An emergent model of multisensory integration in superior colliculus neurons

• Main Authors: Cristiano Cuppini, Mauro Ursino, Elisa Magosso, Benjamin A Rowland, Barry E Stein
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2010-03-01
• Series: Frontiers in Integrative Neuroscience
• Subjects: anterior ectosylvian sulcus; enhancement; inverse effectiveness principle; neural network modeling; Suppression; visual-acoustic neurons
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnint.2010.00006/full

Neurons in the cat superior colliculus (SC) integrate information from different senses to enhance their responses to cross-modal stimuli. These multisensory SC neurons receive multiple converging unisensory inputs from many sources; those received from association cortex are critical for the manifestation of multisensory integration. The mechanisms underlying this characteristic property of SC neurons are not completely understood, but can be clarified with the use of mathematical models and computer simulations. Thus the objective of the current effort was to present a plausible model that can explain the main physiological features of multisensory integration based on the current neurological literature regarding the influences received by SC from cortical and subcortical sources. The model assumes the presence of competitive mechanisms between inputs, nonlinearities in NMDA receptor responses, and provides a priori synaptic weights to mimic the normal responses of SC neurons. As a result, it provides a basis for understanding the dependence of multisensory enhancement on an intact association cortex, and simulates the changes in the SC response that occur during NMDA receptor blockade. Finally, it makes testable predictions about why significant response differences are obtained in multisensory SC neurons when they are confronted with pairs of cross-modal and within-modal stimuli. By postulating plausible biological mechanisms to complement those that are already known, the model provides a basis for understanding how SC neurons are capable of engaging in this remarkable process.