Resting-state brain dynamics characteristics in obsessive-compulsive disorder: A study based on hidden Markov model

Area of Science:

• Neuroscience
• Psychiatry
• Computational Neuroscience

Background:

• Obsessive-compulsive disorder (OCD) pathophysiology remains unclear despite identified functional abnormalities.
• Understanding brain dynamics is crucial for elucidating neural activity mechanisms in complex systems like the brain.

Purpose of the Study:

• To investigate dynamic alterations in resting-state brain activity in OCD patients using hidden Markov modeling (HMM).
• To offer a dynamic perspective on OCD pathophysiology by analyzing brain state transitions and temporal features.

Main Methods:

• Employed hidden Markov modeling (HMM) on resting-state fMRI data from 60 OCD patients and 57 healthy controls (HCs).
• Identified distinct brain states and compared their temporal features and transition patterns between OCD patients and HCs.

Main Results:

• OCD patients spent more time in a state of mildly elevated global activation.
• OCD patients spent less time in a state with high auditory/salience network activation and low default mode/frontoparietal network activation.
• OCD patients exhibited reduced switching rates between brain states and difficulty transitioning into specific states.

Conclusions:

• Altered dynamic brain network activity patterns, including abnormal state occupancy and reduced switching, are characteristic of OCD.
• These dynamic alterations may be linked to salience network dysfunction and cognitive inflexibility in OCD.
• Further research is needed to confirm the specificity and clinical relevance of these findings.