The amplitude of fNIRS hemodynamic response in the visual cortex unmasks autistic traits in typically developing children

Abstract

Autistic traits represent a continuum dimension across the population, with autism spectrum disorder (ASD) being the extreme end of the distribution. Accumulating evidence shows that neuroanatomical and neurofunctional profiles described in relatives of ASD individuals reflect an intermediate neurobiological pattern between the clinical population and healthy controls. This suggests that quantitative measures detecting autistic traits in the general population represent potential candidates for the development of biomarkers identifying early pathophysiological processes associated with ASD. Functional near-infrared spectroscopy (fNIRS) has been extensively employed to investigate neural development and function. In contrast, the potential of fNIRS to define reliable biomarkers of brain activity has been barely explored. Features of non-invasiveness, portability, ease of administration and low-operating costs make fNIRS a suitable instrument to assess brain function for differential diagnosis, follow-up, analysis of treatment outcomes and personalized medicine in several neurological conditions. Here, we introduce a novel standardized procedure with high entertaining value to measure hemodynamic responses (HDR) in the occipital cortex of adult subjects and children. We found that the variability of evoked HDR correlates with the autistic traits of children, assessed by the Autism-Spectrum Quotient. Interestingly, HDR amplitude was especially linked to social and communication features, representing the core symptoms of ASD. These findings establish a quick and easy strategy for measuring visually-evoked cortical activity with fNIRS that optimize the compliance of young subjects, setting the background for testing the diagnostic value of fNIRS visual measurements in the ASD clinical population.

Shedding Light on functional Near Infrared Spectroscopy and Open Science Practices

“…Additionally, sharing materials promotes replicability and aids advanced researchers to refine or build new methods inspired by others in the fNIRS community. Sharing such tools and materials (see Mazziotti et al, 2022;Meidenbauer, Choe, Cardenas-Iniguez, Huppert, & Berman, 2021 for examples of sharing fNIRS presentation paradigms) has become easier across all fields with code sharing databases such as GitHub, and fNIRS specific code sharing databases (e.g., https://fnirs.org/resources/data-analysis/software/). In addition, our fNIRS journal, Neurophotonics, already promotes code sharing through its acceptance of tutorial manuscripts and also provides suggestion for code sharing on its website (see https://codeocean.com/signup/spie).…”