The brain's ability to bind incoming auditory and visual stimuli depends critically on the temporal structure of this information. Specifically, there exists a temporal window of audiovisual integration within which stimuli are highly likely to be bound together and perceived as part of the same environmental event. Several studies have described the temporal bounds of this window, but few have...

Multisensory integration has often been characterized as an automatic process. Recent findings indicate that multisensory integration can occur across various stages of stimulus processing that are linked to, and can be modulated by, attention. Stimulus-driven, bottom-up mechanisms induced by crossmodal interactions can automatically capture attention towards multisensory events, particularly w...

Computational modeling largely based on advances in artificial intelligence and machine learning has helped furthering the understanding of some of the principles and mechanisms of multisensory object perception. Furthermore, this theoretical work has led to the development of new experimental paradigms and to important new questions. The last 20 years have seen an increasing emphasis on models...

Integrating the multisensory features of talking faces is critical to learning and extracting coherent meaning from social signals. While we know much about the development of these capacities at the behavioral level, we know very little about the underlying neural processes. One prominent behavioral milestone of these capacities is the perceptual narrowing of face-voice matching, whereby young...

Flexible spatial behavior requires the ability to orchestrate the interaction of multiple parallel processes. At the sensory level, multimodal inputs must be combined to produce a robust description of the spatiotemporal properties of the environment. At the action-selection level, multiple concurrent navigation policies must be dynamically weighted in order to adopt the strategy that is the mo...

The ability to integrate information across multiple sensory systems offers several behavioral advantages, from quicker reaction times and more accurate responses to better detection and more robust learning. At the neural level, multisensory integration requires large-scale interactions between different brain regions--the convergence of information from separate sensory modalities, represente...

Previous neurophysiological and neurobiological research has revealed different areas of multisensory integration in the CNS. Behavioral consequences of multimodal convergent stimuli arrays (visual/auditory/ somatosensory) have been observed on different kinds of higher mammals (cats, monkeys). Multisensory convergence neurons output directly affects motor behavior: Depending on convergent or d...

In this paper, we present two neural network models - devoted to two specific and widely investigated aspects of multisensory integration - in order to evidence the potentialities of computational models to gain insight into the neural mechanisms underlying organization, development, and plasticity of multisensory integration in the brain. The first model considers visual-auditory interaction i...

Interactions between multisensory integration and attention were studied using a combined audiovisual streaming design and a rapid serial visual presentation paradigm. Event-related potentials (ERPs) following audiovisual objects (AV) were compared with the sum of the ERPs following auditory (A) and visual objects (V). Integration processes were expressed as the difference between these AV and ...

Functional neuroimaging studies have implicated a number of brain regions, especially the posterior parietal cortex (PPC), as being potentially important for visual-tactile multisensory integration. However, neuroimaging studies are correlational and do not prove the necessity of a region for the behavioral improvements that are the hallmark of multisensory integration. To remedy this knowledge...