A temporal classification method based on ...
Type de document :
Article dans une revue scientifique: Article original
PMID :
URL permanente :
Titre :
A temporal classification method based on behavior time series data in patients with behavioral variant of frontotemporal dementia and apathy.
Auteur(s) :
Peltier, C. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Lejeune, F. X. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Jorgensen, L. G. T. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Rametti-Lacroux, A. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Tanguy, D. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Godefroy, V. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Bendetowicz, D. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Carle, G. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Cognat, E. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Bombois, Stephanie [Auteur]
Lille Neurosciences & Cognition (LilNCog) - U 1172
Migliaccio, R. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Levy, R. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Marin, F. [Auteur]
Université de Technologie de Compiègne [UTC]
Batrancourt, B. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Institut du Cerveau = Paris Brain Institute [ICM]
Lejeune, F. X. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Jorgensen, L. G. T. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Rametti-Lacroux, A. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Tanguy, D. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Godefroy, V. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Bendetowicz, D. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Carle, G. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Cognat, E. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Bombois, Stephanie [Auteur]

Lille Neurosciences & Cognition (LilNCog) - U 1172
Migliaccio, R. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Levy, R. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Marin, F. [Auteur]
Université de Technologie de Compiègne [UTC]
Batrancourt, B. [Auteur]
Institut du Cerveau = Paris Brain Institute [ICM]
Titre de la revue :
J Neurosci Methods
Nom court de la revue :
J Neurosci Methods
Numéro :
376
Pagination :
109625
Date de publication :
2022-06-04
ISSN :
1872-678X
Mot(s)-clé(s) en anglais :
Subjects behavior
Testing session under ecological settings
Human ethology
Ethological approach
Measuring behavior
Temporal classification method
ECOCAPTURE kinetics
Time series behavior
Behavioral variant of frontotemporal dementia
Apathy
Behavioral kinetics
Neuropsychological profiles
Key features of apathetic behaviors
Behavioral study encoding time
R package
Open-source software (OSS)
Testing session under ecological settings
Human ethology
Ethological approach
Measuring behavior
Temporal classification method
ECOCAPTURE kinetics
Time series behavior
Behavioral variant of frontotemporal dementia
Apathy
Behavioral kinetics
Neuropsychological profiles
Key features of apathetic behaviors
Behavioral study encoding time
R package
Open-source software (OSS)
Discipline(s) HAL :
Sciences du Vivant [q-bio]
Résumé en anglais : [en]
Background Apathy is a common behavioral syndrome that occurs across neurological and psychiatric disorders. An influential theoretical framework defined apathy as the quantitative reduction of self-generated voluntary and ...
Lire la suite >Background Apathy is a common behavioral syndrome that occurs across neurological and psychiatric disorders. An influential theoretical framework defined apathy as the quantitative reduction of self-generated voluntary and purposeful behaviors. There is evidence in the literature of the multidimensional nature of apathy with cognitive, behavioral, and emotional dimensions. To date, apathy has been assessed using various scales and questionnaires. Alternative objective and ecological measurements of apathy are needed. New method We used the ECOCAPTURE protocol and an ethological approach to investigate behavior in bvFTD patients under ecological conditions (a waiting room) while they freely explored a novel environment. Data were collected by behavioral coding from 7-minute video using an ethogram and transformed into behavior time series data. We present an approach considering behavioral kinetics to assess behavior. We aimed to construct a new behavior analysis method, called ECOCAPTURE kinetics, using temporal classification for behavior time series data analysis. To develop our classifier, we retained a nonelastic Euclidian metric, combined with a convolutional approach. Results We applied the ECOCAPTURE kinetics method to a cohort of 20 bvFTD patients and 18 healthy controls. We showed that bvFTD patients can be classified according to their behavioral kinetics into three groups. Each subgroup was characterized by specific behavior disorders and neuropsychological profile. Comparison with Existing Method(s) The ECOCAPTURE kinetics method is different from those of the classical approach of measuring behavior, producing time budgets, frequency of behavior occurrences, or kinematic diagrams. Conclusions This approach can be extended to any behavioral study encoding time.Lire moins >
Lire la suite >Background Apathy is a common behavioral syndrome that occurs across neurological and psychiatric disorders. An influential theoretical framework defined apathy as the quantitative reduction of self-generated voluntary and purposeful behaviors. There is evidence in the literature of the multidimensional nature of apathy with cognitive, behavioral, and emotional dimensions. To date, apathy has been assessed using various scales and questionnaires. Alternative objective and ecological measurements of apathy are needed. New method We used the ECOCAPTURE protocol and an ethological approach to investigate behavior in bvFTD patients under ecological conditions (a waiting room) while they freely explored a novel environment. Data were collected by behavioral coding from 7-minute video using an ethogram and transformed into behavior time series data. We present an approach considering behavioral kinetics to assess behavior. We aimed to construct a new behavior analysis method, called ECOCAPTURE kinetics, using temporal classification for behavior time series data analysis. To develop our classifier, we retained a nonelastic Euclidian metric, combined with a convolutional approach. Results We applied the ECOCAPTURE kinetics method to a cohort of 20 bvFTD patients and 18 healthy controls. We showed that bvFTD patients can be classified according to their behavioral kinetics into three groups. Each subgroup was characterized by specific behavior disorders and neuropsychological profile. Comparison with Existing Method(s) The ECOCAPTURE kinetics method is different from those of the classical approach of measuring behavior, producing time budgets, frequency of behavior occurrences, or kinematic diagrams. Conclusions This approach can be extended to any behavioral study encoding time.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
Inserm
CHU Lille
Inserm
CHU Lille
Collections :
Équipe(s) de recherche :
Troubles cognitifs dégénératifs et vasculaires
Date de dépôt :
2024-06-22T22:03:21Z
2024-12-18T11:40:25Z
2024-12-18T11:40:25Z
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