The relevant resting-state brain activity of ecological microexpression recognition test (EMERT)

Area of Science:

• Neuroscience
• Psychology
• Cognitive Science

Background:

• The ecological microexpression recognition test (EMERT) previously lacked diverse models and brain activity analysis.
• Existing research did not explore the neural correlates of microexpression recognition using fMRI.

Purpose of the Study:

• To improve the ecological validity of EMERT by incorporating diverse ethnic models.
• To investigate the brain activity associated with microexpression recognition using resting-state fMRI.
• To identify neural predictors for microexpression recognition performance.

Main Methods:

• Enhanced EMERT materials with white, black, and yellow models for microexpressions and backgrounds.
• Utilized eyes-closed and eyes-open resting-state functional magnetic resonance imaging (fMRI).
• Analyzed Amplitude of Low-Frequency Fluctuations (ALFFs) to predict microexpression recognition scores (M and SD).

Main Results:

• The improved EMERT demonstrated good reliability and validity, with significant background effects on recognition.
• ALFFs in resting-states and their differences predicted microexpression recognition scores (M and SD).
• Identified specific frontal, insula, cingulate, and other brain regions involved in microexpression recognition.

Conclusions:

• The enhanced EMERT is a valid tool for assessing microexpression recognition.
• Resting-state brain activity, particularly ALFFs, can predict microexpression recognition performance.
• Targeted training of identified brain areas may enhance microexpression recognition abilities.