Literature DB >> 19764874

Visuotactile representation of peripersonal space: a neural network study.

Elisa Magosso1, Melissa Zavaglia, Andrea Serino, Giuseppe di Pellegrino, Mauro Ursino.   

Abstract

Neurophysiological and behavioral studies suggest that the peripersonal space is represented in a multisensory fashion by integrating stimuli of different modalities. We developed a neural network to simulate the visual-tactile representation of the peripersonal space around the right and left hands. The model is composed of two networks (one per hemisphere), each with three areas of neurons: two are unimodal (visual and tactile) and communicate by synaptic connections with a third downstream multimodal (visual-tactile) area. The hemispheres are interconnected by inhibitory synapses. We applied a combination of analytic and computer simulation techniques. The analytic approach requires some simplifying assumptions and approximations (linearization and a reduced number of neurons) and is used to investigate network stability as a function of parameter values, providing some emergent properties. These are then tested and extended by computer simulations of a more complex nonlinear network that does not rely on the previous simplifications. With basal parameter values, the extended network reproduces several in vivo phenomena: multisensory coding of peripersonal space, reinforcement of unisensory perception by multimodal stimulation, and coexistence of simultaneous right- and left-hand representations in bilateral stimulation. By reducing the strength of the synapses from the right tactile neurons, the network is able to mimic the responses characteristic of right-brain-damaged patients with left tactile extinction: perception of unilateral left tactile stimulation, cross-modal extinction and cross-modal facilitation in bilateral stimulation. Finally, a variety of sensitivity analyses on some key parameters was performed to shed light on the contribution of single-model components in network behaviour. The model may help us understand the neural circuitry underlying peripersonal space representation and identify its alterations explaining neurological deficits. In perspective, it could help in interpreting results of psychophysical and behavioral trials and clarifying the neural correlates of multisensory-based rehabilitation procedures.

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Mesh:

Year:  2010        PMID: 19764874     DOI: 10.1162/neco.2009.01-08-694

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  16 in total

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2.  Organization, maturation, and plasticity of multisensory integration: insights from computational modeling studies.

Authors:  Cristiano Cuppini; Elisa Magosso; Mauro Ursino
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3.  The wheelchair as a full-body tool extending the peripersonal space.

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4.  Extending peripersonal space representation without tool-use: evidence from a combined behavioral-computational approach.

Authors:  Andrea Serino; Elisa Canzoneri; Marilena Marzolla; Giuseppe di Pellegrino; Elisa Magosso
Journal:  Front Behav Neurosci       Date:  2015-02-02       Impact factor: 3.558

5.  Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin.

Authors:  Alessandro Roncone; Matej Hoffmann; Ugo Pattacini; Luciano Fadiga; Giorgio Metta
Journal:  PLoS One       Date:  2016-10-06       Impact factor: 3.240

6.  Crossmodal links between vision and touch in spatial attention: a computational modelling study.

Authors:  Elisa Magosso; Andrea Serino; Giuseppe di Pellegrino; Mauro Ursino
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7.  Rapid Recalibration of Peri-Personal Space: Psychophysical, Electrophysiological, and Neural Network Modeling Evidence.

Authors:  Jean-Paul Noel; Tommaso Bertoni; Emily Terrebonne; Elisa Pellencin; Bruno Herbelin; Carissa Cascio; Olaf Blanke; Elisa Magosso; Mark T Wallace; Andrea Serino
Journal:  Cereb Cortex       Date:  2020-07-30       Impact factor: 5.357

8.  A neural network model of ventriloquism effect and aftereffect.

Authors:  Elisa Magosso; Cristiano Cuppini; Mauro Ursino
Journal:  PLoS One       Date:  2012-08-03       Impact factor: 3.240

9.  Global and local processing near the left and right hands.

Authors:  Robin M Langerak; Carina L La Mantia; Liana E Brown
Journal:  Front Psychol       Date:  2013-10-29

10.  A neural network model can explain ventriloquism aftereffect and its generalization across sound frequencies.

Authors:  Elisa Magosso; Filippo Cona; Mauro Ursino
Journal:  Biomed Res Int       Date:  2013-10-21       Impact factor: 3.411

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