Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity.

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., 'motion' parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 â€‹Hz, here referred to as 'HF-motion'), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0-2.5 â€‹s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 â€‹s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.

Age-related differences in functional brain network segregation are consistent with a cascade of cerebrovascular, structural, and cognitive effects.

Age-related declines in cognition are associated with widespread structural and functional brain changes, including changes in resting-state functional connectivity and gray and white matter status. Recently we have shown that the elasticity of cerebral arteries also explains some of the variance in cognitive and brain health in aging. Here, we investigated how network segregation, cerebral arterial elasticity (measured with pulse-DOT-the arterial pulse based on diffuse optical tomography) and gray and white matter status jointly account for age-related differences in cognitive performance. We hypothesized that at least some of the variance in brain and cognitive aging is linked to reduced cerebrovascular elasticity, leading to increased cortical atrophy and white matter abnormalities, which, in turn, are linked to reduced network segregation and decreases in cognitive performance. Pairwise comparisons between these variables are consistent with an exploratory hierarchical model linking them, especially when focusing on association network segregation (compared with segregation in sensorimotor networks). These findings suggest that preventing or slowing age-related changes in one or more of these factors may induce a neurophysiological cascade beneficial for preserving cognition in aging.

The Optical Effective Attenuation Coefficient as an Informative Measure of Brain Health in Aging.

Aging is accompanied by widespread changes in brain tissue. Here, we hypothesized that head tissue opacity to near-infrared light provides information about the health status of the brain's cortical mantle. In diffusive media such as the head, opacity is quantified through the Effective Attenuation Coefficient (EAC), which is proportional to the geometric mean of the absorption and reduced scattering coefficients. EAC is estimated by the slope of the relationship between source-detector distance and the logarithm of the amount of light reaching the detector (optical density). We obtained EAC maps across the head in 47 adults (age range 18-75 years), using a high-density dual-wavelength optical system. We correlated regional and global EAC measures with demographic, neuropsychological, structural and functional brain data. Results indicated that EAC values averaged across wavelengths were strongly associated with age-related changes in cortical thickness, as well as functional and neuropsychological measures. This is likely because the EAC largely depends on the thickness of the sub-arachnoid cerebrospinal fluid layer, which increases with cortical atrophy. In addition, differences in EAC values between wavelengths were correlated with tissue oxygenation and cardiorespiratory fitness, indicating that information about cortical health can be derived non-invasively by quantifying the EAC.

Optical measures of cerebral arterial stiffness are associated with white matter signal abnormalities and cognitive performance in normal aging.

Decline in fluid abilities in normal aging is associated with increased white matter lesions, measured on T1-weighted images as white matter signal abnormalities (WMSAs). WMSAs are particularly evident in hypertensive older adults, suggesting vascular involvement. However, because hypertension is assessed systemically, the specific role of cerebral arterial stiffening in WMSAs has yet to be demonstrated. In 93 cognitively normal adults (aged 18-87 years), we used a novel method to measure cerebral arterial elasticity (pulse relaxation function [PReFx]) with diffuse optical tomography (pulse-DOT) and investigated its association with WMSAs, age, and cognition. PReFx was associated with WMSAs, with older adults with low PReFx showing the greatest WMSA burden. PReFx in brain regions perfused by the middle cerebral artery showed the largest associations with WMSAs and partially mediated the relationship between age and WMSAs. Finally, WMSAs partially mediated the relationship between PReFx and fluid but not crystallized abilities scores. Taken together, these findings suggest that loss of cerebral arterial elasticity is associated with cerebral white matter lesions and age-related cognitive decline.