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EnglishIt 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.
| Titolo: | A neural network for the analysis of multisensory integration in the Superior Colliculus | |
| Autore/i: | CUPPINI, CRISTIANO; MAGOSSO, ELISA; SERINO, ANDREA; DI PELLEGRINO, GIUSEPPE; URSINO, MAURO | |
| Autore/i Unibo: | ||
| Anno: | 2007 | |
| Titolo del libro: | Artificial Neural Networks - ICANN 2007: 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II | |
| Pagina iniziale: | 9 | |
| Pagina finale: | 18 | |
| Abstract: | 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. | |
| Data prodotto definitivo in UGOV: | 16-ott-2007 | |
| Appare nelle tipologie: | 2.01 Capitolo / saggio in libro |
File in questo prodotto:
http://hdl.handle.net/11585/47582
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