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Low back pain (LBP) has been associated with altered body sway during quiet standing, but the pattern of results is inconsistent. The purpose of this meta-analysis is to examine the effects of vision (eyes open, eyes closed) and changing the support surface (foam surface, firm surface) on postural sway during quiet standing in individuals with chronic LBP (cLBP). Five electronic databases were searched on March 27th, 2022. Of 2,856, 16 studies (n = 663) were included. Across all conditions, we found a positive and medium effect size (g = 0.77 [0.50, 1.04]) that represented greater body sway in individuals with cLBP. Subgroup analyses revealed medium effects during eyes open conditions (firm surface: g = 0.60 [0.33, 0.87]; foam surface: g = 0.68 [0.38, 0.97]), and large effects during eyes closed conditions (firm surface: g = 0.97 [0.60, 1.35]; foam surface: g = 0.89 [0.28, 1.51]). We quantified effects of self-reported pain and found a moderate effect during eyes closed plus firm surface conditions (Q = 3.28; p  = 0.070). We conclude that cLBP is associated with increased postural sway, with largest effect sizes evident when vision is removed and when self-reported pain intensity is higher.

•We applied single dipole source localization and meta-analysis in age-related alpha rhythm research.•The elderly group showed slower alpha rhythms and reduced power compared to younger individuals.•Age effects on alpha rhythms manifested differently across brain regions.•The largest age effect on PAF was observed in occipital regions.•The largest age effect on power at PAF was observed in sensorimotor regions. With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.

In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now strong evidence that somatotopic organization is evident across other regions in the sensorimotor network. This raises several experimental questions: To what extent is activity in the sensorimotor network effector-dependent and effector-independent? How important is the sensorimotor cortex when predicting the motor effector? Is there redundancy in the distributed somatotopically organized network such that removing one region has little impact on classification accuracy? To answer these questions, we developed a novel experimental approach. fMRI data were collected while human subjects performed a precisely controlled force generation task separately with their hand, foot, and mouth. We used a simple linear iterative clustering (SLIC) algorithm to segment whole-brain beta coefficient maps to build an adaptive brain parcellation and then classified effectors using extreme gradient boosting (XGBoost) based on parcellations at various spatial resolutions. This allowed us to understand how data-driven adaptive brain parcellation granularity altered classification accuracy. Results revealed effector-dependent activity in regions of the post-central gyrus, precentral gyrus, and paracentral lobule. SMA, regions of the inferior and superior parietal lobule, and cerebellum each contained effector-dependent and effector-independent representations. Machine learning analyses showed that increasing the spatial resolution of the data-driven model increased classification accuracy, which reached 94% with 1755 supervoxels. Our SLIC-based supervoxel parcellation outperformed classification analyses using established brain templates and random simulations. Occlusion experiments further demonstrated redundancy across the sensorimotor network when classifying effectors. Our observations extend our understanding of effector-dependent and effector-independent organization within the human brain and provide new insight into the functional neuroanatomy required to predict the motor effector used in a motor control task. [Display omitted]

Integrating visual information for motor output is an essential process of visually-guided motor control. The brainstem is known to be a major center involved in the integration of sensory information for motor output, however, limitations of functional imaging in humans have impaired our knowledge about the individual roles of sub-nuclei within the brainstem. Thus, the bulk of our knowledge surrounding the function of the brainstem is based on anatomical and behavioral studies in non-human primates, cats, and rodents, despite studies demonstrating differences in the organization of visuomotor processing between mammals. fMRI studies in humans have examined activity related to visually-guided motor tasks, however, few have done so while controlling for both force without visual feedback activity and visual stimuli without force activity. Of the studies that have controlled for both conditions, none have reported brainstem activity. Here, we employed a novel fMRI paradigm focused on the brainstem and cerebellum to systematically investigate the hypothesis that the pons and midbrain are critical for the integration of visual information for motor control. Visuomotor activity during visually-guided pinch-grip force was measured while controlling for force without visual feedback activity and visual stimuli without force activity in healthy adults. Using physiological noise correction and multiple task repetitions, we demonstrated that visuomotor activity occurs in the inferior portion of the basilar pons and the midbrain. These findings provide direct evidence in humans that the pons and midbrain support the integration of visual information for motor control. We also determined the effect of physiological noise and task repetitions on the visuomotor signal that will be useful in future studies of neurodegenerative diseases affecting the brainstem.

Precise motor control requires the ability to scale the parameters of movement. Theta oscillations across the cortex have been associated with changes in memory, attention, and sensorimotor processing. What has proven more elusive is pinpointing the region-specific frequency band oscillations that are associated with specific parameters of movement during the acceleration and deceleration phases. We report a study using 3D analytic techniques for high density electroencephalography that examines electrocortical dynamics while participants produce upper limb movements to different distances at varying rates. During fast ballistic movements, we observed increased theta band activity in the left motor area contralateral to the moving limb during the acceleration phase of the movement, and theta power correlated with the acceleration of movement. In contrast, beta band activity scaled with the type of movement during the deceleration phase near the end of the movement and correlated with movement time. In the ipsilateral motor and somatosensory area, alpha band activity decreased with the type of movement near the end of the movement, and gamma band activity in visual cortex increased with the type of movement near the end of the movement. Our results suggest that humans use distinct lateralized cortical activity for distance and speed dependent arm movements. We provide new evidence that a temporary increase in theta band power relates to movement acceleration and is important during movement execution. Further, the theta power increase is coupled with desychronization of beta band power and alpha band power which are modulated by the task near the end of movement. •We use Measure Projection Analysis for source dynamics in upper arm movements•We show 3D maps with statistical significance for ERSP and ITC measures in upper limb movements•Theta activity from motor cortex is related to movement acceleration•We found that distinct lateralized cortical activity is recruited at the end of movement

Increased force variability constitutes a hallmark of arm disabilities following stroke. Force variability is related to the modulation of force below 1 Hz in healthy young and older adults. However, whether the increased force variability observed post stroke is related to the modulation of force below 1 Hz remains unknown. Thus, the purpose of this study was to compare force modulation below 1 Hz in chronic stroke and age-matched healthy individuals. Both stroke and control individuals (N = 26) performed an isometric grip task to submaximal force levels. Coefficient of variation quantified force variability, and power spectrum density of force quantified force modulation below 1 Hz with a high resolution (0.07 Hz). Analyses indicated that force variability was greater for the stroke group compared with to healthy controls and for the paretic hand compared with the non-paretic hand. Force modulation below 1 Hz differentiated the stroke individuals and healthy controls, as well as the paretic and non-paretic hands. Specifically, stroke individuals (paretic hand) exhibited greater power ~0.2 Hz (0.07-0.35 Hz) and lesser power ~0.6 Hz (0.49-0.77 Hz) compared to healthy controls (non-dominant hand). Similarly, the paretic hand exhibited greater power ~0.2 Hz, and lesser power ~0.6 Hz than the non-paretic hand. Moreover, variability of force was strongly predicted from the modulation of specific frequencies below 1 Hz (R(2) = 0.80). Together, these findings indicate that the modulation of force below 1 Hz provides significant insight into changes in motor control after stroke.

Advanced aging is associated with robust changes in neural activity. In addition to the well-established age-related slowing of the peak alpha frequency, there is a growing body of evidence showing that older age is also associated with changes in alpha power and beta power. Despite the important progress that has been made, the interacting effects of age and frequency band have not been directly tested in sensor and source space while controlling for aperiodic components. In the current study we address these limitations. We recruited 54 healthy younger and older adults and measured neural oscillations using a high-density electroencephalogram (EEG) system during resting-state with eyes closed. After preprocessing the EEG data and controlling for aperiodic components, we computed alpha and beta power in both sensor and source space. Permutation two-way ANOVAs between frequency band and age group were performed across all electrodes and across all dipoles. Our findings revealed significant interactions in sensorimotor, parietal, and occipital regions. The pattern driving the interaction varied across regions, with older age associated with a progressive decrease in alpha power and a progressive increase in beta power from parietal to sensorimotor regions. Our findings demonstrate that age-related changes in neural oscillations vary as a function of brain region and frequency band. We interpret our findings in the context of clinical and preclinical evidence of age effects on the cholinergic circuit and the Cortico-Basal Ganglia-Thalamo-Cortical (CBGTC) circuit.

Our current understanding of response inhibition comes from go/no-go studies that draw conclusions based on the overt movement of single limbs (i.e., a single finger pushing a button). In general, go/no-go paradigms have found that an individual’s ability to correctly inhibit the motor system is indicative of a healthy central nervous system. However, measuring inhibition by an overt behavioral response may lack the sensitivity to conclude whether the motor system is completely inhibited. Therefore, our goal was to use behavioral and neurophysiological measures to investigate inhibition of the motor system during a full-body reaching task. When directly comparing neurophysiological and behavioral measures, we found that neurophysiological measures were associated with a greater number of errors during no-go trials and faster onset times during go trials. Further analyses revealed a negative correlation between errors and onset times, such that the muscles that activated the earliest during go trials also had the greatest number of errors during no-go trials. Together, our observations show that the absence of an overt behavioral response does not always translate to total inhibition of the motor system.

Regulator of G-protein signaling 10 (RGS10), a key homeostatic regulator of immune cells, has been implicated in multiple diseases associated with aging and chronic inflammation including Parkinson’s Disease (PD). Interestingly, subjects with idiopathic PD display reduced levels of RGS10 in subsets of peripheral immune cells. Additionally, individuals with PD have been shown to have increased activated peripheral immune cells in cerebrospinal fluid (CSF) compared to age-matched healthy controls. However, it is unknown whether peripheral immune cells in the CSF of individuals with PD also exhibit decreased levels of RGS10. Utilizing the Michael J. Fox Foundation Parkinson’s Progression Markers Initiative (PPMI) study we found that RGS10 levels are decreased in the CSF of individuals with PD compared to healthy controls and prodromal individuals. As RGS10 levels are decreased in the CSF and circulating peripheral immune cells of individuals with PD, we hypothesized that RGS10 regulates peripheral immune cell responses to chronic systemic inflammation (CSI) prior to the onset of neurodegeneration. To test this, we induced CSI for 6 weeks in C57BL6/J mice and RGS10 KO mice to assess circulating and CNS-associated immune cell responses. We found that RGS10 deficiency synergizes with CSI to induce a bias for inflammatory and cytotoxic cell populations, a reduction in antigen presentation machinery in peripheral blood immune cells, as well as in and around the brain that is most notable in males. These results highlight RGS10 as an important regulator of the systemic immune response to CSI and implicate RGS10 as a potential contributor to the development of immune dysregulation in PD.

Background Autism spectrum disorder (ASD) is a lifelong condition that profoundly impacts health, independence, and quality of life. However, research on brain aging in autistic adults is limited, and microstructural variations in white and gray matter remain poorly understood. To address this critical gap, we assessed novel diffusion MRI (dMRI) biomarkers, free water, and free water corrected fractional anisotropy (fwcFA), and mean diffusivity (fwcMD) across 32 transcallosal tracts and their corresponding homotopic grey matter origin/endpoint regions of interest (ROIs) in middle and old aged autistic adults. Methods Forty-three autistic adults aged 30–73 and 43 age-, sex-, and IQ-matched neurotypical controls underwent dMRI scans. We examined free water, fwcFA, fwcMD differences between the two groups and age-related pattern of each dMRI metric across the whole brain for each group. The relationships between clinical measures of ASD and free water in regions that significantly differentiated autistic adults from neurotypical controls were also explored. In supplementary analyses, we also assessed free water uncorrected FA and MD using conventional single tensor modeling. Results Autistic adults exhibited significantly elevated free water in seven frontal transcallosal tracts compared to controls. In controls, age-related increases in free water and decreases in fwcFA were observed across most transcallosal tracts. However, these age-associated patterns were entirely absent in autistic adults. In gray matter, autistic adults showed elevated free water in the calcarine cortices and lower fwcMD in the dorsal premotor cortices compared to controls. Lastly, age-related increases in free water were found across all white matter and gray matter ROIs in neurotypical controls, whereas no age-related associations were detected in any dMRI metrics for autistic adults. Limitations We only recruited cognitively capable autistic adults, which limits the generalizability of our findings across the full autism spectrum. The cross-sectional design precludes inferences about microstructural changes over time in middle and old aged autistic adults. Conclusions Our findings revealed increased free water load in frontal white matter in autistic adults and identified distinct age-associated microstructural variations between the two groups. These findings highlight more heterogeneous brain aging profiles in autistic adults. Our study also demonstrated the importance of quantifying free water in dMRI studies of ASD.