A neural network for the analysis of multisensory integration in the Superior Colliculus

It is well documented that superior colliculus (SC) neurons integrate stimuli of different modalities (e.g., visual and auditory). In this work, a mathematical model of the integrative response of SC neurons is presented, to gain a deeper insight into the possible mechanisms implicated. The model includes two unimodal areas (auditory and visual, respectively) sending information to a third area (in the SC) responsible for multisensory integration. Each neuron is represented via a sigmoidal relationship and a first-order dynamic. Neurons in the same area interact via lateral synapses. Simulations show that the model can mimic various responses to different combinations of stimuli: i) an increase in the neuron response in presence of multisensory stimulation, ii) the inverse ef-fectiveness principle; iii) the existence of within- and cross-modality suppres-sion between spatially disparate stimuli. The model suggests that non linearities in neural responses and synaptic connections can explain several aspects of multisensory integration.