Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
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Resting functional connectivity in the semantic appraisal network predicts accuracy of emotion identification.

OBJECTIVE: Structural and task-based functional studies associate emotion reading with frontotemporal brain networks, though it remains unclear whether functional connectivity (FC) alone predicts emotion reading ability. The predominantly frontotemporal salience and semantic appraisal (SAN) networks are selectively impacted in neurodegenerative disease syndromes like behavioral-variant frontotemporal dementia (bvFTD) and semantic-variant primary progressive aphasia (svPPA). Accurate emotion identification diminishes in some of these patients, but studies investigating the source of this symptom in patients have predominantly examined structural rather than functional brain changes. Thus, we investigated the impact of altered connectivity on their emotion reading.

METHODS: One-hundred-eighty-five participants (26 bvFTD, 21 svPPA, 24 non-fluent variant PPA, 24 progressive supranuclear palsy, 49 Alzheimer's disease, 41 neurologically healthy older controls) underwent task-free fMRI, and completed the Emotion Evaluation subtest of The Awareness of Social Inference Test (TASIT-EET), watching videos and selecting labels for actors' emotions.

RESULTS: As expected, patients averaged significantly worse on emotion reading, but with wide inter-individual variability. Across all groups, lower mean FC in the SAN, but not other ICNs, predicted worse TASIT-EET performance. Node-pair analysis revealed that emotion identification was predicted by FC between 1) right anterior temporal lobe (RaTL) and right anterior orbitofrontal (OFC), 2) RaTL and right posterior OFC, and 3) left basolateral amygdala and left posterior OFC.

CONCLUSION: Emotion reading test performance predicts FC in specific SAN regions mediating socioemotional semantics, personalized evaluations, and salience-driven attention, highlighting the value of emotion testing in clinical and research settings to index neural circuit dysfunction in patients with neurodegeneration and other neurologic disorders.

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