Multisensory integration in the superior colliculus: a neural network model (Ursino et al. 2009)

 Download zip file 
Help downloading and running models
Accession:118261
" ... The model includes three distinct neural areas: two unimodal areas (auditory and visual) are devoted to a topological representation of external stimuli, and communicate via synaptic connections with a third downstream area (in the SC) responsible for multisensory integration. The present simulations show that the model, with a single set of parameters, can mimic various responses to different combinations of external stimuli including the inverse effectiveness, both in terms of multisensory enhancement and contrast, the existence of within- and cross-modality suppression between spatially disparate stimuli, a reduction of network settling time in response to cross-modal stimuli compared with individual stimuli. ..."
Reference:
1 . Ursino M, Cuppini C, Magosso E, Serino A, di Pellegrino G (2009) Multisensory integration in the superior colliculus: a neural network model. J Comput Neurosci 26:55-73 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Superior colliculus;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Activity Patterns; Vision; Audition;
Implementer(s):
%% DYNAMICAL RANGES
% the SC activity is evaluated in response to different sensory modality
% external stimuli, at different intensities:
% red line   -> response to multisensory stimuli;
% blu line   -> response to visual stimuli;
% green line -> response to auditory stimuli.

clear

load RANGE_DIN_Ivisivo_LuDeboli_LmForti
load RANGE_DIN_Iacustico_LuDeboli_LmForti
load RANGE_DIN_Imultisensoriale_LuDeboli_LmForti

somma_IvIa=xm_v_regime+xm_a_regime;

figure
plot(stimoli,xm_m_regime,'r',stimoli,xm_v_regime,'b',stimoli,xm_a_regime,'g',stimoli,somma_IvIa,'k') %
title('Dynamical ranges');
xlabel('input intensity')
ylabel('SCN normalized activity')