The relationship between processing speed and remodeling spatial patterns of intrinsic brain activity in the elderly with different sleep duration

Abstract

ObjectiveBrain neuroplasticity in which sleep affects the speed of information processing in the elderly population has not been reported. Therefore, this study was conducted to explore the effects of sleep on information processing speed and its central plasticity mechanism in the elderly.MethodsA total of 50 individuals aged 60 and older were enrolled in this case control study. All subjects were divided into two groups according to the sleep time: short sleep duration (< 360 min) (6 men and 19 women; mean age: 66.96 ± 4.28 years old), and non-short sleep duration (> 360 min) (13 men and 12 women). Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected, and the amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated for each participant. Two-sample t-tests were performed to compare the ALFF, ReHo, and DC maps between the two groups. Then, the relationships among clinical features, fMRI and cognitive function were analyzed using general linear model.ResultsShort sleep duration group showed significantly increased ALFF value in the bilateral middle frontal gyrus and right insula; significantly increased ReHo value in the left superior parietal gyrus, and decreased ReHo value in the right crebellum; significantly decreased DC value in the left inferior occipital gyrus, left superior parietal gyrus and right cerebellum (p < 0.05, AlphaSim correction). The ALFF value of right insula is significantly associated with symbol digit modalities test (SDMT) score (β = −0.363, p = 0.033).ConclusionShort sleep duration and processing speed are significantly associated with remodeling spatial patterns of intrinsic brain activity in the elderly.

Motor imagery-based brain–computer interface rehabilitation programs enhance upper extremity performance and cortical activation in stroke patients

“…The analysis of resting-state data was performed with RESTplus V1.2 (the Resting-State fMRI Data Analysis Toolkit plus V1.2, http://restfmri.net/forum/RESTplusV1.2 ), to perform amplitude of low-frequency fluctuations (ALFF) or regional homogeneity (ReHo) computations. In line with our previous research [ 21 , 22 ], we followed the same data processing protocol by discarding the initial ten volumes of each subject to reach signal equilibrium, then the processing procedure including: (1) time correction of slice scans; (2) the correction of head movement (all head movements were below 2.5 mm or 2.5° in any direction); (3) aligning the functional brain images to the standard EPI template through spatial normalization; (4) regression of nuisance variables, including the white matter and cerebral spinal fluid blood oxygen level-dependent (BOLD) signals and head motion with six motion profiles; (5) spatial smoothing using a Gaussian kernel with a full width at half maximum of 6 mm before the ALFF calculation and after ReHo calculation; (6) removal of linear trends; (7) ALFF and ReHo calculations for the traditional low-frequency band (0.01–0.08 Hz), and (8) transformation of both ALFF and ReHo values into a Z score (zALFF and zReHo)for further comparison between groups.…”