Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task

Jan 25, 2024Journal of affective disorders

Brain wave patterns during response control help early identification of bipolar versus unipolar depression in a Go/No-Go task

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Abstract

Patients with bipolar disorder exhibited approximately 80% accuracy in distinguishing their neural activity from those with unipolar disorder.

Response inhibition is linked to alterations in neural circuits in mood disorders.
Patients with bipolar disorder showed reduced connectivity between the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA).
Bipolar disorder patients had lower beta power and higher peak frequency compared to unipolar disorder patients.
Delayed activity in the rIFG was observed in bipolar disorder, indicating a specific abnormality.
Neuronal activity during response inhibition may serve as an early diagnostic biomarker for bipolar disorder.

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BACKGROUND: Response inhibition is a key neurocognitive factor contributing to impulsivity in mood disorders. Here, we explored the common and differential alterations of neural circuits associated with response inhibition in bipolar disorder (BD) and unipolar disorder (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 initially diagnosed with UD who later underwent diagnostic conversion to BD, 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.

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. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80 %.

CONCLUSIONS: The inefficiency of the prefrontal control network is a shared mechanism in mood disorders, while the abnormal activity of rIFG is more specific to BD. Neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.

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Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task

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