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BackgroundReduced cortical sensorimotor inhibition is associated with mobility and cognitive impairments in people with Parkinson's disease (PD) and older adults (OAs). However, there is a lack of clarity regarding the relationships among sensorimotor, cognitive, and mobility impairments. The purpose of this study was to determine how cortical sensorimotor inhibition relates to impairments in mobility and cognition in people with PD and OAs.MethodCortical sensorimotor inhibition was characterized with short-latency afferent inhibition (SAI) in 81 people with PD and 69 OAs. Six inertial sensors recorded single- and dual-task gait and postural sway characteristics during a 2-minute walk and a 1-minute quiet stance. Cognition was assessed across the memory, visuospatial, executive function, attention, and language domains.ResultsSAI was significantly impaired in the PD compared to the OA group. The PD group preformed significantly worse across all gait and postural sway tasks. In PD, SAI significantly correlated with single-task foot strike angle and stride length variability, sway area, and jerkiness of sway in the coronal and sagittal planes. In OAs, SAI significantly related to single-task gait speed and stride length, dual-task stride length, and immediate recall (memory domain). No relationship among mobility, cognition, and SAI was observed.ConclusionsImpaired SAI related to slower gait in OA and to increased gait variability and postural sway in people with PD, all of which have been shown to be related to increased fall risk.

A complete understanding of cognitive function in humansmust incorporate a model of interactions between networkedbrain regions. Alterations to these network interactions under-lie cognitive impairment in many neurodegenerative diseases,providing an important physiological link between brain struc-ture and cognitive function. Cognitive architectures have of-ten been used to explain how healthy brains function, typi-cally using task-based activity. However, this description isincomplete. Most systems-level brain activity is spontaneous,or intrinsic, and occurs whether or not a subject is performinga task. Here, we provide evidence that the Common Modelof Cognition, a consensus model derived from an analysis ofexisting cognitive architectures, can (a) be generalized to ac-count for brain activity at rest, rather than during tasks, and (b)correctly identify differences in basal ganglia connectivity inParkinson’s Disease.

Background/objectivesThe salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function.Subjects/methodsMonozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin, and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders.ResultsSN connectivity was reduced by a meal ingestion (β = -0.20; P

Background: Mobility and sensorimotor inhibition impairments are heterogeneous in Parkinson's disease (PD). Genetics may contribute to this heterogeneity since the apolipoprotein (APOE) ε4 allele and glucocerebrosidase (GBA) gene variants have been related to mobility impairments in otherwise healthy older adult (OA) and PD cohorts. The purpose of this study is to determine if APOE or GBA genetic status affects sensorimotor inhibition and whether the relationship between sensorimotor inhibition and mobility differs in genetic sub-groups of PD. Methods: Ninety-three participants with idiopathic PD (53 non-carriers; 23 ε4 carriers; 17 GBA variants) and 72 OA (45 non-carriers; 27 ε4 carriers) had sensorimotor inhibition characterized by short-latency afferent inhibition. Mobility was assessed in four gait domains (pace/turning, rhythm, trunk, variability) and two postural sway domains (area/jerkiness and velocity) using inertial sensors. Results: Sensorimotor inhibition was worse in the PD than OA group, with no effect of genetic status. Gait pace/turning was slower and variability was higher (p < 0.01) in PD compared to OA. Postural sway area/jerkiness (p < 0.01) and velocity (p < 0.01) were also worse in the PD than OA group. Genetic status was not significantly related to any gait or postural sway domain. Sensorimotor inhibition was significantly correlated with gait variability (r = 0.27; p = 0.02) and trunk movement (r = 0.23; p = 0.045) in the PD group. In PD non-carriers, sensorimotor inhibition related to variability (r = 0.35; p = 0.010) and trunk movement (r = 0.31; p = 0.025). In the PD ε4 group, sensorimotor inhibition only related to rhythm (r = 0.47; p = 0.024), while sensorimotor inhibition related to pace/turning (r = -0.49; p = 0.046) and rhythm (r = 0.59; p = 0.013) in the PD GBA group. Sensorimotor inhibition was significantly correlated with gait pace/turning (r = -0.27; p = 0.04) in the OA group. There was no relationship between sensorimotor inhibition and postural sway. Conclusion: ε4 and GBA genetic status did not affect sensorimotor inhibition or mobility impairments in this PD cohort. However, worse sensorimotor inhibition was associated with gait variability in PD non-carriers, but with gait rhythm in PD ε4 carriers and with gait rhythm and pace in PD with GBA variants. Impaired sensorimotor inhibition had a larger effect on mobility in people with PD than OA and affected different domains of mobility depending on genetic status.

IntroductionGait and balance impairments are cardinal features of Parkinson's disease (PD) that require cognitive input. However, the extent to which specific gait and balance characteristics relate to cognition in PD is unclear. In addition, independent models of gait and balance have not been developed from the same cohort. We aimed to i) develop models of gait and balance in a large PD cohort and ii) determine which gait and balance characteristics best related to cognition.MethodsOne hundred and ninety-eight people with PD were recruited to the Pacific Udall Center. Using six inertial sensors (APDM, Inc.), comprehensive gait measurements were collected over a 2-min continuous walk and comprehensive static balance measures were collected during a 60-second standing task. Six domains of cognition were assessed: global cognition, attention, executive function, language, memory, and visuospatial function. Correlations and hierarchical linear regression determined independent associations.ResultsPrincipal components analysis identified a gait model containing four domains accounting for 80.1% of total variance: pace/turning, rhythm, variability, and trunk. The balance model contained four independent domains accounting for 84.5% of total variance: sway area/jerkiness, sway velocity, sway frequency anteroposterior, and sway frequency mediolateral. Gait domains of pace/turning and variability were strongly associated with attention and executive function. Sway area and jerkiness of balance associated with attention and visuospatial function.ConclusionsGait and balance characteristics were associated with specific types of cognition. The specific relationships between gait or balance with cognitive functions suggests shared cerebral cortical circuitry for mobility and cognitive functions.

Purpose: Studies investigating language deficits in individuals with left temporal-lobe epilepsy have consistently demonstrated impairments in proper name retrieval. The aim of this Phase I rehabilitation study was to investigate the effects of a linguistically distributed word retrieval treatment on proper name retrieval in an individual with left temporal-lobe epilepsy. Method: A 61-year old right-handed male with left temporal-lobe epilepsy (clinical onset at the age of 50) and a deficit in proper name retrieval participated in this study. A single-subject, repeated-probe ABAA design with testing before, immediately after, and 3 months after treatment completion was employed. Proper name retrieval treatment was administered 2 hr per day for 5 days. Results: Results demonstrated improved naming on trained items and maintenance of trained items 3 months after treatment completion. Conclusion: Treatment, which took advantage of the individual's undamaged linguistic networks, promoted the reorganization of networks supporting proper naming, leading to improved proper name retrieval. Further research replicating these findings in individuals with varying degrees of proper name retrieval impairment is warranted. Additionally, the mechanism behind the observed improvements in proper name retrieval needs to be investigated further using functional neuroimaging. (Contains 1 table and 1 figure.)

Background: While traditional histologic neuropathological assessment of neurodegenerative disease has tremendous diagnostic value, insights into neurodegeneration's pathophysiological underpinnings can be significantly enhanced with large‐scale quantitative analyses. As part of the Seattle Alzheimer's Disease Brain Cell Atlas (SEA‐AD), we present a neuropathology dataset across 84 brains spanning the spectrum of AD neuropathologic change donated by UW Alzheimer's Disease Research Center and Adult Changes in Thought study participants. Method: Human brain tissue was collected at rapid autopsy (postmortem interval <12 hours). One hemisphere (randomly selected) was embedded in alginate for uniform coronal slicing (4mm), with alternating slabs fixed in 10% neutral buffered formalin or frozen in a dry ice isopentane slurry. Superior and Middle Temporal Gyrus (MTG) was sampled from fixed slabs and subjected to standard processing, embedding, sectioning (5µm), histochemical (H&E/Luxol fast blue), and immunohistochemical (duplex pTau and pTDP‐43, Aβ and Iba1, and monoplex GFAP, a‐synuclein, and NeuN) labeling. HALO image analysis software (Indica Labs, Albuquerque NM) was used to define and quantify relevant cellular and pathological features within each cortical layer (Figures 1‐3). Result: 84 individuals were included in these analyses (Table 1). While quantitative metrics of pTau and Aβ aligned with traditional neuropathological measures, they showed substantial variability within discrete diagnostic stages (Figure 4). These findings were robust to quantification (discrete count vs. total area stained) and normalization (total nuclei vs. total area analyzed) methods, and highlight the importance of deploying highly quantitative, continuous measures of pathology in the study of neurodegeneration. This unique resource provides spatially preserved measures of pathologic burden across the spectrum of AD with potential for correlative analysis across pathologies, clinical and biomarker parameters, and omics applications to better support the identification of vulnerable cell types in early stages of AD progression, the principal goal of SEA‐AD. Conclusion: Here we present a large‐scale quantitative neuropathology dataset, which enables analysis of pathological proteins and cell types at unprecedented scale and accuracy. Little is known about the interactions of AD‐relevant cell types with pathologic peptides across disease progression. The presented analyses exemplify the potential of this unique publicly‐accessible resource to identify and quantify novel disease‐relevant relationships. [ABSTRACT FROM AUTHOR]