Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals

Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

New insights into the impact of Lactobacillus population on host-bacteria metabolic interplay

We aimed at evaluating the association between intestinal Lactobacillus sp. composition and their metabolic activity with the host metabolism in adult and elderly individuals. Faecal and plasma metabolites were measured and correlated to the Lactobacillus species distribution in healthy Estonian cohorts of adult (n=16; <48 y) and elderly (n=33; >65 y). Total cholesterol, LDL, C-reactive protein and glycated hemoglobin were statistically higher in elderly, while platelets, white blood cells and urinary creatinine were higher in adults. Aging was associated with the presence of L. paracasei and L. plantarum and the absence of L. salivarius and L. helveticus. High levels of intestinal Lactobacillus sp. were positively associated with increased concentrations of faecal short chain fatty acids, lactate and essential amino acids. In adults, high red blood cell distribution width was positively associated with presence of L. helveticus and absence of L. ruminis. L. helveticus was correlated to lactate and butyrate in faecal waters. This indicates a strong relationship between the composition of the gut Lactobacillus sp. and host metabolism. Our results confirm that aging is associated with modulations of blood biomarkers and intestinal Lactobacillus species composition. We identified specific Lactobacillus contributions to gut metabolic environment and related those to blood biomarkers. Such associations may prove useful to decipher the biological mechanisms underlying host-gut microbial metabolic interactions in an ageing population.