Reducing false discoveries in resting-state functional connectivity using short channel correction: an fNIRS study

Abstract

. Significance: Functional 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. Aim: We 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. Approach: A 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. Results: By 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. Conclusions: Resting-state functional connectivity analysis with short channel correction performs better than without correction in its ability to distinguish functional networks with distinct connectivity characteristics.

Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS

“…First, this approach attempts to address the issue of spurious correlations in functional connectivity measures introduced by systemic physiological artifacts (particularly due to Mayer waves around 0.05-0.1 Hz). Consistent with the findings of previous studies [36][37][38], peaks of coherence were observed in our results in the frequency band associated with Mayer waves (0.05-0.15 Hz) as shown in figures 6(b)-(e), potentially indicating the presence of spurious correlations in connectivity measures. Second, some form of normalization of coherence data is required as coherence measured in some infant participants could be slightly higher than their agematched peers due to inherent differences in brain structure and anatomy.…”

Prefrontal cortical connectivity and coupling of infraslow oscillation in the resting human brain: a 2-channel broadband NIRS study

“…2021 ). It is reported only recently that RSFC can be quantified more accurately with a short S-D reading correction than without correction ( Paranawithana et al. 2022 ).…”

Enhancement of Frequency-Specific Hemodynamic Power and Functional Connectivity by Transcranial Photobiomodulation in Healthy Humans

“…To remove such potential contamination, extra optical channels of fNIRS with a short source-detector (S-D) separation (commonly ∼0.8-1.2 cm) have been used for systemic noise removal in task-evoked hemodynamic studies (Zhang et al, 2007;Tian et al, 2011;Yücel et al, 2015;Zhou et al, 2020;Noah et al, 2021), where a cortical region is functionally stimulated by a given task. However, most fNIRS-derived FC studies did not consider this confound effect until a recent report demonstrated that resting-state FC analysis with short S-D correction provides better accuracy than without correction (Paranawithana et al, 2022). We knowledge another weakness of this study is that the potential contribution from the extracranial layers to the hemodynamic results has not been considered.…”