ArticleNeuroImage2022
Classification of emotion categories based on functional connectivity patterns of the human brain.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Oxytocin Reduces Subjective Fear in Naturalistic Social Contexts via Enhancing Top-Down Middle Cingulate Amygdala Regulation and Brain-Wide Fear Representations.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Trial
- Ecologically-Valid Emotion Signatures Enhance Mood Disorder Diagnostics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Intrinsic network static and dynamic functional connectivity associated with induced affect.Social cognitive and affective neuroscience · 2026Article
- Cognitive training at home for clinically defined insomnia: effects on sleep and psychological functioning.Frontiers in digital health · 2026Article
- Article
- It's all connected! Multivariate pattern analysis of inter-network connectivity distinguishes between reappraisal and passive viewing of emotional scenes.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Neural Patterns of Social Pain in the Brain-Wide Representations Across Social Contexts.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Identifying the human olfactory and chemosignaling neural networks using event related fMRI and graph theory.Scientific reports · 2025Article
- Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations.Diagnostics (Basel, Switzerland) · 2025Review
- Cerebral topographies of perceived and felt emotions.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Dissociative Symptoms and Interoceptive Integration.Current topics in behavioral neurosciences · 2025Review
- Functional brain connectivity changes associated with day-to-day fluctuations in affective states.Cognitive, affective & behavioral neuroscience · 2024Article
- Brain mechanisms underlying the modulation of heart rate variability when accepting and reappraising emotions.Scientific reports · 2024Article
- Aberrant degree centrality profiles during rumination in major depressive disorder.Human brain mapping · 2023Article
- Decoding six basic emotions from brain functional connectivity patterns.Science China. Life sciences · 2023Article
- Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs.Cyborg and bionic systems (Washington, D.C.) · 2023Article
- Neural mechanisms of expert persuasion on willingness to pay for sugar.Frontiers in behavioral neuroscience · 2023Article
- Unsupervised classification reveals consistency and degeneracy in neural network patterns of emotion.Social cognitive and affective neuroscience · 2022Article
- State-related neural influences on fMRI connectivity estimation.NeuroImage · 2021Review
- Large-scale functional brain networks for consciousness.Anatomy & cell biology · 2021Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurophysiological and psychological models posit that emotions depend on connections across wide-spread corticolimbic circuits. While previous studies using pattern recognition on neuroimaging data have shown differences between various discrete emotions in brain activity patterns, less is known about the differences in functional connectivity. Thus, we employed multivariate pattern analysis on functional magnetic resonance imaging data (i) to develop a pipeline for applying pattern recognition in functional connectivity data, and (ii) to test whether connectivity patterns differ across emotion categories. Six emotions (anger, fear, disgust, happiness, sadness, and surprise) and a neutral state were induced in 16 participants using one-minute-long emotional narratives with natural prosody while brain activity was measured with functional magnetic resonance imaging (fMRI). We computed emotion-wise connectivity matrices both for whole-brain connections and for 10 previously defined functionally connected brain subnetworks and trained an across-participant classifier to categorize the emotional states based on whole-brain data and for each subnetwork separately. The whole-brain classifier performed above chance level with all emotions except sadness, suggesting that different emotions are characterized by differences in large-scale connectivity patterns. When focusing on the connectivity within the 10 subnetworks, classification was successful within the default mode system and for all emotions. We thus show preliminary evidence for consistently different sustained functional connectivity patterns for instances of emotion categories particularly within the default mode system.
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