When affect overlaps with concept: emotion recognition in semantic variant of primary progressive aphasia.


Journal

Brain : a journal of neurology
ISSN: 1460-2156
Titre abrégé: Brain
Pays: England
ID NLM: 0372537

Informations de publication

Date de publication:
01 12 2020
Historique:
received: 02 06 2020
revised: 20 07 2020
accepted: 31 07 2020
pubmed: 23 11 2020
medline: 2 3 2021
entrez: 22 11 2020
Statut: ppublish

Résumé

The most recent theories of emotions have postulated that their expression and recognition depend on acquired conceptual knowledge. In other words, the conceptual knowledge derived from prior experiences guide our ability to make sense of such emotions. However, clear evidence is still lacking to contradict more traditional theories, considering emotions as innate, distinct and universal physiological states. In addition, whether valence processing (i.e. recognition of the pleasant/unpleasant character of emotions) also relies on semantic knowledge is yet to be determined. To investigate the contribution of semantic knowledge to facial emotion recognition and valence processing, we conducted a behavioural and neuroimaging study in 20 controls and 16 patients with the semantic variant of primary progressive aphasia, a neurodegenerative disease that is prototypical of semantic memory impairment, and in which an emotion recognition deficit has already been described. We assessed participants' knowledge of emotion concepts and recognition of 10 basic (e.g. anger) or self-conscious (e.g. embarrassment) facial emotional expressions presented both statically (images) and dynamically (videos). All participants also underwent a brain MRI. Group comparisons revealed deficits in both emotion concept knowledge and emotion recognition in patients, independently of type of emotion and presentation. These measures were significantly correlated with each other in patients and with semantic fluency in patients and controls. Neuroimaging analyses showed that both emotion recognition and emotion conceptual knowledge were correlated with reduced grey matter density in similar areas within frontal ventral, temporal, insular and striatal regions, together with white fibre degeneration in tracts connecting frontal regions with each other as well as with temporal regions. We then performed a qualitative analysis of responses made during the facial emotion recognition task, by delineating valence errors (when one emotion was mistaken for another of a different valence), from other errors made during the emotion recognition test. We found that patients made more valence errors. The number of valence errors correlated with emotion conceptual knowledge as well as with reduced grey matter volume in brain regions already retrieved to correlate with this score. Specificity analyses allowed us to conclude that this cognitive relationship and anatomical overlap were not mediated by a general effect of disease severity. Our findings suggest that semantic knowledge guides the recognition of emotions and is also involved in valence processing. Our study supports a constructionist view of emotion recognition and valence processing, and could help to refine current theories on the interweaving of semantic knowledge and emotion processing.

Identifiants

pubmed: 33221846
pii: 5998326
doi: 10.1093/brain/awaa313
pmc: PMC7805810
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3850-3864

Commentaires et corrections

Type : CommentIn

Informations de copyright

© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.

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Auteurs

Maxime Bertoux (M)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.
Univ. Lille, Inserm, CHU Lille, UMRS1172, Lille Neurosciences & Cognition Institute, F-59000 Lille, France.

Harmony Duclos (H)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.
CRP-CPO, Picardy Jules Verne University, Amiens, France.

Marie Caillaud (M)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.

Shailendra Segobin (S)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.

Catherine Merck (C)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.
Neurology Department, Pontchaillou University Hospital, Rennes, France.

Vincent de La Sayette (V)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.
Neurology Department, Caen University Hospital, Caen, France.

Serge Belliard (S)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.
Neurology Department, Pontchaillou University Hospital, Rennes, France.

Béatrice Desgranges (B)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.

Francis Eustache (F)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.

Mickaël Laisney (M)

Neuropsychology and Imaging of Human Memory research unit, Caen-Normandy University-PSL Research University-EPHE-INSERM-Caen University Hospital, UMRS1077, GIP Cyceron, Caen, France.

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Classifications MeSH