Multisensory Integration Uses a Real-Time Unisensory-Multisensory Transform.

The manner in which the brain integrates different sensory inputs to facilitate perception and behavior has been the subject of numerous speculations. By examining multisensory neurons in cat superior colliculus, the present study demonstrated that two operational principles are sufficient to understand how this remarkable result is achieved: (1) unisensory signals are integrated continuously and in real time as soon as they arrive at their common target neuron and (2) the resultant multisensory computation is modified in shape and timing by a delayed, calibrating inhibition. These principles were tested for descriptive sufficiency by embedding them in a neurocomputational model and using it to predict a neuron's moment-by-moment multisensory response given only knowledge of its responses to the individual modality-specific component cues. The predictions proved to be highly accurate, reliable, and unbiased and were, in most cases, not statistically distinguishable from the neuron's actual instantaneous multisensory response at any phase throughout its entire duration. The model was also able to explain why different multisensory products are often observed in different neurons at different time points, as well as the higher-order properties of multisensory integration, such as the dependency of multisensory products on the temporal alignment of crossmodal cues. These observations not only reveal this fundamental integrative operation, but also identify quantitatively the multisensory transform used by each neuron. As a result, they provide a means of comparing the integrative profiles among neurons and evaluating how they are affected by changes in intrinsic or extrinsic factors. Multisensory integration is the process by which the brain combines information from multiple sensory sources (e.g., vision and audition) to maximize an organism's ability to identify and respond to environmental stimuli. The actual transformative process by which the neural products of multisensory integration are achieved is poorly understood. By focusing on the millisecond-by-millisecond differences between a neuron's unisensory component responses and its integrated multisensory response, it was found that this multisensory transform can be described by two basic principles: unisensory information is integrated in real time and the multisensory response is shaped by calibrating inhibition. It is now possible to use these principles to predict a neuron's multisensory response accurately armed only with knowledge of its unisensory responses.