Mark T. Wallace

Purpose: In our prior work, conventional event-related potential (ERP) responses to audiovisual versus auditory-only speech were found to explain variance in language abilities in autistic and non-autistic children but failed to differentiate autistic children from non-autistic children. This study extends previous ERP analyses of responses to audiovisual versus auditory-only speech in autistic and non-autistic school-aged children to investigate group and condition differences in the strength and topography of the ERP based on data-driven, reference-independent metrics that overcome limitations of conventional ERP analyses. Methods: Extant ERP data from 50 5-12-year-old children (25 per group, matched at the group level on age and sex assigned at birth) recorded during a passive task of listening and watching videos of auditory-only and audiovisual speech syllables were analyzed for differences in ERP strength and topography, quantified via global field power (GFP) and global map dissimilarity (GMD), respectively. Results: GFP was significantly reduced for audiovisual compared to auditory-only speech at 245–275 ms post-stimulus. Groups differed in GMD of the ERPs reflecting the difference in response to audiovisual versus auditory-only speech at 139–170 ms post-stimulus, wherein microstates suggested predominantly differential occipital electrode responses. Conclusions: The benefits of audiovisual integration manifest as a facilitation effect (reduced signal strength of the ERP response to audiovisual versus auditory-only speech) across autistic and non-autistic children. Autistic children also display different patterns of activation underlying ERPs in response to audiovisual versus auditory-only speech relative to non-autistic children. Topographic ERP analyses show promise for advancing our understanding of audiovisual speech processing in autism.

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.

Understanding how listeners perceive speech in complex audiovisual (AV) environments is essential for characterizing communication in everyday settings. Here, we used loudness ratings to examine how AV scene characteristics shape the perceptual representation of a target talker in multitalker babble. Twenty-five normal-hearing adults rated the perceived loudness of a female talker presented in four-talker babble at four target-to-masker ratios (TMRs: − 21, − 9, − 6, − 3 dB). Audiovisual temporal coherence was manipulated by delaying the audio relative to the video at five stimulus onset asynchronies (SOAs: 0–500 ms), and three linguistic categories were tested: words, pseudowords, and reversed words. At synchronous presentations, loudness ratings scaled with TMR and were higher for words than pseudowords and reversed words, despite identical physical intensities. Increasing AV asynchrony reduced perceived loudness, with significant drops emerging beyond 150–300 ms SOA. Mapping loudness ratings onto perceived TMR change using individual loudness-growth slopes eliminated the main effect of the linguistic category, isolating a 2–3 dB perceived TMR drop at 500 ms SOA across all categories. These results demonstrate that both AV temporal synchrony and linguistic content shape loudness perception in noise, but their contributions are dissociable. This provides a novel view into how the perceptual construct of loudness changes with the AV scene, with implications for how loudness ratings can be used to study scene analysis and communication.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with both genetic and environmental contributions. Previous work identified a de novo mutation in the dopamine transporter (DAT T356M) in an autism proband that results in profound behavioral changes when expressed homozygously in mice. Since complex human genetics are more likely to be present as heterozygous (single allele) mutations, we characterized mice that were heterozygous for the mutation. Both male and female DAT T356M ^+/− mice exhibited hyperactivity but normal habituation to novel environments. The difference in hyperactivity compared to wild‐type littermates was dramatically smaller than previously reported in homozygous animals. Other behavioral alterations were sex‐specific, with only male heterozygous mice exhibiting greater repetitive behaviors and impaired spatial learning in the Barnes maze. Sensorimotor gating measured by prepulse inhibition of the startle response was largely unchanged in both sexes. Motor performance on the rotarod showed opposing effects, with male heterozygotes showing decreased latency to fall while females demonstrated increased latency (i.e., enhanced performance). These findings suggest that even a single copy of the DAT T356M variant can impact behavior in a sex‐specific manner. The identification of intermediate phenotypes makes these mice an appropriate model for future studies examining how environmental factors might interact with genetic susceptibility to influence autism‐relevant behaviors, particularly in the context of dopaminergic dysfunction.

Purpose: In addition to the core domains of social communication impairments (SCI) and patterns of restricted and repetitive behaviors and interests (RRBIs), autism is characterized by changes in sensory processing, including in the integration of information across the different sensory modalities. While there is significant evidence that audiovisual (AV) integration is altered in the temporal domain in autism—and that these differences are associated with presentation of SCI and RRBIs—very little is known about how autistic individuals integrate AV information in the domain of space. Methods: We conducted a free-response AV spatial localization task in autistic and non-autistic children aged 7–17 years to understand better AV localization abilities, as well as how these abilities relate to SCI, RRBIs, and other clinical features of autism. Results: While we found no group differences in AV spatial performance, an exploratory analysis revealed three clusters of autism features that were significantly predictive of performance across groups: a motor/somatosensory cluster, a sensory responsivity cluster, and a social communication cluster. Conclusions: Although autistic children appear to have intact audiovisual spatial integration ability, we believe that specific autism features and their links to AV spatial integration need to be further explored in future research. Limitations and future research directions are discussed.

We recorded single neurons in macaque dorsolateral prefrontal cortex during visual, auditory, and audiovisual motion. Nearly half of the responsive neurons were multisensory, and a third displayed significant super- or subadditive interactions, while ensemble activity reliably decoded stimulus modality. These findings provide direct evidence that the dorsolateral prefrontal cortex (DLPFC) performs rapid, nonlinear audiovisual integration, extending multisensory computations beyond classical posterior regions into the prefrontal circuits that support cognition.

In 2024, the United States House of Representatives passed ruling H.R.7213, the Autism CARES Act, which, if passed by the Senate, will reauthorize funding to extant national autism research programs, with an emphasis on including autistic individuals significantly affected by the disorder. This shift toward research inclusion across the autism spectrum clearly highlights the lack of representation in the past. In the field of multisensory integration, it is well documented that there are changes to how autistic individuals integrate stimuli across different sensory modalities, and the relationship between atypical (multi)sensory processing and the core features of autism is well documented. However, much of this research utilizes samples of autistic individuals with high cognitive, verbal, and functional ability. The purpose of this review is to draw attention to disparities in the samples used in multisensory research in autism. We conducted a systematic review of all studies examining multisensory function in autism to date and provide basic descriptive statistics of the studies. We observed that the vast majority of multisensory research is focused on young, low support needs autistic individuals, with very little investigation in autistic individuals with high support needs (HSN). Additionally, we found investigation into the effect of sex or comorbidities to be lacking. We propose methodological improvements addressing gaps in the research in order to make multisensory research in autism more inclusive to HSN autistics.

Multisensory integration (MSI) is a core neurobehavioral operation that enhances our ability to perceive, decide, and act by combining information from different sensory modalities. This integrative capability is essential for efficiently navigating complex environments and responding to their multisensory nature. One of the powerful behavioral benefits of MSI is in speeding responses. To evaluate this speeding, traditional research in MSI often relies on so-called race models, which predict reaction times (RTs) based on the assumption that information from the different sensory modalities is initially processed independently. When observed RTs are faster than those predicted by these models, it indicates the presence of true convergence and integration of multisensory information prior to the initiation of the motor response. Despite the strong applicability of race models in MSI research, analysis of multisensory RT data often poses challenges for researchers, particularly in managing, interpreting and modeling large datasets or a collection of datasets. To surmount these challenges, we developed a user-friendly graphical user interface (GUI) packaged into a freely available software application that is compatible with both Windows and Mac and that requires no programming expertise. This tool simplifies the processes of data loading, filtering, and statistical analysis. It allows the calculation and visualization of RTs across different sensory modalities, the performance of robust statistical tests, and the testing of race model violations. By integrating these capabilities into a single platform, the CART-GUI facilitates MSI analyses and makes it accessible to a wider range of users, from novice researchers to experts in the field. The GUI’s user-friendly design and advanced analytical features will allow for valuable insights into the mechanisms underlying MSI and contribute to the advancement of research in this domain.