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Decoding Six Basic Emotions From Functional Brain Connectivity Patterns

Published in Brain/Neurology.

Summary: Whole brain functional connectivity patterns successfully classified six basic emotions from neutral expressions.

Source: Science China Press

Emotions are an important part of human intelligence. Identifying specific emotional categories from complex neural patterns (i.e., the neural decoding of emotional information) is a key issue in current emotion research.

The categorial emotion models have suggested a set of basic emotion units (e.g., anger, disgust, fear, happiness, sadness, and surprise) that have specialized and independent neural circuits in the brain to support the expression of different emotional information.

As a result, different brain regions are specifically involved in processing specific basic emotions. In recent years, increasing evidence suggests that the representations of basic emotions may be supported by large-scale functional connectivity (FC) networks in the brain.

Recently, a paper entitled “Decoding six basic emotions from brain functional connectivity patterns” was published online in Science China Life Sciences by Dr. Fang Fang’s group in the School of Psychological and Cognitive Sciences at Peking University.

This study analyzed the neural mechanism of emotional information represented by brain network patterns from a data-driven perspective. By leveraging the sliding window technique and the random forest model, this study constructed the decoding model of emotional brain networks and provided evidence that functional connectivity patterns contained the representational information of basic emotions.