05). There was no significant between-group differences in the FER performance and no significant correlation between the FER performance and the PNHC in the HR and BD groups (all p>0.35). The potential confounding effect of medications in the BD group. The hyper-activation of the DLPCF in HR group during FER could indicate an increased risk for BD. However, the lack of similar findings in the BD group might reflect a possible normalizing effect of medications. It is equally likely that differences in the PNHC are detectable earlier than the differences in FER task performance during the course of the illness. This requires further exploration.
科研通智能强力驱动
Strongly Powered by AbleSci AI