Negative symptoms and resting state functional connectivity: Leveraging ecological momentary assessment and...

Area of Science:

• Neuroscience
• Psychiatry
• Cognitive Science

Background:

• Motivational deficits are common in psychotic and mood disorders.
• Previous research on functional connectivity and motivation is inconsistent, often due to limitations in accounting for individual differences.
• Ecological momentary assessment (EMA) and individual-specific techniques offer promising approaches to address this variability.

Purpose of the Study:

• To investigate the transdiagnostic relationships between motivational deficits and resting-state functional connectivity.
• To explore how individual variability influences these neural-behavioral associations.
• To differentiate the neural underpinnings of motivation and pleasure (MAP) across schizophrenia/schizoaffective disorder, bipolar disorder, major depressive disorder, and healthy controls.

Main Methods:

• 144 participants (schizophrenia/schizoaffective, bipolar, major depressive, controls) completed EMA for MAP and resting-state fMRI scans.
• Individual-specific network connectivity matrices were computed using a template-matching technique.
• Bayesian hierarchical regression models analyzed associations between MAP, within-network connectivity, participation coefficient, and network spatial extent.

Main Results:

• MAP levels varied across diagnostic groups: intact in bipolar and major depressive disorders, elevated in schizophrenia/schizoaffective disorder.
• Positive associations were found between MAP and dorsal attention network connectivity.
• Specific diagnostic differences emerged: ventral attention network participation coefficient in schizophrenia/schizoaffective disorder, salience network connectivity in schizophrenia/schizoaffective disorder, and salience network spatial extent in controls.

Conclusions:

• Attentional processes play a significant role in motivation and pleasure (MAP).
• The neural mechanisms underlying MAP deficits differ across psychiatric diagnoses.
• Accounting for inter-individual variability is crucial for a comprehensive understanding of MAP phenomenology and its neural basis.