Prediction of Individual Melodic Contour Processing in Sensory Association Cortices From Resting State Functional...

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Functional Neuroimaging

Background:

• Recent studies indicate that resting-state functional connectivity (rsFC) can predict individual brain spatial activation patterns during tasks.
• However, the extent to which this prediction holds true across the entire brain remains unclear.

Purpose of the Study:

• To investigate whether individual task activation is best predicted by localized, specialized brain regions or by domain-independent areas.
• To determine if rsFC can predict brain responses to auditory stimuli across the whole brain versus within auditory cortices.

Main Methods:

• Utilized functional magnetic resonance imaging (fMRI) data from participants at rest and during an auditory oddball paradigm.
• Predicted individual differences in brain responses to melodic deviants using rsFC, analyzing both global and local (auditory cortex) parcellations.

Main Results:

• Predictability of individual brain activation from rsFC was consistently higher in sensory association cortices.
• Within the auditory cortex, the right superior temporal gyrus (STG) showed the highest predictability.
• When considering the whole brain, the bilateral visual association cortex emerged as the most predictable network.

Conclusions:

• Individual differences in task-related brain activation can be predicted in both task-relevant specialized areas and general brain regions exhibiting high inter-individual variability.
• Predicting individual task activation from rsFC holds potential clinical relevance, such as informing surgical targets for patients unable to perform specific tasks.