No abstract

Background: functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait. However, this comes with a number of challenges, like the correction for movement-induced systemic changes (i.e., changes in blood pressure, heart rate, breathing). We investigated gait-related tasks in a controlled and seated environment, to validate whether fNIRS can yield comparable results to functional magnetic resonance imaging. More specifically, we studied the fNIRS sensitivity to leg movements and to movement automaticity, and compared this to finger movements.Methods: Twenty-seven healthy participants performed sequential automatic and non-automatic finger tapping and foot stepping tasks. A multichannel fNIRS device including 12 short channels covered the primary motor cortex (M1), the premotor cortex, the prefrontal cortex, and the posterior parietal cortex. Changes in oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) were assessed by a general linear model (GLM). However, we noticed a correlation between the short channels and the expected functional hemodynamic responses, necessitating performing a separate short channel regression instead of adding them as nuisance regressors to the GLM.Results: Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen’s d = 1.35, p<0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot stepping (Cohen’s d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were in line with expectations, though the effect sizes did not yield significance. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels.Discussion: Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that task-evoked systemic effects may cause destabilization of GLM estimates when short channels are correlated with the task regressor.