Viewpoint on Multisensory Integration in Psychiatric Disorders.
TL;DR
The conversation highlights the shift from descriptive accounts of multisensory phenomena toward normative models, including maximum likelihood estimation, causal inference, and correlation detection, as well as the need to link these computations to neural circuits and clinical heterogeneity.
Abstract
This article presents a compiled interview with three researchers in the field of multisensory integration, with an emphasis on how multisensory integration may go awry in psychiatric and neurodevelopmental conditions. Through structured dialogue, the authors reflect on the origins of the field, the development of key empirical and computational frameworks, and the growing relevance of multisensory science for understanding autism, schizophrenia, dyslexia, and related conditions. The discussion highlights the shift from descriptive accounts of multisensory phenomena toward normative models, including maximum likelihood estimation, causal inference, and correlation detection, as well as the need to link these computations to neural circuits and clinical heterogeneity. The authors consider ongoing challenges in the field, including inconsistent findings across clinical studies, limited statistical power, difficulties in defining and measuring multisensory function, and the need for larger, better-characterized cohorts. They also discuss emerging directions, including naturalistic paradigms, adaptive coding, open and team science, precision psychiatry, and the application of artificial intelligence to complex multimodal datasets. The interview concludes by emphasizing the promise of multisensory integration as a framework for understanding perception, cognition, and belief updating in health and disease.