Neural Oscillatory Patterns Show Reliable Early Identification of Bipolar from Unipolar Depression
Poster No:
605
Submission Type:
Abstract Submission
Authors:
Yi Xia1, Xiaoqin Wang1, Lingling Hua1, Zhilu Chen1, Yingying Huang1, Moxuan Song1, Zhijian Yao1
Institutions:
1The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
First Author:
Co-Author(s):
Introduction:
Response inhibition is a key neurocognitive factor contributing to impulsivity in bipolar disorder (BD) and unipolar disorder (UD). However, the neurological mechanism under response inhibition impairment is unclear in mood disorders. We explored the common and differential alterations of neural circuits associated with response inhibition in BD and UD and whether the oscillatory signatures can be used as early biomarkers in BD.
Methods:
39 patients with BD, 36 patients with UD, 29 patients who were initially diagnosed as UD and then transformed into BD (tBD), and 36 healthy controls performed a Go/No-Go task during MEG scanning. We carried out time-frequency and connectivity analysis on MEG data. Further, we performed machine learning using oscillatory features as input to identify bipolar from unipolar depression at the early clinical stage.
·Diagram of the processing flow
Results:
Compared to healthy controls, patients had reduced rIFG-to-pre-SMA connectivity and delayed activity of rIFG. Among patients, lower beta power and higher peak frequency were observed in BD patients than in UD patients. Motor impulsivity was related to power and latency of activity in rIFG and strength of functional connectivity between rIFG and pre-SMA. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80%.
·Group difference in time-frequency response
Conclusions:
The inefficiency of the prefrontal control network is a shared mechanism of response inhibition impairment in mood disorders, while the abnormal activity of rIFG is more special to BD. Our findings demonstrate that neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis
Novel Imaging Acquisition Methods:
MEG 2
Physiology, Metabolism and Neurotransmission :
Neurophysiology of Imaging Signals
Keywords:
Cognition
MEG
Psychiatric Disorders
1|2Indicates the priority used for review