Network state dynamics underpin basal craving in a transdiagnostic population.

Area of Science:

• Neuroscience
• Psychiatry
• Computational Neuroscience

Background:

• Affective states and their regulation are crucial in psychopathology, but the underlying dynamic brain responses are not well understood.
• Individual differences in affective and motivation states may arise from fluctuations in brain responses.

Purpose of the Study:

• To introduce a novel framework for identifying brain network states associated with affective experiences.
• To investigate how the dynamic engagement of these network states contributes to affective experiences, specifically basal craving.

Main Methods:

• Utilized connectome-based predictive modeling (CPM) to identify brain networks predictive of basal craving in a transdiagnostic sample (N=252).
• Employed an edge-centric time-series approach to quantify moment-to-moment engagement of craving-related subnetworks.
• Replicated findings in an independent dataset (N=173) using distinct participants and stimuli.

Main Results:

• Higher basal craving was associated with greater persistence in craving-positive brain network states.
• Reduced dwelling in craving-negative brain network states also characterized individuals with higher craving.
• These associations were robust and consistent across datasets and network definitions.

Conclusions:

• Dynamic engagement of brain network states significantly underlies individual differences in basal craving.
• The developed framework offers a new method to explore the role of network state dynamics in affective experiences.
• Findings have implications for understanding and potentially treating craving-related disorders.