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Detecting fine and elaborate movements with piezo sensors provides non-invasive access to overlooked behavioral components.
Carreño-Muñoz, Maria Isabel; Medrano, Maria Carmen; Ferreira Gomes Da Silva, Arnaldo; Gestreau, Christian; Menuet, Clément; Leinekugel, Thomas; Bompart, Maelys; Martins, Fabienne; Subashi, Enejda; Aby, Franck; Frick, Andreas; Landry, Marc; Grana, Manuel; Leinekugel, Xavier.
Afiliação
  • Carreño-Muñoz MI; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Medrano MC; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Ferreira Gomes Da Silva A; INMED, INSERM, Aix Marseille University, Marseille, France.
  • Gestreau C; INMED, INSERM, Aix Marseille University, Marseille, France.
  • Menuet C; INMED, INSERM, Aix Marseille University, Marseille, France.
  • Leinekugel T; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Bompart M; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Martins F; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Subashi E; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Aby F; IINS, CNRS, Bordeaux, France.
  • Frick A; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France.
  • Landry M; IINS, CNRS, Bordeaux, France.
  • Grana M; Facultad de Informatica, University of the Basque Country UPV/EHU, Donostia-San Sebastian, Spain.
  • Leinekugel X; Université de Bordeaux, INSERM, Neurocentre Magendie, Bordeaux, France. xavier@arcadi.eu.
Neuropsychopharmacology ; 47(4): 933-943, 2022 03.
Article em En | MEDLINE | ID: mdl-34764433
ABSTRACT
Behavioral phenotyping devices have been successfully used to build ethograms, but many aspects of behavior remain out of reach of available phenotyping systems. We now report on a novel device, which consists in an open-field platform resting on highly sensitive piezoelectric (electromechanical) pressure-sensors, with which we could detect the slightest movements (up to individual heart beats during rest) from freely moving rats and mice. The combination with video recordings and signal analysis based on time-frequency decomposition, clustering, and machine learning algorithms provided non-invasive access to previously overlooked behavioral components. The detection of shaking/shivering provided an original readout of fear, distinct from but complementary to behavioral freezing. Analyzing the dynamics of momentum in locomotion and grooming allowed to identify the signature of gait and neurodevelopmental pathological phenotypes. We believe that this device represents a significant progress and offers new opportunities for the awaited advance of behavioral phenotyping.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Movimento Limite: Animals Idioma: En Revista: Neuropsychopharmacology Assunto da revista: NEUROLOGIA / PSICOFARMACOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Movimento Limite: Animals Idioma: En Revista: Neuropsychopharmacology Assunto da revista: NEUROLOGIA / PSICOFARMACOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França