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.
Subject(s)
Functional Neuroimaging/standards , Microcephaly/therapy , Neurodevelopmental Disorders/diagnosis , Spectroscopy, Near-Infrared/standards , Zika Virus Infection/complications , Brain/diagnostic imaging , Brain/physiopathology , Brazil , Child, Preschool , Functional Neuroimaging/methods , Humans , Longitudinal Studies , Male , Microcephaly/physiopathology , Microcephaly/virology , Neurodevelopmental Disorders/physiopathology , Neurodevelopmental Disorders/prevention & control , Practice Guidelines as Topic , Treatment Outcome , Zika Virus Infection/virologyABSTRACT
The fMRI-based functional connectome was shown to be sufficiently unique to allow individual identification (fingerprinting). We aimed to test whether a fNIRS-based connectome could also be used to identify individuals. Forty-four participants performed experimental protocols that consisted of two periods of resting-state interleaved by a cognitive task period. Connectome identification was performed for all possible pairwise combinations of the three periods. The influence of hemodynamic global variation was tested using global signal regression and principal component analysis. High identification accuracies well-above chance level (2.3%) were observed overall, being particularly high (93%) to the oxyhemoglobin signal between resting conditions. Our results suggest that fNIRS is a suitable technique to assess connectome fingerprints.
