The Quest for Functional Biomarkers in the Prefrontal Cortex Using Functional Near-Infrared Spectroscopy (fNIRS)

Abstract The prefrontal cortex (PFC) has been recognized as one of the most crucial brain regions responsible for cognitive control, thoughts, and actions. Advanced functional imaging has provided tools needed for the sensitive assessment of functional brain activities and also functional abnormalities in various brain regions. Functional near-infrared spectroscopy (fNIRS) is a highly promising neuroimaging modality that provides an efficient way to continuously monitor changes in blood oxygenation in the brain. Functional biomarkers validated and measured from fNIRS data have provided reliable and predictive information on various brain functional disorders. However, selecting optimum biomarkers from a set of hemodynamic features can be extremely challenging. Here, we focus on functional biomarkers driven from fNIRS data and advanced multivariate analysis used to extract those biomarkers. We introduce hemodynamic activation in the left and right prefrontal cortex and the oxygenation variability (OV) index, which is based on variability in oxygen saturation at frequencies attributed to cerebral autoregulation. The OV index has been calculated for toddlers of the age 18–36 months with varying levels of language development in order to compare it with other behavioral measurement. Furthermore, we discuss how multivariate machine learning techniques can be used in order to drive functional biomarkers in the human PFC which can be used as an aid in diagnosis of brain dysfunction such as traumatic brain injury (TBI).

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