Cerebellar contribution to multisensory integration: A computational modeling exploration

The remarkable ability of the human brain to create a coherent perception of reality relies heavily on multisensory integration-the complex process of combining inputs from different senses. While this mechanism is fundamental to our understanding of the world, its underlying neural architecture remains partially unknown. This study investigates the role of the cerebellum in multisensory integration through a novel computational approach inspired by clinical observations of a patient with cerebellar agenesis. With reference to the clinical data comparing an acerebellar patient with age-matched control subjects, we exploited biologically realistic spiking neural networks to model both conditions. Our computational framework enables testing multiple network configurations and parameters, effectively replicating and extending the clinical experiments in silico. To enhance accessibility and promote broader adoption among researchers, we complemented this framework with a user-friendly web-based interface, eliminating the need for programming expertise. The computational results closely mirror the clinical findings, providing support for the critical contribution of the cerebellum in multisensory integration. Beyond being a consistent proof of concept for the previous clinical observations, this study introduces a versatile platform for testing brain models through our newly developed framework and interface. Thus, this work not only advances our understanding of the cerebellar role in sensory processing but also establishes a robust methodology for future computational investigations of neural mechanisms.