Embodiment of an artificial limb in the mouse model - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2024

Embodiment of an artificial limb in the mouse model

Résumé

Having the ability to probe the strength of limb embodiment is a requirement to better understand body ownership disorders that are triggered both by disease and by accidental body damage. It is also an essential tool towards the development of neuro-prostheses that better integrate into the user's body representation.

One key way to probe limb embodiment is through the rubber hand illusion. Here we adapted this paradigm to the mouse forelimb, which is a relevant model for upper limb research thanks to its diverse and rich behavioural characteristics and unparalleled access to genetic and optogenetic research tools.

We exposed head-fixed mice to a visible, static 3D printed replica of their right forelimb, while their own forelimb was removed from their sight and stimulated by brush strokes in synchrony with the replica. Following these visuo-tactile stimulations, the replica was visually threatened, and we probed the mice's reaction using automated tracking of pupils and facial expression. We found that mice focused significantly more their gaze towards the forelimb replica when they received congruent tactile and visual information, compared to control conditions. This observation is consistent with the human overt response to the rubber hand illusion. In summary, these findings indicate that mice can experience forelimb embodiment, and this phenomenon can be evaluated with the method we developed.

Domaines

Neurosciences
Fichier principal
Vignette du fichier
2024.04.25.591084v1.full.pdf (1.52 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04740657 , version 1 (16-10-2024)

Identifiants

Citer

Zineb Hayatou, Hongkai Wang, Antoine Chaillet, Daniel E Shulz, Luc Estebanez. Embodiment of an artificial limb in the mouse model. 2024. ⟨hal-04740657⟩
22 Consultations
17 Téléchargements

Altmetric

Partager

More