Algorithm-defined memory impairment in older American Indians: The Strong Heart Study.

OBJECTIVE: Assessment of cognition in American Indians poses challenges, including barriers to healthcare, unvalidated clinical standards, and confounding social determinants of health. Alternative strategies for case identification include algorithmic methods, which can outperform clinical judgment in some circumstances. METHOD: Algorithmic methods can be maximized using single-domain tests with multiple-serial trial tasks, such as the California Verbal Learning Test II-Short Form (CVLT-SF). We collected CVLT-SF and detailed clinical data, including dementia gold standard by consensus adjudication, in 818 American Indians aged 65-95 in 2010-2013 and repeated in 403 returning participants in 2017-2019 (mean follow-up 6.7 years, range: 4-9). Our algorithm categorized CVLT-SF scores into four memory deficit categories: none, encoding, storage, and retrieval. RESULTS: At Visit 1, 75.4% had no memory deficit, 15.6% encoding deficit, 3.5% storage deficit, and 5.5% retrieval deficit. At Visit 2, comparable percentages were 68.7%, 10.6%, 6.5%, and 14.2% (respectively). The majority with any deficit at Visit 1-especially encoding-were lost to follow-up by Visit 2. Most with deficits at Visit 2 were newly categorized from those previously intact. The performance of our memory algorithm, compared with adjudication for dementia, was moderately good: correct classification 69%, sensitivity 51%, and specificity 91%. CONCLUSIONS: These descriptive findings encompass a novel contribution in defining memory impairment among American Indians from a single cognitive test. However, more work is needed to improve the sensitivity of this algorithm and maximize its utility for case identification over conventional methods. Altogether, these data provide an important step toward better cognitive characterization and dementia care for an understudied, underserved population. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Unraveling Alzheimer's Disease: Investigating Dynamic Functional Connectivity in the Default Mode Network through DCC-GARCH Modeling.

Alzheimer's disease (AD) has a prolonged latent phase. Sensitive biomarkers of amyloid beta ( A ß ), in the absence of clinical symptoms, offer opportunities for early detection and identification of patients at risk. Current A ß biomarkers, such as CSF and PET biomarkers, are effective but face practical limitations due to high cost and limited availability. Recent blood plasma biomarkers, though accessible, still incur high costs and lack physiological significance in the Alzheimer's process. This study explores the potential of brain functional connectivity (FC) alterations associated with AD pathology as a non-invasive avenue for A ß detection. While current stationary FC measurements lack sensitivity at the single-subject level, our investigation focuses on dynamic FC using resting-state functional MRI (rs-fMRI) and introduces the Generalized Auto-Regressive Conditional Heteroscedastic Dynamic Conditional Correlation (DCC-GARCH) model. Our findings demonstrate the superior sensitivity of DCC-GARCH to CSF A ß status, and offer key insights into dynamic functional connectivity analysis in AD.

A Framework for the Administration of Anti-amyloid Monoclonal Antibody Treatments in Early-Stage Alzheimer's Disease.

The US Food and Drug Administration (FDA) approval of lecanemab for early-stage Alzheimer's disease (AD) represents an exciting new chapter in the management of neurodegenerative disease, but likewise presents numerous clinical, technical, and financial logistical challenges for both academic and non-academic medical institutions hoping to administer this drug. Minimal resources exist that provide guidance for establishing and maintaining a lecanemab treatment program at the institutional level. The current report aims to provide healthcare institutions a framework for the planning, onboarding, and longitudinal treatment of AD with anti-amyloid monoclonal antibody treatments. We present an implementation study involving three stages: (1) feasibility assessment, (2) operations and going live, and (3) monitoring assessment. We found that implementation of lecanemab in clinical practice was feasible due to the assignment of an enterprise-wide project manager to facilitate the planning phase, a cost analysis showing that lecanemab was financially sustainable, and the development of electronic medical record tools to support operational efficiency.

Epidemiology and prevalence of dementia and Alzheimer's disease in American Indians: Data from the Strong Heart Study.

INTRODUCTION: Accurate epidemiologic estimates for dementia are lacking for American Indians, despite substantive social and health disparities. METHODS: The Strong Heart Study, a population-based cohort of 11 American Indian tribes, conducted detailed cognitive testing and examinations over two visits approximately 7 years apart. An expert panel reviewed case materials for consensus adjudication of cognitive status (intact; mild cognitive impairment [MCI]; dementia; other impaired/not MCI) and probable etiology (Alzheimer's disease [AD], vascular bain injury [VBI], traumatic brain injury [TBI], other). RESULTS: American Indians aged 70-95 years had 54% cognitive impairment including 10% dementia. VBI and AD were primary etiology approximately equal proportions (>40%). Apolipoprotein (APO) Eε4 carriers were more common among those with dementia (p = 0.040). Plasma pTau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were higher among those with cognitive impairment, but not amyloid beta (Aß). Cognitive intact had mean 3MSE 92.2 (SD 6.4) and mean Montreal Cognitive Assessment (MoCA) score of 21.3 (SD 3.2). DISCUSSION: This is the first population-based study to estimate the prevalence of vascular and Alzheimer's dementias in a population-based study of American Indians. HIGHLIGHTS: The Strong Heart Study is a population-based cohort of American Indian tribes, conducted over 30+ years and three US geographic regions (Northern Plains, Southern Plains, Southwest). Our teams conducted detailed cognitive testing, neurological examination, and brain imaging over two visits approximately 7 years apart. An expert panel reviewed collected materials for consensus-based adjudication of cognitive status (intact; MCI; dementia; other impaired/not MCI) and probable underlying etiology (AD; VBI; TBI; other). In this cohort of American Indians aged 70-95, 54% were adjudicated with cognitive impairment, including approximately 35% MCI and 10% dementia. These data expand on prior reports from studies using electronic health records, which had suggested prevalence, and incidence of dementia in American Indians to be more comparable to the majority population or non-Hispanic White individuals, perhaps due to latent case undercounts in clinical settings. Vascular and neurodegenerative injuries were approximately equally responsible for cognitive impairment, suggesting that reduction of cardiovascular disease is needed for primary prevention. Traumatic injury was more prevalent than in other populations, and common among those in the "other/not MCI" cognitive impairment category. Mean scores for common dementia screening instruments-even among those adjudicated as unimpaired-were relatively low compared to other populations (mean unimpaired 3MSE 92.2, SD 6.4; mean unimpaired MoCA 21.3, SD 3.2), suggesting the need for cultural and environmental adaptation of common screening and evaluation instruments.

Plasma biomarkers of Alzheimer's disease and related dementias in American Indians: The Strong Heart Study.

INTRODUCTION: Identification of Alzheimer's disease (AD) needs inexpensive, noninvasive biomarkers, with validation in all populations. METHODS: We collected plasma markers in older American Indian individuals: phosphorylated-tau181 (pTau181); amyloid-beta (Aß) 40,42; glial fibrillary acidic protein (GFAP); and neurofilament light chain (NfL). Plasma markers were analyzed for discriminant properties with cognitive status and etiology using receiver operating characteristic (ROC) analysis. RESULTS: PTau181, GFAP, NfL plasma values were significantly associated with cognition, but Aß were not. Discriminant performance was moderate for individual markers, with pTau181, GFAP, NfL performing best, but an empirically selected panel of markers (age, sex, education, pTau181, GFAP, NfL, Aß4240 ratio) had excellent discriminant performance (AUC > 0.8). DISCUSSION: In American Indian individuals, pTau181 and Aß values suggested more common pathology than in majority populations. Aß was less informative than in other populations; however, all four markers were needed for a best-performing dementia diagnostic model. These data validate utility of AD plasma markers, while suggesting population-specific diagnostic characteristics.

Protocol for the Systematic Fixation, Circuit-Based Sampling, and Qualitative and Quantitative Neuropathological Analysis of Human Brain Tissue.

Human brain tissue has long been a critical resource for neuroanatomy and neuropathology, but with the advent of advanced imaging and molecular sequencing techniques, it has become possible to use human brain tissue to study, in great detail, the structural, molecular, and even functional underpinnings of human brain disease. In the century following the first description of Alzheimer's disease (AD), numerous technological advances applied to human tissue have enabled novel diagnostic approaches using diverse physical and molecular biomarkers, and many drug therapies have been tested in clinical trials (Schachter and Davis, Dialogues Clin Neurosci 2:91-100, 2000). The methods for brain procurement and tissue stabilization have remained somewhat consistently focused on formalin fixation and freezing. Although these methods have enabled research protocols of multiple modalities, new, more advanced technologies demand improved methodologies for the procurement, characterization, stabilization, and preparation of both normal and diseased human brain tissues. Here, we describe our current protocols for the procurement and characterization of fixed brain tissue, to enable systematic and precisely targeted diagnoses, and describe the novel, quantitative molecular, and neuroanatomical studies that broadly expand the use of formalin-fixed, paraffin-embedded (FFPE) tissue that will further our understanding of the mechanisms underlying human neuropathologies.

Educational and Clinical Associations With Longitudinal Cognitive Function and Brain Imaging in American Indians: The Strong Heart Study.

BACKGROUND: Little is known about incidence of vascular and Alzheimer's dementias in American Indians. METHODS We conducted a large, heterogeneous, population-based, longitudinal cohort study of brain aging in community-dwelling American Indians aged 64-95 years from 11 tribes across 3 states, with neurological examinations, 1.5T magnetic resonance imaging (MRI), and extensive cognitive testing. Visit 1 in 2010-2013 (n=817) and Visit 2 in 2017-2019 (n=403) included all willing, surviving participants. Standardized cognitive tests at both visits included Modified Mini Mental Status Examination (3MSE), Wechsler Adult Intelligence Scale digit symbol coding (WAIS), Controlled Oral Word Association fas (COWA), California Verbal Learning Test short form (CVLT). Test materials added at follow-up included Wide Range Achievement (reading) Test (WRAT) and National Alzheimer's Coordinating Center Uniform Data Set cognitive battery (v3 form C2) , including Montreal Cognitive Assessment (MoCA). MRI neuroradiologists coded infarcts, hemorrhages, white matter hyperintensities, sulcal atrophy, and ventricle enlargement. RESULTS Mean time between exams was 6.7 years (SD 1.1, range 3.8-9.1). Years of formal education had modest correlation with WRAT reading score (r=0.45). Prevalence and incidence of infarcts were (respectively) 32% and 12.8/1000 person-years (PY); hemmorhages 6% and 4.4/1000 PY; worsening sulci 74% and 19.0/1000 PY; wosening ventricle 79% and 30.1/1000 PY; worsening leukoaraiosis 44% and 26.1/1000 PY. Linear losses per year in cognitive scores were 0.6% 3MSE, 1.2% WAIS, 0.6% COWA, 2.2% CVLT. Mean MoCA scores were 18.9 (SD 4.3). DISCUSSION These are the first data on longitudinal cognitive and imaging changes in American Indians, as well as first reports of AD related features. Mean scores in MoCA were similar or lower than standard cutoffs used to diagnose dementia in other racial/ethnic groups, suggesting that standardized cognitive tests may not perform well in this population. Test validation, adaptation, and score adjustment are warranted. Years of education was a poor proxy for premorbid function, suggesting novel methods for cognitive score contextualization is also needed in this population. Evaluation of selective survival suggests attrition from death and frailty should be accounted for in causal analyses. Overall, these data represent a unique opportunity to examine neurology topics of critical importance to an understudied population.

Prediction of Naming Outcome With fMRI Language Lateralization in Left Temporal Epilepsy Surgery.

BACKGROUND AND OBJECTIVES: Naming decline after left temporal lobe epilepsy (TLE) surgery is common and difficult to predict. Preoperative language fMRI may predict naming decline, but this application is still lacking evidence. We performed a large multicenter cohort study of the effectiveness of fMRI in predicting naming deficits after left TLE surgery. METHODS: At 10 US epilepsy centers, 81 patients with left TLE were prospectively recruited and given the Boston Naming Test (BNT) before and ≈7 months after anterior temporal lobectomy. An fMRI language laterality index (LI) was measured with an auditory semantic decision-tone decision task contrast. Correlations and a multiple regression model were built with a priori chosen predictors. RESULTS: Naming decline occurred in 56% of patients and correlated with fMRI LI (r = -0.41, p < 0.001), age at epilepsy onset (r = -0.30, p = 0.006), age at surgery (r = -0.23, p = 0.039), and years of education (r = 0.24, p = 0.032). Preoperative BNT score and duration of epilepsy were not correlated with naming decline. The regression model explained 31% of the variance, with fMRI contributing 14%, with a 96% sensitivity and 44% specificity for predicting meaningful naming decline. Cross-validation resulted in an average prediction error of 6 points. DISCUSSION: An fMRI-based regression model predicted naming outcome after left TLE surgery in a large, prospective multicenter sample, with fMRI as the strongest predictor. These results provide evidence supporting the use of preoperative language fMRI to predict language outcome in patients undergoing left TLE surgery. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that fMRI language lateralization can help in predicting naming decline after left TLE surgery.

Increased Basal Ganglia Modulatory Effective Connectivity Observed in Resting-State fMRI in Individuals With Parkinson's Disease.

Alterations to interactions between networked brain regions underlie cognitive impairment in many neurodegenerative diseases, providing an important physiological link between brain structure and cognitive function. Previous attempts to characterize the effects of Parkinson's disease (PD) on network functioning using resting-state functional magnetic resonance imaging (rs-fMRI), however, have yielded inconsistent and contradictory results. Potential problems with prior work arise in the specifics of how the area targeted by the diseases (the basal ganglia) interacts with other brain regions. Specifically, current computational models point to the fact that the basal ganglia contributions should be captured with modulatory (i.e., second-order) rather than direct (i.e., first-order) functional connectivity measures. Following this hypothesis, a principled but manageable large-scale brain architecture, the Common Model of Cognition, was used to identify differences in basal ganglia connectivity in PD by analyzing resting-state fMRI data from 111 participants (70 patients with PD; 41 healthy controls) using Dynamic Causal Modeling (DCM). Specifically, the functional connectivity of the basal ganglia was modeled as two second-level, modulatory connections that control projections from sensory cortices to the prefrontal cortex, and from the hippocampus and medial temporal lobe to the prefrontal cortex. We then examined group differences between patients with PD and healthy controls in estimated modulatory effective connectivity in these connections. The Modulatory variant of the Common Model of Cognition outperformed the Direct model across all subjects. It was also found that these second-level modulatory connections had higher estimates of effective connectivity in the PD group compared to the control group, and that differences in effective connectivity were observed for all direct connections between the PD and control groups.We make the case that accounting for modulatory effective connectivity better captures the effects of PD on network functioning and influences the interpretation of the directionality of the between-group results. Limitations include that the PD group was scanned on dopaminergic medication, results were derived from a reasonable but small number of individuals and the ratio of PD to healthy control participants was relatively unbalanced. Future research will examine if the observed effect holds for individuals with PD scanned off their typical dopaminergic medications.

Association of Performance on Dichotic Auditory Tests With Risk for Incident Dementia and Alzheimer Dementia.

Importance: Age-related hearing difficulties can include problems with signal audibility and central auditory processing. Studies have demonstrated associations between audibility and dementia risk. To our knowledge, limited data exist to determine whether audibility, central processing, or both drive these associations. Objective: To determine the associations between signal sensitivity, central auditory processing, and dementia and Alzheimer dementia (AD) risk. Design, Setting, and Participants: This follow-up observational study of a sample from the prospective Adult Changes in Thought study of dementia risk was conducted at Kaiser Permanente Washington, a western Washington health care delivery system, and included 280 volunteer participants without dementia who were evaluated from October 2003 to February 2006 with follow-up through September 2018. Analyses began in 2019 and continued through 2021. Exposures: Hearing tests included pure tone signal audibility, a monaural word recognition test, and 2 dichotic tests: the Dichotic Sentence Identification (DSI) test and the Dichotic Digits test (DDT). Main Outcomes and Measures: Cognition was assessed biennially with the Cognitive Abilities Screening Instrument (range, 1-100; higher scores are better), and scores of less than 86 prompted clinical and neuropsychological evaluations. All data were reviewed at multidisciplinary consensus conferences, and standardized criteria were used to define incident cases of dementia and probable or possible AD. Cox proportional hazard models were used to determine associations with hearing test performance. Results: A total of 280 participants (177 women [63%]; mean [SD] age, 79.5 [5.2] years). As of September 2018, there were 2196 person-years of follow-up (mean, 7.8 years) and 89 incident cases of dementia (66 not previously analyzed), of which 84 (94.4%) were AD (63 not previously analyzed). Compared with people with DSI scores of more than 80, the dementia adjusted hazard ratio (aHR) for DSI scores of less than 50 was 4.18 (95% CI, 2.37-7.38; P < .001); for a DSI score of 50 to 80, it was 1.82 (95% CI, 1.10-3.04; P = .02). Compared with people with DDT scores of more than 80, the dementia aHR for DDT scores of less than 50 was 2.66 (95% CI, 1.31-5.42; P = .01); for a DDT score of 50 to 80, it was 2.40 (95% CI, 1.45-3.98; P = .001). The AD results were similar. Pure tone averages were weakly and insignificantly associated with dementia and AD, and associations were null when controlling for DSI scores. Conclusions and Relevance: In this cohort study, abnormal central auditory processing as measured by dichotic tests was independently associated with dementia and AD risk.

Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease.

We propose a novel framework for Alzheimer's disease (AD) detection using brain MRIs. The framework starts with a data augmentation method called Brain-Aware Replacements (BAR), which leverages a standard brain parcellation to replace medically-relevant 3D brain regions in an anchor MRI from a randomly picked MRI to create synthetic samples. Ground truth "hard" labels are also linearly mixed depending on the replacement ratio in order to create "soft" labels. BAR produces a great variety of realistic-looking synthetic MRIs with higher local variability compared to other mix-based methods, such as CutMix. On top of BAR, we propose using a soft-label-capable supervised contrastive loss, aiming to learn the relative similarity of representations that reflect how mixed are the synthetic MRIs using our soft labels. This way, we do not fully exhaust the entropic capacity of our hard labels, since we only use them to create soft labels and synthetic MRIs through BAR. We show that a model pre-trained using our framework can be further fine-tuned with a cross-entropy loss using the hard labels that were used to create the synthetic samples. We validated the performance of our framework in a binary AD detection task against both from-scratch supervised training and state-of-the-art self-supervised training plus fine-tuning approaches. Then we evaluated BAR's individual performance compared to another mix-based method CutMix by integrating it within our framework. We show that our framework yields superior results in both precision and recall for the AD detection task.

Superior Verbal Memory Outcome After Stereotactic Laser Amygdalohippocampotomy.

Objective: To evaluate declarative memory outcomes in medically refractory epilepsy patients who underwent either a highly selective laser ablation of the amygdalohippocampal complex or a conventional open temporal lobe resection. Methods: Post-operative change scores were examined for verbal memory outcome in epilepsy patients who underwent stereotactic laser amygdalohippocampotomy (SLAH: n = 40) or open resection procedures (n = 40) using both reliable change index (RCI) scores and a 1-SD change metric. Results: Using RCI scores, patients undergoing open resection (12/40, 30.0%) were more likely to decline on verbal memory than those undergoing SLAH (2/40 [5.0%], p = 0.0064, Fisher's exact test). Patients with language dominant procedures were much more likely to experience a significant verbal memory decline following open resection (9/19 [47.4%]) compared to laser ablation (2/19 [10.5%], p = 0.0293, Fisher's exact test). 1 SD verbal memory decline frequently occurred in the open resection sample of language dominant temporal lobe patients with mesial temporal sclerosis (8/10 [80.0%]), although it rarely occurred in such patients after SLAH (2/14, 14.3%) (p = 0.0027, Fisher's exact test). Memory improvement occurred significantly more frequently following SLAH than after open resection. Interpretation: These findings suggest that while verbal memory function can decline after laser ablation of the amygdalohippocampal complex, it is better preserved when compared to open temporal lobe resection. Our findings also highlight that the dominant hippocampus is not uniquely responsible for verbal memory. While this is at odds with our simple and common heuristic of the hippocampus in memory, it supports the findings of non-human primate studies showing that memory depends on broader medial and lateral TL regions.

Leveraging Neuroimaging Tools to Assess Precision and Accuracy in an Alzheimer's Disease Neuropathologic Sampling Protocol.

INTRODUCTION: The study of Alzheimer's disease investigates topographic patterns of degeneration in the context of connected networks comprised of functionally distinct domains using increasingly sophisticated molecular techniques. Therefore, obtaining high precision and accuracy of neuropathologic tissue sampling will enhance the reliability of molecular studies and contribute to the understanding of Alzheimer's disease pathology. Neuroimaging tools can help assess these aspects of current sampling protocols as well as contribute directly to their improvement. METHODS: Using a virtual sampling method on magnetic resonance images (MRIs) from 35 participants (21 women), we compared the precision and accuracy of traditional neuropathologic vs. neuroimaging-guided sampling. The impact of the resulting differences was assessed by evaluating the functional connectivity pattern of regions selected by each approach. RESULTS: Virtual sampling using the traditional neuropathologic approach had low neuroanatomical precision and accuracy for all cortical regions tested. Neuroimaging-guided strategies narrowed these gaps. Discrepancies in the location of traditional and neuroimaging-guided samples corresponded to differences in fMRI measures of functional connectivity. DISCUSSION: Integrating neuroimaging tools with the neuropathologic assessment will improve neuropathologic-neuroimaging correlations by helping to ensure specific functional domains are accurately sampled for quantitative molecular neuropathologic applications. Our neuroimaging-based simulation of current sampling practices provides a benchmark of precision and accuracy against which to measure improvements when using novel tissue sampling approaches. Our results suggest that relying on gross landmarks alone to select samples at autopsy leads to significant variability, even when sampled by the same neuropathologist. Further, this exercise highlights how sampling precision could be enhanced if neuroimaging were integrated with the standard neuropathologic assessment. More accurate targeting and improved biological homogeneity of sampled brain tissue will facilitate the interpretation of neuropathological analyses in AD and the downstream research applications of brain tissue from biorepositories.

Alzheimer's Disease-Related Neuropathology Among Patients with Medication Treated Type 2 Diabetes in a Community-Based Autopsy Cohort.

BACKGROUND: Diabetes is a risk factor for Alzheimer's disease and related dementias (ADRD). Epidemiologic evidence shows an association between diabetes medications and ADRD risk; cell and mouse models show diabetes medication association with AD-related neuropathologic change (ADNC). OBJECTIVE: This hypothesis-generating analysis aimed to describe autopsy-measured ADNC for individuals who used diabetes medications. METHODS: Descriptive analysis of ADNC for Adult Changes in Thought (ACT) Study autopsy cohort who used diabetes medications, including sulfonylureas, insulin, and biguanides; total N = 118. ADNC included amyloid plaque distribution (Thal phasing), neurofibrillary tangle (NFT) distribution (Braak stage), and cortical neuritic plaque density (CERAD score). We also examined quantitative measures of ADNC using the means of standardized Histelide measures of cortical PHF-tau and Aß1-42. Adjusted analyses control for age at death, sex, education, APOE genotype, and diabetes complication severity index. RESULTS: Adjusted analyses showed no significant association between any drug class and traditional neuropathologic measures compared to nonusers of that class. In adjusted Histelide analyses, any insulin use was associated with lower mean levels of Aß1-42 (-0.57 (CI: -1.12, -0.02)) compared to nonusers. Five years of sulfonylureas and of biguanides use was associated with lower levels of Aß1-42 compared to nonusers (-0.15 (CI: -0.28, -0.02), -0.31 (CI: -0.54, -0.07), respectively). CONCLUSION: Some evidence exists that diabetes medications are associated with lower levels of Aß1-42, but not traditional measures of neuropathology. Future studies are needed in larger samples to build understanding of the mechanisms between diabetes, its medications, and ADRD, and to potentially repurpose existing medications for prevention or delay of ADRD.

Reassessing relationships between appetite and adiposity in people at risk of obesity: A twin study using fMRI.

BACKGROUND: Neuroimaging studies suggest that appetitive drive is enhanced in obesity. OBJECTIVE: To test if appetitive drive varies in direct proportion to the level of body adiposity after accounting for genetic factors that contribute to both brain response and obesity risk. SUBJECTS/METHODS: Participants were adult monozygotic (n = 54) and dizygotic (n = 30) twins with at least one member of the pair with obesity. Body composition was assessed by dual-energy X-ray absorptiometry. Hormonal and appetite measures were obtained in response to a standardized meal that provided 20% of estimated daily caloric needs and to an ad libitum buffet meal. Pre- and post-meal functional magnetic resonance imaging (fMRI) assessed brain response to visual food cues in a set of a priori appetite-regulating regions. Exploratory voxelwise analyses outside a priori regions were performed with correction for multiple comparisons. RESULTS: In a group of 84 adults, the majority with obesity (75%), body fat mass was not associated with hormonal responses to a meal (glucose, insulin, glucagon-like peptide-1 and ghrelin, all P>0.40), subjective feelings of hunger (ß=-0.01 mm [95% CI -0.35, 0.34] P = 0.97) and fullness (ß=0.15 mm [-0.15, 0.44] P = 0.33), or buffet meal intake in relation to estimated daily caloric needs (ß=0.28% [-0.05, 0.60] P = 0.10). Body fat mass was also not associated with brain response to high-calorie food cues in appetite-regulating regions (Pre-meal ß=-0.12 [-0.32, 0.09] P = 0.26; Post-meal ß=0.18 [-0.02, 0.37] P = 0.09; Change by a meal ß=0.29 [-0.02, 0.61] P = 0.07). Conversely, lower fat mass was associated with being weight reduced (ß=-0.05% [-0.07, -0.03] P<0.001) and greater pre-meal activation to high-calorie food cues in the dorsolateral prefrontal cortex (Z = 3.63 P = 0.017). CONCLUSIONS: In a large study of adult twins, the majority with overweight or obesity, the level of adiposity was not associated with excess appetitive drive as assessed by behavioral, hormonal, or fMRI measures.

Relationships Between Sensorimotor Inhibition and Mobility in Older Adults With and Without Parkinson's Disease.

BACKGROUND: Reduced 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. METHOD: Cortical 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. RESULTS: SAI 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. CONCLUSIONS: Impaired 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.

Learning Cortical Parcellations Using Graph Neural Networks.

Deep learning has been applied to magnetic resonance imaging (MRI) for a variety of purposes, ranging from the acceleration of image acquisition and image denoising to tissue segmentation and disease diagnosis. Convolutional neural networks have been particularly useful for analyzing MRI data due to the regularly sampled spatial and temporal nature of the data. However, advances in the field of brain imaging have led to network- and surface-based analyses that are often better represented in the graph domain. In this analysis, we propose a general purpose cortical segmentation method that, given resting-state connectivity features readily computed during conventional MRI pre-processing and a set of corresponding training labels, can generate cortical parcellations for new MRI data. We applied recent advances in the field of graph neural networks to the problem of cortical surface segmentation, using resting-state connectivity to learn discrete maps of the human neocortex. We found that graph neural networks accurately learn low-dimensional representations of functional brain connectivity that can be naturally extended to map the cortices of new datasets. After optimizing over algorithm type, network architecture, and training features, our approach yielded mean classification accuracies of 79.91% relative to a previously published parcellation. We describe how some hyperparameter choices including training and testing data duration, network architecture, and algorithm choice affect model performance.

Sensorimotor Inhibition and Mobility in Genetic Subgroups of Parkinson's Disease.

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.

White Matter Lesions in Mild Cognitive Impairment and Idiopathic Parkinson's Disease: Multimodal Advanced MRI and Cognitive Associations.

Cerebrovascular disease is a common comorbidity in older adults, typically assessed in terms of white matter hyperintensities (WMHs) on MRI. While it is well known that WMHs exacerbate cognitive symptoms, the exact relation of WMHs with cognitive performance and other degenerative diseases is unknown. Furthermore, based on location, WMHs are often classified into periventricular and deep WMHs and are believed to have different pathological origins. Whether the two types of WMHs influence cognition differently is unclear. Using regression models, we assessed the independent association of these two types of WMHs with cognitive performance in two separate studies focused on distinct degenerative diseases, early Alzheimer's (mild cognitive impairment), and Parkinson's disease. We further tested if the two types of WMHs were differentially associated with reduced cortical cerebral blood flow (CBF) as measured by arterial spin labeling and increased mean diffusivity (MD, a marker of tissue injury) as measured by diffusion imaging. Our approach revealed that both deep and periventricular WMHs were associated with poor performance on tests of global cognition (Montreal cognitive Assessment, MoCA), task processing (Trail making test), and category fluency in the study of mild cognitive impairment. They were associated with poor performance in global cognition (MoCA) and category fluency in the Parkinson's disease study. Of note, more associations were detected between cognitive performance and deep WMHs than between cognitive performance and periventricular WMHs. Mechanistically, both deep and periventricular WMHs were associated with increased MD. Both deep and periventricular WMHs were also associated with reduced CBF in the gray matter.

Temporal lobe regions essential for preserved picture naming after left temporal epilepsy surgery.

OBJECTIVE: To define left temporal lobe regions where surgical resection produces a persistent postoperative decline in naming visual objects. METHODS: Pre- and postoperative brain magnetic resonance imaging data and picture naming (Boston Naming Test) scores were obtained prospectively from 59 people with drug-resistant left temporal lobe epilepsy. All patients had left hemisphere language dominance at baseline and underwent surgical resection or ablation in the left temporal lobe. Postoperative naming assessment occurred approximately 7 months after surgery. Surgical lesions were mapped to a standard template, and the relationship between presence or absence of a lesion and the degree of naming decline was tested at each template voxel while controlling for effects of overall lesion size. RESULTS: Patients declined by an average of 15% in their naming score, with wide variation across individuals. Decline was significantly related to damage in a cluster of voxels in the ventral temporal lobe, located mainly in the fusiform gyrus approximately 4-6 cm posterior to the temporal tip. Extent of damage to this region explained roughly 50% of the variance in outcome. Picture naming decline was not related to hippocampal or temporal pole damage. SIGNIFICANCE: The results provide the first statistical map relating lesion location in left temporal lobe epilepsy surgery to picture naming decline, and they support previous observations of transient naming deficits from electrical stimulation in the basal temporal cortex. The critical lesion is relatively posterior and could be avoided in many patients undergoing left temporal lobe surgery for intractable epilepsy.