A guide for the use of fNIRS in microcephaly associated to congenital Zika virus infection

Abstract

Congenital Zika Syndrome (CZS) is characterized by changes in cranial morphology associated with heterogeneous neurological manifestations and cognitive and behavioral impairments. In this syndrome, longitudinal neuroimaging could help clinicians to predict developmental trajectories of children and tailor treatment plans accordingly. However, regularly acquiring magnetic resonance imaging (MRI) has several shortcomings besides cost, particularly those associated with childrens' clinical presentation as sensitivity to environmental stimuli. The indirect monitoring of local neural activity by non-invasive functional near-infrared spectroscopy (fNIRS) technique can be a useful alternative for longitudinally accessing the brain function in children with CZS. In order to provide a common framework for advancing longitudinal neuroimaging assessment, we propose a principled guideline for fNIRS acquisition and analyses in children with neurodevelopmental disorders. Based on our experience on collecting fNIRS data in children with CZS we emphasize the methodological challenges, such as clinical characteristics of the sample, desensitization, movement artifacts and environment control, as well as suggestions for tackling such challenges. Finally, metrics based on fNIRS can be associated with established clinical metrics, thereby opening possibilities for exploring this tool as a long-term predictor when assessing the effectiveness of treatments aimed at children with severe neurodevelopmental disorders.

Mobile fNIRS for exploring inter-brain synchrony across generations and time

“…Researchers studying children's development (Noreika et al, 2020 ; Turk et al, 2022 ) and spoken communication (Kelsen et al, 2022 ) have also signaled that longitudinal hyperscanning could advance their research. Moreover, others suggest that fNIRS would be a suitable technique to address the lack of longitudinal data pertaining to the development of cognition in infants and children (Miguel et al, 2019 ; Sato et al, 2021 ), neurodegenerative diseases (Bonilauri et al, 2020 ; Srinivasan et al, 2023 ), psychiatric disorders (Kumar et al, 2017 ; Ho et al, 2020 ), hearing after receiving a cochlear implant (McKay et al, 2015 ; Anderson C. A. et al, 2017 ; Zhou et al, 2022 ), and use of psychedelic substances (Scholkmann and Vollenweider, 2022 ). While these authors do not explicitly refer to hyperscanning as their technique of choice, INS recorded with fNIRS over multiple sessions could address several methodological aspirations (i.e., ecological validity, two-brain design, longitudinal assessment) at once.…”

Mobile fNIRS for exploring inter-brain synchrony across generations and time

“…Researchers studying children's development (Noreika et al, 2020;Turk et al, 2022) and spoken communication (Kelsen et al, 2022) have also signaled that longitudinal hyperscanning could advance their research. Moreover, others suggest that fNIRS would be a suitable technique to address the lack of longitudinal data pertaining to the development of cognition in infants and children (Miguel et al, 2019;Sato et al, 2021), neurodegenerative diseases (Bonilauri et al, 2020;Srinivasan et al, 2023), psychiatric disorders (Kumar et al, 2017;Ho et al, 2020), hearing after receiving a cochlear implant (McKay et al, 2015;Anderson C. A. et al, 2017;Zhou et al, 2022), and use of psychedelic substances (Scholkmann and Vollenweider, 2022). While these authors do not explicitly refer to hyperscanning as their technique of choice, INS recorded with fNIRS over multiple sessions could address several methodological aspirations (i.e., ecological validity, two-brain design, longitudinal assessment) at once.…”

A Novel Exploratory Graph-Based Analytical Tool for Functional Near-Infrared Spectroscopy in Naturalistic Experiments: An Illustrative Application in Typically Developing Children

“…Preliminary studies have shown that the use of naturalistic stimuli (e.g., movies) enhances the reproducibility of functional connectivity and large-scale functional network findings [ 9 , 10 , 11 ]. In this scenario, recent modeling methods and complexity-based analysis have been suggested to address the limitations of the classical GLM-based analysis for non-structured paradigms [ 12 , 13 ].…”