Multisensory features of peripersonal space representation: an analysis via neural network modelling.

Vissani, Matteo (2017) Multisensory features of peripersonal space representation: an analysis via neural network modelling. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria biomedica [LM-DM270] - Cesena, Documento full-text non disponibile
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Abstract

The peripersonal space (PPS) is the space immediately surrounding the body. It is coded in the brain in a multisensory, body part-centered (e.g. hand-centered, trunk-centered), modular fashion. This is supported by the existence of multisensory neurons (in fronto-parietal areas) with tactile receptive field on a specific body part (hand, arm, trunk, etc.) and visual/auditory receptive field surrounding the same body part. Recent behavioural results (Serino et al. Sci Rep 2015), obtained by using an audio-tactile paradigm, have further supported the existence of distinct PPS representations, each specific of a single body part (hand, trunk, face) and characterized by specific properties. That study has also evidenced that the PPS representations– although distinct – are not independent. In particular, the hand-PPS loses its properties and assumes those of the trunk-PPS when the hand is close to the trunk, as the hand-PPS was encapsulated within the trunk-PPS. Similarly, the face-PPS appears to be englobed into the trunk-PPS. It remains unclear how this interaction, which manifests behaviourally, can be implemented at a neural level by the modular organization of PPS representations. The aim of this Thesis is to propose a neural network model to help the comprehension of the underlying neurocomputational mechanisms. The model includes three subnetworks devoted to the single PPS representations around the hand, face and the trunk. Furthermore, interaction mechanisms– controlled by proprioceptive neurons – have been postulated among the subnetworks. The network is able to reproduce the behavioural data, explaining them in terms of neural properties and response. Moreover, the network provides some novel predictions, that can be tested in vivo. One of this prediction has been tested in this work, by performing an ad-hoc behavioural experiment at the Laboratory of Cognitive Neuroscience (Campus Biotech, Geneva) under the supervision of the neuropsychologist Dr Serino.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Vissani, Matteo
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Neurocomputational modelling,In silico neurons and synapses,Audio-tactile interaction,Multisensory neurons,Peripersonal space,Neuropsychology
Data di discussione della Tesi
16 Marzo 2017
URI

Altri metadati

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