fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction.

BACKGROUND: functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics. METHODS: Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in 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 tapping (Cohen's d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. 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 systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses.

No association between markers of systemic inflammation and endothelial dysfunction with Alzheimer's disease progression: a longitudinal study.

INTRODUCTION: Systemic inflammation and endothelial dysfunction are potentially modifiable factors implicated in Alzheimer's disease (AD), which offer potential therapeutic targets to slow disease progression. METHODS: We investigated the relationship between baseline circulating levels of inflammatory (TNF-α, IL-1ß) and endothelial cell markers (VCAM-1, ICAM-1, E-selectin) and 18-month cognitive decline (ADAS-cog12) in 266 mild-to-moderate AD patients from the NILVAD study. We employed individual growth models to examine associations, potential mediation, and interaction effects while adjusting for confounders. RESULTS: The average increase in ADAS-cog12 scores over all patients was 8.1 points in 18 months. No significant association was found between the markers and the rate of cognitive decline. Mediation analysis revealed no mediating role for endothelial cell markers, and interaction effects were not observed. DISCUSSION: Our results do not support the role of systemic inflammation or endothelial dysfunction in progression in persons with AD.