Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease

心理学 认知 焦虑 脑电图 默认模式网络 萧条(经济学) 神经科学 帕金森病 联想(心理学) 疾病 大脑活动与冥想 听力学 精神科 医学 内科学 经济 心理治疗师 宏观经济学
作者
Kartik K. Iyer,Tiffany R. Au,Anthony J. Angwin,David A. Copland,N. Dissanayaka
出处
期刊:Journal of Affective Disorders [Elsevier BV]
卷期号:277: 875-884 被引量:12
标识
DOI:10.1016/j.jad.2020.08.086
摘要

The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response. 70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups. A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age. This study only reports on optimal dosage of dopaminergic treatment (‘on’ state) in PD and did not investigate at “off” medication”. Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.
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