bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tracing individual trajectory of longitudinal tau spreading in deep latent space
Authors: Kim Sohee , Cho Hanna , Lee Wha Jin , Kim Sung‐Woo , Lyoo Chul Hyoung , Seong Joon‐Kyung 
Published: February 2022

AbstractBackgroundAlzheimer’s disease (AD) usually appears in mid‐60s (Late‐Onset AD, LOAD), but also rarely appears in patients younger than 65 (Early‐Onset AD, EOAD), while showing distinct features. Tau shows high correlation with AD prognosis and can be detected through positron emission tomography (PET) scan. Tau data mapped into a low dimensional latent space will help detect longitudinal change pattern along AD spectrum. Furthermore, fitting tensors using individual line segments will enable us to track individual tau trajectory in the latent space.MethodWe recruited 74 healthy controls, 75 mild cognitive impairment patients, and 38 AD patients with two PET scans ([18F]Flortaucipir for tau and [18F]Florbetaben for Aβ) with two‐year follow‐up. We used standardized uptake value ratios (SUVRs) for tau PET data. All patients’ tau data went through autoencoder and principal component analysis, pretrained using baseline (BL) tau data. Using only amyloid positive AD patients’ BL – follow‐up (FU) line segments, we fit tensors and tracked individual trajectories in the latent space using a tensor tracing algorithm.ResultIn the 2‐dimensional latent space the points dispersed toward the upper‐ and right‐side as the disease deteriorated. Reconstructed SUVR maps showed tau accumulation pattern of EOAD through x‐axis, such as tau spreading in temporal, prefrontal, and parietal lobes. Reconstructed map of 1st quartile group in y‐axis showed tau spreading dominance in parietal lobe and 4th quartile group showed dominance in prefrontal, temporal lobe. Each patient’s trajectory, predicted based on the latent space, showed reconstructed map following individual tau accumulation pattern. In addition, EOAD tau spreading trajectory tend to precede LOAD tau spreading trajectory.ConclusionWe decomposed high dimensional tau accumulation pattern into 2 independent components through deep‐learning methods. X‐axis showed EOAD tau accumulation pattern and y‐axis was divided into LOAD tau accumulation pattern and non‐prefrontal dominant pattern. In addition, tensor fitting of the longitudinal vector field enables us to find individual tau spreading trajectories which can be used to predict future and past spreading. Even though this study was done using only one factor, tau, it has the potential to be expanded to other factors such as amyloid or neurodegeneration data.
Networking analysis for neuroimaging and genetic markers in Alzheimer's disease
Authors: Moon Seok Woo 
Published: February 2022

AbstractBackgroundThis paper examines late‐onset dementia‐related cognitive impairment and neuroimaging‐genetics biomarker association using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data archive.MethodThe demographics of the 1,026 ADNI 1, ADNI GO and ADNI 2 arms of the ADNI study included participants ages 65 to 85, 266 normal CN’s (CDR=0, Male:138, Female:128), 572 mild cognitively impaired MCI’s (CDR=0.5, Male:227, Female:245), and 188 AD patients (CDR=0.5/1, Male:102, Female:86).The extracted AD‐related imaging and genetic markers were employed in a subsequent network analysis. We used Plink, to model the genetics data, and the Pipeline environment, to develop an end‐to‐end neuroimaging‐genetics data analysis protocol that identified the neuroimaging associations with SNPs and the clinical diagnosis. The expected significant correlations between the SNPs and the neuroimaging phenotypes were confirmed using neuroimaging genetics networking analyses.Genotype dosage data for AD‐associated SNPs were extracted from the imputed ADNI genetics dosage data using sample‐major additive coding. 29 such SNPs were selected (Jansen, et al., 2019) that meet a minor allele frequency threshold (MAF>0.5%).ResultThere were 9 ROIs (7 thicknesses, 1 volume, and 1 gauscurve) which were associated with 6 genomic markers in the level of ‘p<0.001’ in the CN cohort. There were 43 ROIs (31 thicknesses, 11 volume, and 1 pct) which were associated with 5 genomic markers in the level of ‘p<0.001’. There were 10 ROIs (9 thicknesses and 1 volumes) which were associated with 3 genomic markers in the level of ‘p<0.0001 in the MCI cohort. There were 3 ROIs (1 thicknesses, 1 volume, and 1 pct) which were associated with 3 genomic markers in the level of ‘p<0.001’ in the AD cohort. The 29 genes were influencing on the 200 neuroimaging markers with some networking patterns using WGCNA R‐package for the CN, MCI and AD groups, even though we could not find any networking the 29 genes themselves.ConclusionStructural brain changes are important indicators of dementia progression. Network analysis pairing morphometric biomarkers with genetic indicators allows investigation of clinical and phenotypic associations that facilitate deep systematic understanding of genetic and environmental influences on aging and cognitive decline.
Individual variability in the cortical distribution of elevated 18F‐flortaucipir uptake in posterior cortical atrophy
Authors: Katsumi Yuta , Eckbo Ryan , Putcha Deepti , Wong Bonnie , Quimby Megan , McGinnis Scott M. , Touroutoglou Alexandra , Dickerson Brad C. 
Published: February 2022

AbstractBackgroundAccumulating evidence supports the relevance of the localization of tau pathology, as measured with 18F‐flortaucipir (FTP) PET imaging, for characterizing clinical phenotypes of Alzheimer’s disease (AD), including posterior cortical atrophy (PCA). The present study investigated the degree to which the cortical distribution of elevated FTP uptake varies across individual patients with PCA, with the goal to identify regions of heightened vulnerability to tau pathology in this population. Based on available PET imaging evidence and using a systems neuroscience approach, we hypothesized that the majority of PCA patients would exhibit elevated FTP uptake in the visual and dorsal attention networks of the brain, consistent with impairments in basic and higher‐order visual processing characteristic of this syndrome.Method15 patients with PCA underwent FTP PET imaging. Individual FTP standardized uptake value ratio (SUVR) maps were partial volume corrected and projected to template cortical surface space. These individual SUVR maps were converted to Z‐score maps using data obtained from 24 age‐matched healthy control subjects, then binarized at Z > 1.5. Percent overlap maps were created based on the individual binarized Z‐score maps. A parcellation of the cerebral cortex into seven canonical intrinsic functional networks was used to characterize the spatial topography of elevated FTP uptake.Result100% of PCA patients showed elevated FTP uptake in brain regions including bilateral superior parietal lobule, area MT, and importantly, bilateral frontal eye fields, which are key nodes of the dorsal attention network. In more than 80% of patients, elevated signal was also observed bilaterally in the occipital, parietal, and temporal areas that are nodes of the visual, frontoparietal, and default mode networks, with more circumscribed and variable involvement of prefrontal cortex.ConclusionThe results support the hypothesis that tau pathology in PCA universally affects the key nodes of the dorsal attention network consistent with visuospatial and visuomotor deficits commonly observed in PCA, including oculomotor apraxia (impaired voluntary control of eye movements). In addition to the nearly universal involvement of visual association networks, key nodes of default mode and frontoparietal control networks likely subserve other cognitive deficits that are common but more variable in PCA.
Determining the efficacy of non‐pharmacological interventions to manage neuropsychiatric symptoms of dementia in residential aged care settings: A systematic review of systematic reviews
Authors: Koch Jana , Amos Jessica , Mortby Moyra E 
Published: February 2022

AbstractBackgroundNon‐pharmacological interventions such as music, physical activity, and reminiscence provide a cost‐effective and safe approach to managing neuropsychiatric symptoms in neurocognitive disorders. While much research has focused on evaluating the efficacy of individual non‐pharmacological interventions used to manage neuropsychiatric symptoms and inform best practice, they have struggled to provide clear results and recommendations. A possible explanation for the lack of clear results may be the failure of previous studies to examine the efficacy in specific population settings (e.g. residential aged care vs. community settings). This systematic review of systematic reviews evaluates the efficacy of non‐pharmacological interventions used to manage neuropsychiatric symptoms in the context of residential aged care settings only.MethodA systematic review of systematic reviews was conducted. PubMed/Medline, Embase, Cochrane Library and Web of Science were searched for eligible reviews in December 2019 and February 2020. Two authors independently screened title and abstracts, and assessed full‐text reviews for eligibility. The quality of systematic reviews was appraised with ‘AMSTAR‐2: A Measurement tool to assess systematic reviews’. Narrative summaries were created to group findings by intervention domains.ResultFrom 1362 systematic reviews identified, 26 met the inclusion criteria and were included. Of these, 10 focused on person tailored interventions, six on sensory stimulation interventions, three on environmental interventions, three on exercise interventions and four on other interventions. Quality ratings identified reviews to be of mostly moderate quality (73%). The majority of reviews report positive results, but effects were not always statistically significant. Tailored interventions that included music and social elements appeared to be most beneficial for depressive symptoms and mood. Furthermore, outcome measures and intervention protocols were highly heterogenetic across interventions.ConclusionThis systematic review of systematic review highlights the importance of considering intervention settings when evaluating the efficacy of non‐pharmacological interventions in neurocognitive disorders across studies. The findings suggest that in this setting, combining different types of interventions and tailoring them to the personal experiences of the resident is recommended. Use of a more standardized approach for outcome measures is vital in order to accurately assess intervention efficacy and allow for comparison of intervention approaches.
Electrophysiological brain functional network alterations associated with hippocampal volume in healthy and pathological aging
Authors: Torres Lucia , Cuesta Pablo , Fernández Ricardo Bruña , Vilca Brenda Chino , Dolado Alberto Marcos , Fuertes Miguel Yus , Arrazola Juan , Fernandez Alberto , Verdejo Juan , Maestú Fernando , Higes Ramón López 
Published: February 2022

AbstractBackgroundThe early detection of Alzheimer disease is currently one of the main worldwide scientific goals. Estructural biomarkers, such as cortical deterioration and medial temporal lobe atrophy (MTLa), are well known and deeply studied. The relation of these structural changes with brain connectivity could help to understand the consequences of neurodegeneration in brain functioning, with the ultimate goal of explaining cognitive impairment. Magnetoencephalogram (MEG) quantitative analysis is a precise, non‐invasive tool to evaluate changes in bioelectrical activity of the brain. Therefore, it brings us the opportunity to study disruption of functional brain networks associated with changes in MTLa volume, as assessed with structural MRI.MethodWe recruited 376 healthy elders and 130 mild cognitive impairment patients (MCI) (aged from 61 to 85) from the “Hospital Universitario San Carlos” and the Center for elders at the Chamartín District, all located in Madrid, Spain. All of them underwent a neuropsychological evaluation, MRI assessment, and MEG recordings. The MCI diagnosis was established according to the NIA‐AA criteria. None of the participants exhibited a history of psychiatric or neurological disorders (other than MCI). We used a completely data‐driven approach to evaluate the relationship between functional connectivity (FC) and the hippocampal volume.ResultOur main finding was an augmented theta band functional connectivity (FC) in right temporal (RTemp) areas associated with lower hippocampal volume, and we found this FC signature to correlate negatively with memory performance. Furthermore, the average theta FC of this area differed significantly between groups, although the original relationship remained significant for each group independently. Finally, we performed a seed‐based analysis targeting the original right temporal region and found that the modulation of the theta FC was driven by connections to 1) superior frontal and 2) contralateral temporal areas.ConclusionThe results depict a clear FC pattern that seems to be associated with both healthy and pathological aging. This MEG signature may be useful as a non‐invasive biomarker for the progressive subcortical degeneration that occurs along aging, both healthy and pathological. Furthermore, it is also related with cognitive performance, especially with memory functioning.
Comparison of diffusion weighted, imaging‐derived, fractional anisotropy with a novel MRI contrast‐weighted ratio method for measuring myelin in older adults at risk for Alzheimer’s disease
Authors: Price Lauren Rose , Deardorff Rachael , Wu Yu‐Chien , McDonald Brenna C. , West John D. , Risacher Shannon L. , Saykin Andrew J. 
Published: February 2022

AbstractBackgroundMRI measures sensitive to myelin integrity have been investigated as potential AD biomarkers. T1‐weighted/T2‐weighted ratio is a simple yet informative measure, but many cohorts have transitioned to only T1‐weighted and T2‐weighted Fluid Attenuated Inversion Recovery (FLAIR) acquisitions. We previously obtained similar results using FLAIR instead of T2 (T1w/T2FLAIRw). Our goal now is to compare T1w/T2FLAIRw to fractional anisotropy (FA) from diffusion weighted imaging (DWI).MethodPearson’s correlations of T1w/T2FLAIRw and FA values of hippocampal white matter (WM) integrity were calculated in two independent cohorts acquired on different scanners: Cohort 1 (21 CN; 7 SCD; 20 MCI; 4 AD) and Cohort 2 (40 CN; 43 SCD; 45 MCI; 20 AD). Image‐processing algorithms were designed in‐house, building on previous methods and implemented using SPM12 and FSL dtifit. Diagnostic group differences were assessed in both cohorts using one‐way ANOVA and independent sample T‐tests with Tukey correction.ResultCohort 1 demonstrated significant correlation of WM integrity values between methods in the left hippocampus (p=.002) and approached significance in the right (p = .074). Between‐group analyses showed significant differences in left hippocampal WM between cognitively unimpaired (CU [CN and SCD]) and cognitively impaired (CI [MCI and AD]) groups, with follow‐up tests showing differences between CN and AD patients in both methods. Right hippocampal T1w/T2FLAIRw ratio values showed significant differences between CU and CI, though no significant diagnostic group differences. Right hippocampal FA values were not significant.Cohort 2 demonstrated significant bilateral correlation between imaging methods (p < .001), with bilateral significant differences between CU and CI groups in both methods. CN and MCI right hippocampal values were significantly different from each other in both methods. Box plots demonstrated clear similarities in patterns of diagnostic profile between methods.ConclusionA similar overall pattern was observed across the T1w/T2FLAIRw and DWI‐FA methods. This may reflect myelin disruption although further studies are needed to address source of signal differences on imaging. Differences in FA effect sizes for the hippocampus across samples and scanners merits further exploration.
White matter fiber density for vocabulary better maintained than fluid abilities in aging
Authors: Gazes Yunglin , Li Ruiyang , Mensing Ashley , Babukutty Reshma S. , Noofoory Diala , Nazario Geneva Hidalgo , Langfield Christopher , Sakhardande Jayant , Lee Seonjoo 
Published: February 2022

AbstractBackgroundAging research has repeatedly shown that crystallized abilities, cognitive processes reliant on learned knowledge, are well preserved well into old age. On the other hand, fluid abilities, processes that are not knowledge‐dependent, show decline as early as the third decade of life. It is still unclear what mechanism enables the two starkly contrasting aging trajectories to exist all within the same brains.MethodFrom the Reference Ability Neural Network (RANN) study, 181 participants (age=51.2±17.2, 101females) with both baseline and 5‐year follow‐up diffusion weighted imaging data were included in the current analysis. Based on fMRI activation data, the set of brain regions were derived that are associated with performance of each of four cognitive abilities: vocabulary, processing speed, episodic memory, and reasoning. Using these regions as seeds, white matter tracts connecting the brain regions for each ability were extracted and used to calculate the mean fiber density associated with each ability. Three models, linear, partial linear, and quadratic were performed to model the longitudinal changes in fiber density for each ability. Mixed effect regression was used to test whether vocabulary, the only crystallized ability, shows more gradual decline than white matter for the other three abilities, which were all fluid abilities. The non‐linear trend of age was modeled using B‐splines with the knot point selection based on Bayesian information criteria (BIC).ResultConsistent with cross‐sectional results reported in Gazes et al. 2020, mean fiber density for white matter tracts associated with the vocabulary ability was shown to follow a slower decline with age than that for the three fluid abilities – processing speed [F(2,1251)=57.5, p<.001], episodic memory [F(2,1251)=5.32, p<.001), and reasoning [F(2,1251)=4.05, p<.001]. Figure 1 shows the age‐related trajectory modeled with quadratic trend, which was the best fitting model based on BIC values. Vocabulary, in purple, clearly demonstrates a shallower decline than the other three abilities for fiber density.ConclusionThis study demonstrated that longitudinal changes in the microstructural integrity of white matter tracts are better preserved for vocabulary, a crystallized ability, than that for the three fluid abilities, suggesting that preservation of white matter contributes to the maintenance of crystallized abilities with age.
Employing the Moca‐T (telephone) as a means of cognitive screening in a rural, ethnically diverse population during Covid‐19 restrictions
Authors: Wiese Lisa Ann Kirk , Williams Ishan Canty , Schoenberg Nancy E , Galvin James E , Lingler Jennifer H 
Published: February 2022

AbstractBackgroundRural, ethnically diverse older adults face a heightened risk of Alzheimer’s disease and related dementias (ADRD), but experience disparities in dementia education, detection, and treatment. The Covid‐19 pandemic struck during a rural, faith‐based outreach to address this gap. In‐person research activities were redesigned to employ a telephone approach.MethodThe revised research question targeting a rural community of 89% African American, Hispanic, and Haitian Creole residents was adapted to “Is the telephone an effective method for a) increasing AD knowledge, and b) detecting cognitive risk, in a rural underserved setting?” Faith‐based health educators, trained using online Alzheimer’s Association resources, contacted church congregants who responded to announcements during virtual worship services. Participants completed a measure of basic dementia knowledge (BKAD; Wiese et al., 2020), and MoCA‐T with a cut point of 11 indicating need for referral (Nasreddine, 2019) .ResultOf the estimated 120 persons across five churches who received an invitation, 75% (n = 90) participated in dementia education and memory screening via telephone. Dependent samples t‐test showed a significant increase in dementia knowledge: t(89) = ‐6.3, p < .001), and paired samples pre/post; t(24) = ‐2.23, p = < 004). Of the 60 who completed cognitive screening using the MoCA‐T, 15 (25%) were found to be at risk for memory impairment. Twelve (80%) of the 15 participants assessed as being at risk did follow‐up with their provider.ConclusionRural residents were willing to participate in telephone‐based health‐seeking activities during quarantine, and the Moca‐T was useful in identifying cognitive risk.
Predicting memory in preclinical AD from resting‐state functional connectivity
Authors: Fountain‐Zaragoza Stephanie , Heshung Liu , Jensen Jens H. , Helpern Joseph A. , Benitez Andreana 
Published: February 2022

AbstractBackgroundEmerging research suggests that patterns of brain functional connectivity can be used to predict clinical features and disease states. Individuals across the Alzheimer’s Continuum exhibit alterations in connectivity across various brain networks (Contreras et al., 2019). However, less is known about functional changes during the preclinical stage and whether those changes are associated with cognitive test performance. This study sought to identify functional connectivity characteristics that track with episodic memory, one of the earliest cognitive changes observed in the disease course (Mortamais et al., 2017), among cognitively unimpaired older adults with and without brain amyloid deposition.Method
n = 51) and ‐negative group (AB‐, n = 89). Resting‐state data were submitted to a pipeline for creating individual‐specific functional parcellations that account for variability in brain topology (Wang et al., 2015). Functional connectivity was used to predict demographically‐adjusted memory factor scores (Besser et al., 2018; Kiselica et al., 2020) in each group. Predictive models were generated using ridge regression and 50 iterations of 10‐fold cross‐validation. Prediction accuracies (i.e., Spearman rank correlations between predicted and observed scores) from the median performing models are reported.ResultMedian prediction accuracy was r
s = 0.40 (IQR = .063) in the AB+ group and r
s = 0.11 (IQR = .059) in the AB‐ group. Although the two groups did not differ on memory scores, the resulting networks were topologically distinct (Fig. 1). Qualitative visual review showed that the AB+ networks were predominantly comprised of inter‐network connections, whereas the networks in the AB‐ group appeared more circumscribed. In the AB+ group, the majority of connections predicting better memory were frontoparietal inter‐network connections, a pattern suggestive of compensatory hyper‐connectivity.ConclusionIndividual‐specific patterns of resting‐state functional connectivity can be used to predict episodic memory in the preclinical stages of the Alzheimer’s Continuum. These results suggest that the presence of beta‐amyloid is associated with less network segregation, potentially reflecting early disease‐related network disruption even prior to the emergence of clinical symptoms.