Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates

Area of Science:

• Neuroscience
• Psychology
• Affective Science

Background:

• Physiological responses are often used as proxies for subjective experiences in affective disorders.
• The validity of using physiological
• biosignals
• is questioned due to potential dissociation between subjective and objective measures.

Purpose of the Study:

• To investigate the dissociation between subjective fear and objective physiological responses using machine learning.
• To identify distinct neural correlates for subjective fear versus physiological reactivity.

Main Methods:

• Functional magnetic resonance imaging (fMRI) data was analyzed using machine learning-based whole-brain multivoxel decoders.
• Decoders were trained to predict subjective fear ratings and objective physiological responses separately.

Main Results:

• While correlated, subjective fear and physiological responses exhibited distinct predictive patterns in whole-brain analyses.
• The amygdala and insula were key predictors of physiological reactivity.
• Prefrontal cortex regions associated with metacognition predicted subjective fear experience.

Conclusions:

• Subjective fear and physiological responses are not perfectly aligned, challenging the direct use of biosignals.
• Distinct neural circuits underlie subjective emotional experience and physiological arousal.
• Caution is advised when assuming a one-to-one relationship between subjective distress and objective physiological measures.