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Convergence and Specificity in Neural and Conceptual Representations of Affect: Investigating Affective Representation across Multiple Levels of Analysis

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Title: Convergence and Specificity in Neural and Conceptual Representations of Affect: Investigating Affective Representation across Multiple Levels of Analysis
Authors: Kwon, Mijin
Source: Dartmouth College Ph.D Dissertations
Publisher Information: Dartmouth Digital Commons
Publication Year: 2026
Collection: Dartmouth Digital Commons (Dartmouth College)
Subject Terms: affective neuroscience, construct validity, insula, predictive models, decoding models, emotion concepts, cross-linguistic emotion representation, fMRI, representational similarity analysis, large language models, Cognitive Neuroscience
Description: How do the brain and the mind represent affect? This thesis examines this question across three levels of analysis—individual brain regions, distributed whole-brain patterns, and conceptual structures across languages—using large-scale multi-study and cross-linguistic datasets. The guiding principle is construct validity: testing what our measures and frameworks actually capture across systematic variations in task, context, and population. At the single-region level, a Bayesian mega-analysis of insular cortex across 36 studies reveals domain-general convergence zones in dorsal anterior insula coexisting with domain-selective zones in surrounding regions, organized in a spatial gradient, with distinct neurobiological properties confirmed through coactivation, cytoarchitectonic, and neurotransmitter profiling. At the whole-brain level, evaluation of 29 multivariate predictive models (“brain signatures”) using data from 66 studies reveals that pain signatures show high specificity and generalizability, but aversive and appetitive signatures show bidirectional confusion, with each responding to studies from the other domain that share the stimulus modality of its training data. Reconstructed encoding patterns and data-driven clustering further show that the brain regions underlying these signatures reflect both affective domain and stimulus modality, indicating that whole-brain affective representations are simultaneously shaped by the target construct and sensory context. At the conceptual level, using English and Korean speakers as a case study of cross-linguistic variation, emotion concept representation shows shared global structure alongside language-specific patterns in local organization. However, neither representations derived from large language models nor appraisal features capture these language-specific patterns, aligning more closely with English representation regardless of target language—suggesting that current frameworks do not adequately account for cross-linguistic variation in how emotions are ...
Document Type: Thesis
File Description: application/pdf
Language: unknown
Relation: https://digitalcommons.dartmouth.edu/dissertations/459; https://digitalcommons.dartmouth.edu/context/dissertations/article/1468/viewcontent/thesis_final_unsigned_Kwon.pdf
Availability: https://digitalcommons.dartmouth.edu/dissertations/459
https://digitalcommons.dartmouth.edu/context/dissertations/article/1468/viewcontent/thesis_final_unsigned_Kwon.pdf
Accession Number: edsbas.9685830C
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  Data: Convergence and Specificity in Neural and Conceptual Representations of Affect: Investigating Affective Representation across Multiple Levels of Analysis
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  Data: 2026
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  Data: <searchLink fieldCode="DE" term="%22affective+neuroscience%22">affective neuroscience</searchLink><br /><searchLink fieldCode="DE" term="%22construct+validity%22">construct validity</searchLink><br /><searchLink fieldCode="DE" term="%22insula%22">insula</searchLink><br /><searchLink fieldCode="DE" term="%22predictive+models%22">predictive models</searchLink><br /><searchLink fieldCode="DE" term="%22decoding+models%22">decoding models</searchLink><br /><searchLink fieldCode="DE" term="%22emotion+concepts%22">emotion concepts</searchLink><br /><searchLink fieldCode="DE" term="%22cross-linguistic+emotion+representation%22">cross-linguistic emotion representation</searchLink><br /><searchLink fieldCode="DE" term="%22fMRI%22">fMRI</searchLink><br /><searchLink fieldCode="DE" term="%22representational+similarity+analysis%22">representational similarity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22large+language+models%22">large language models</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Neuroscience%22">Cognitive Neuroscience</searchLink>
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  Data: How do the brain and the mind represent affect? This thesis examines this question across three levels of analysis—individual brain regions, distributed whole-brain patterns, and conceptual structures across languages—using large-scale multi-study and cross-linguistic datasets. The guiding principle is construct validity: testing what our measures and frameworks actually capture across systematic variations in task, context, and population. At the single-region level, a Bayesian mega-analysis of insular cortex across 36 studies reveals domain-general convergence zones in dorsal anterior insula coexisting with domain-selective zones in surrounding regions, organized in a spatial gradient, with distinct neurobiological properties confirmed through coactivation, cytoarchitectonic, and neurotransmitter profiling. At the whole-brain level, evaluation of 29 multivariate predictive models (“brain signatures”) using data from 66 studies reveals that pain signatures show high specificity and generalizability, but aversive and appetitive signatures show bidirectional confusion, with each responding to studies from the other domain that share the stimulus modality of its training data. Reconstructed encoding patterns and data-driven clustering further show that the brain regions underlying these signatures reflect both affective domain and stimulus modality, indicating that whole-brain affective representations are simultaneously shaped by the target construct and sensory context. At the conceptual level, using English and Korean speakers as a case study of cross-linguistic variation, emotion concept representation shows shared global structure alongside language-specific patterns in local organization. However, neither representations derived from large language models nor appraisal features capture these language-specific patterns, aligning more closely with English representation regardless of target language—suggesting that current frameworks do not adequately account for cross-linguistic variation in how emotions are ...
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      – SubjectFull: insula
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      – SubjectFull: large language models
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      – SubjectFull: Cognitive Neuroscience
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      – TitleFull: Convergence and Specificity in Neural and Conceptual Representations of Affect: Investigating Affective Representation across Multiple Levels of Analysis
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