Decoding Neural Signatures of Semantic Evaluation in Depression and Suicidality.

Depression and suicidality profoundly impact cognition and emotion, yet objective neurophysiological biomarkers remain elusive. We investigated the spatiotemporal neural dynamics underlying affective semantic processing in individuals with varying levels of clinical severity of depression and suicidality using multivariate decoding of electroencephalography (EEG) data. Participants (N=137) completed a sentence evaluation task involving emotionally charged self-referential statements while EEG was recorded. We identified robust, neural signatures of semantic processing, with peak decoding accuracy between 300-600 ms - a window associated with automatic semantic evaluation and conflict monitoring. Compared to healthy controls, individuals with depression and suicidality showed earlier onset, longer duration, and greater amplitude decoding responses, along with broader cross-temporal generalization and increased activation of frontocentral and parietotemporal components. These findings suggest altered sensitivity and impaired disengagement from emotionally salient content in the clinical groups, advancing our understanding of the neurocognitive basis of mental health and providing a principled basis for developing reliable EEG-based biomarkers of depression and suicidality.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2025-07-30
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Decoding Neural Signatures of Semantic Evaluation in Depression and Suicidality.

Shrikanth Narayanan, Assal Habibi, Takfarinas Medani, B. Rael Cahn et al.
PubMed
Mental Health Research Topics
article

Decoding Neural Signatures of Semantic Evaluation in Depression and Suicidality.

Shrikanth Narayanan, Assal Habibi, Takfarinas Medani, B. Rael Cahn, Aditya Kommineni, Dimitrios Pantazis, Thomas McGee, Woojae Jeong, Dani Byrd, Kleanthis Avramidis, Kristina Lerman, Richard M. Leahy, Idan Blank, Donald A. Berry, Myzelle Hughes, Elsi Kaiser, Sudarsana Reddy Kadiri, Cara McDaniel
article en

Abstract

Depression and suicidality profoundly impact cognition and emotion, yet objective neurophysiological biomarkers remain elusive. We investigated the spatiotemporal neural dynamics underlying affective semantic processing in individuals with varying levels of clinical severity of depression and suicidality using multivariate decoding of electroencephalography (EEG) data. Participants (N=137) completed a sentence evaluation task involving emotionally charged self-referential statements while EEG was recorded. We identified robust, neural signatures of semantic processing, with peak decoding accuracy between 300-600 ms - a window associated with automatic semantic evaluation and conflict monitoring. Compared to healthy controls, individuals with depression and suicidality showed earlier onset, longer duration, and greater amplitude decoding responses, along with broader cross-temporal generalization and increased activation of frontocentral and parietotemporal components. These findings suggest altered sensitivity and impaired disengagement from emotionally salient content in the clinical groups, advancing our understanding of the neurocognitive basis of mental health and providing a principled basis for developing reliable EEG-based biomarkers of depression and suicidality.

PubMed
University of Southern California (US), McGovern Institute for Brain Research (US), University of California, Los Angeles (US), Massachusetts Institute of Technology (US), Southern States University (US)
Openalex Percentile: Top 79%
Mental Health Research Topics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.