Decoding individual differences in self-prioritization from the resting-state functional connectome.

Area of Science:

• Neuroscience
• Cognitive Psychology
• Brain Imaging

Background:

• The self is traditionally viewed as a higher-order cognitive function.
• Recent research proposes a fundamental self hypothesis, where the self is a baseline brain function.
• This self function is embedded in spontaneous brain activities, regulating cognition and behavior.

Purpose of the Study:

• To investigate the association between spontaneous neural connectivity and self-biased behavior.
• To determine if resting-state brain signals can predict self-biased behaviors.
• To test the fundamental self hypothesis by examining neural underpinnings of self-bias.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) was used in 348 young adults.
• A support vector regression model decoded whole-brain connectivity patterns to predict self-bias magnitude.
• Results were validated using an external dataset of older adults and computational lesion analyses.

Main Results:

• Spontaneous neural connectivity patterns predicted the magnitude of self-biased behavior.
• Self-biased behavior correlated with specific connections between the default mode, cognitive control, and salience networks.
• Key brain regions involved included the thalamus, extending across six networks.

Conclusions:

• Self-biased behavior originates from spontaneous neural connectivity, supporting the fundamental self hypothesis.
• Distinct functional connectivity patterns underpin self-related processing and behavioral biases.
• An integrated neural network model of the fundamental self is proposed, explaining its emergence at rest and regulation of responses.