In-Scanner Thoughts shape Resting-state Functional Connectivity: how participants "rest" matters

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Psychiatry

Background:

• Resting-state functional connectivity (rs-FC) analysis is crucial for identifying brain alterations in clinical populations.
• Standard preprocessing controls for confounds like motion and demographics, but not subjective experience.

Purpose of the Study:

• To investigate the impact of in-scanner subjective experience on rs-FC measures.
• To determine if rs-FC can predict specific aspects of in-scanner experience.

Main Methods:

• Analysis of 471 resting-state fMRI (rs-fMRI) scans with associated experiential data.
• Statistical comparison of FC patterns based on reported in-scanner experiences.
• Machine learning models to predict experiential aspects from FC data.

Main Results:

• Significant widespread differences in rs-FC were observed between scans with varying in-scanner experiences.
• rs-FC successfully predicted demographic, cognitive, and clinical variables, similar to its predictive power for subjective experience.

Conclusions:

• In-scanner experience is a critical factor influencing rs-fMRI derived FC.
• Future rs-fMRI studies must account for subjective states to improve interpretability and reduce confounds.