Abstract
.SignificanceFunctional near-infrared spectroscopy (fNIRS) is a neuroimaging tool that can measure resting-state functional connectivity; however, non-neuronal components present in fNIRS signals introduce false discoveries in connectivity, which can impact interpretation of functional networks.AimWe investigated the effect of short channel correction on resting-state connectivity by removing non-neuronal signals from fNIRS long channel data. We hypothesized that false discoveries in connectivity can be reduced, hence improving the discriminability of functional networks of known, different connectivity strengths.ApproachA principal component analysis-based short channel correction technique was applied to resting-state data of 10 healthy adult subjects. Connectivity was analyzed using magnitude-squared coherence of channel pairs in connectivity groups of homologous and control brain regions, which are known to differ in connectivity.ResultsBy removing non-neuronal components using short channel correction, significant reduction of coherence was observed for oxy-hemoglobin concentration changes in frequency bands associated with resting-state connectivity that overlap with the Mayer wave frequencies. The results showed that short channel correction reduced spurious correlations in connectivity measures and improved the discriminability between homologous and control groups.ConclusionsResting-state functional connectivity analysis with short channel correction performs better than without correction in its ability to distinguish functional networks with distinct connectivity characteristics.
Highlights
Resting-state functional connectivity refers to the temporal synchronization of spatially remote spontaneous neuronal activity when the brain is at rest
Functional near-infrared spectroscopy is a non-invasive functional neuroimaging technique that measures the relative changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations in the superficial brain tissues to infer the localized neuronal activity of brain regions of interest.[9,10] fNIRS
The majority of the previous fNIRS resting-state functional connectivity studies have overlooked the effect of physiological noise (Mayer waves in particular) on connectivity measures
Summary
Resting-state functional connectivity refers to the temporal synchronization of spatially remote spontaneous neuronal activity when the brain is at rest. Brain regions that produce significantly correlated neural activity in resting state are highly correlated in response to a task or a Neurophotonics. Resting-state functional connectivity studies have provided useful insights into developmental and neuroplastic changes of brain networks in different subject populations including people with cochlear implants,[3] infants, and young children.[4,5,6,7]. Consistent with the findings from resting-statefMRI studies, several fNIRS studies have demonstrated the presence of resting-state networks in homologous brain regions of sensorimotor, visual, and auditory systems.[1,14,15,16,17]
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