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Emotion expression through spoken language in Huntington disease
Charlotte Gallezot1, Rachid Riad1, Hadrien Titeux2
1CoML/ENS/CNRS/EHESS/INRIA/PSL Research University, Paris, France; NPI/ENS/INSERM U855/UPEC/PSL Research University, Creteil, France.
Summary
Patients with Huntington's disease (HD) struggle to express emotions vocally and linguistically. Early-stage HD patients and healthy controls show similar, unimpaired emotional expression, suggesting deficits emerge with disease progression.
Area of Science:
- Neuroscience
- Psychology
- Computational Linguistics
Background:
- Huntington's disease (HD) patients exhibit impaired emotion perception.
- Previous research focused on facial emotion expression deficits in HD.
- Limited understanding exists regarding emotion production via spoken language in HD.
Purpose of the Study:
- To investigate emotion expression through voice and language in Huntington's disease (HD).
- To compare emotion expression capabilities between HD patients, pre-manifest HD participants, and healthy controls.
- To evaluate the utility of machine learning models in assessing emotion expression.
Main Methods:
- 115 participants (68 HD patients, 22 pre-manifest HD, 25 controls) were prospectively studied.
- Participants recalled emotional stories (sad, angry, happy, neutral) during interviews.
- Machine learning models assessed vocal and linguistic emotion expression identifiability in a blind design.
Main Results:
- HD patients demonstrated significant difficulties in expressing emotions via voice and language.
- Pre-manifest HD participants and controls exhibited similar, above-chance emotion expression.
- No significant differences in emotion expression were found between pre-manifest HD and healthy controls.
Conclusions:
- Emotional expression deficits in Huntington's disease affect both vocal and linguistic channels.
- Impaired sensori-motor representations of emotions may underlie these deficits, aligning with embodied cognition theories.
- Machine learning offers a reproducible method for assessing emotion expression in clinical populations.
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