Variance In Cognitive Performance Research Articles

Multi-modal neuroimaging signatures predict cognitive decline in multiple sclerosis: A 5-year longitudinal study

BackgroundCognitive impairment is a hallmark of multiple sclerosis (MS) but is usually an under-recorded symptom of disease progression. Identifying the predictive signatures of cognitive decline in people with MS (pwMS) over time is important to ensure effective preventative treatment strategies. Structural and functional brain characteristics as measured by various magnetic resonance (MR) methods have been correlated with variation in cognitive function in MS, but typically these studies are limited to a single MR modality and/or are cross-sectional designs. Here we assess the predictive value of multiple different MR modalities in relation to cognitive decline in pwMS over 5 years. MethodsA cohort of 43 pwMS was assessed at baseline and 5 years follow-up. Baseline (input) data consisted of 70 multi-modal MRI measures for different brain regions including magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and standard volumetrics. Age, sex, disease duration and treatment were included as clinical inputs. Cognitive function was assessed using the Audio Recorded Cognitive Screen (ARCS) and the Symbol Digit Modalities Test (SDMT). Prediction modelling was performed using the machine learning package - GLMnet, where a penalised regression was applied to identify multi-modal signatures with the most predictive value (and the least error) for each outcome. ResultsThe multi-modal approach to neuroimaging was able to accurately predict cognitive decline in pwMS. The best performing model for change in total ARCS (tARCS) included 16 features from across the various MR modalities and explained 54 % of the variation in change over time (R2=0.54, 95 % CI=0.48–0.51). The features included nine MRS, four volumetric and two DTI parameters. The model also selected disease duration, but not treatment, as a predictive feature. By comparison, the best model for SDMT included several of the same above features and explained 39 % of the change over time (R2=0.39, 95 % CI=0.48–0.51). Conventional volumetric measures were about half as good at predicting change in tARCS score compared to the best multi-modal model (R2=0.26 95 % CI:0.22–0.29). The clinical interpretation of the best predictive model for change in tARCS showed that cognitive decline could be predicted with >90 % accuracy in this cohort (AUC=0.92, SE=0.86 - 0.94). ConclusionMulti-modal MRI signatures can predict cognitive decline in a cohort of pwMS over 5 years with high accuracy. Future studies will benefit from the inclusion of even more MR modalities e.g., functional MRI, quantitative susceptibility mapping, magnetisation transfer imaging, as well as other potential predictors e.g., genetic and environmental factors. With further validation, this signature could be used in future trials with high-risk patients to personalise the management of cognitive decline in pwMS, even in the absence of relapses.

The Association between Education and Cognitive Performance Varies at Different Levels of Cognitive Performance: A Quantile Regression Approach

Introduction: Educational differences in cognitive performance among older adults are well documented. Studies that explore this association typically estimate a single average effect of education on cognitive performance. We argue that the processes that contribute to the association between education and cognitive performance are unlikely to have equal effects at all levels of cognitive performance. In this study, we employ an analytical approach that enables us to go beyond averages to examine the association between education and five measures of global and domain-specific cognitive performance across the outcome distributions. Methods: This cross-sectional study included 1,780 older adults aged 58–68 years from the Longitudinal Aging Study Amsterdam. Conditional quantile regression was used to examine variation across the outcome distribution. Cognitive outcomes included Mini-Mental State Examination (MMSE) score, crystallized intelligence, information processing speed, episodic memory, and a composite score of global cognitive performance. Results: The results showed that the associations between education and different cognitive measures varied across the outcome distributions. Specifically, we found that education had a stronger association with crystallized intelligence, MMSE, and a composite cognitive performance measure in the lower tail of performance distributions. The associations between education and information processing speed and episodic memory were uniform across the outcome distributions. Conclusion: Larger associations between education and some domains of cognitive performance in the lower tail of the performance distributions imply that inequalities are primarily generated among individuals with lower performance rather than among average and high performers. Additionally, the varying associations across some of the outcome distributions indicate that estimating a single average effect through standard regression methods may overlook variations in cognitive performance between educational groups. Future studies should consider heterogeneity across the outcome distribution.

Risk Polymorphisms of FNDC5, BDNF, and NTRK2 and Poor Education Interact and Aggravate Age-Related Cognitive Decline.

Cognitive abilities tend to decline with aging, with variation between individuals, and many studies seek to identify genetic biomarkers that more accurately anticipate risks related to pathological aging. We investigated the influence of BDNF, NTRK2, and FNDC5 single nucleotide polymorphisms (SNPs) on the cognitive performance of young and older adults with contrasting educational backgrounds. We addressed three questions: (1) Is education associated with reduced age-related cognitive decline? (2) Does the presence of SNPs explain the variation in cognitive performance observed late in life? (3) Is education differentially associated with cognition based on the presence of BDNF, NTRK2, or FNDC5 polymorphisms? We measured the cognitive functions of young and older participants, with lower and higher education, using specific and sensitive tests of the Cambridge Automated Neuropsychological Test Assessment Battery. A three-way ANOVA revealed that SNPs were associated with differential performances in executive functions, episodic memory, sustained attention, mental and motor response speed, and visual recognition memory and that higher educational levels improved the affected cognitive functions. The results revealed that distinct SNPs affect cognition late in life differentially, suggesting their utility as potential biomarkers and emphasizing the importance of cognitive stimulation that advanced education early in life provides.

Within‐Day Variability in Mobile Cognitive Assessments: Associations with Mild Cognitive Impairment and Sociodemographic Factors

AbstractBackgroundGreater within‐person variability in cognitive performance on mobile devices is emerging as a sensitive marker of mild cognitive impairment (MCI). It is unclear if sociodemographic differences are associated with this variability, and if so, whether these differences moderate associations between MCI status and within‐person variability. We use a digital health approach with ecological momentary assessments (EMA) to examine sociodemographic differences in within‐day variability among individuals with MCI and those who were cognitively unimpaired (CU).MethodA sample of 308 community‐dwelling older adults from the Einstein Aging Study (mean age = 77.49 years, SD = 4.86, range = 70‐90; 67% female; 45% non‐Hispanic White, 41% non‐Hispanic Black) completed neuropsychological testing and self‐reported questionnaires. Ninety‐eight individuals met Jak/Bondi criteria for MCI. All participants performed mobile tests of processing speed and memory binding on a smartphone up to six times daily over a two‐week period. We employed heterogeneous variance multilevel models to assess sociodemographic and MCI status associations with within‐day variability across assessments. We further tested whether differences in age, gender, race, and education moderated associations between MCI status and within‐day variability.ResultFor processing speed, greater variability was apparent in individuals with MCI, non‐Hispanic Black participants, and individuals with less education (ps<.001). A MCI status*gender interaction occurred; the association between MCI status and variability remained significant for both genders but was smaller among women (p<.01). For memory binding, greater variability was apparent in individuals with MCI, older participants, non‐Hispanic Black participants, and individuals with less education (ps<.001). Numerous interactions occurred; in separate analyses, associations between MCI status and variability remained significant, but were smaller among women, non‐Hispanic Black participants, and individuals with less education (ps<.05).ConclusionIndividuals with MCI exhibited greater within‐day variability in mobile cognitive performance than those who were CU, but the strength of these associations varied by sociodemographic factors. These indices of variability in everyday life may serve as sensitive markers of early cognitive impairment. Future research should examine daily mechanisms and environmental perturbations (e.g., stress, sleep, air pollution) that may explain why associations between MCI status and cognitive variability appeared smaller among women, non‐Hispanic Black participants, and individuals with less education.

A Study on the effects of seasonal variations in cognitive function on driving behaviour.

AbstractBackgroundThe population in Japan is ageing, and approximately 30% of the elderly are said to have Alzheimer’s disease. On the other hand, however, there are areas with insufficient transport services due to the declining birth rate, and the elderly have to drive cars. In order to reduce accidents caused by drivers with dementia, it is necessary to know the relationship between cognitive function and driving, but cognitive function is said to fluctuate daily. The aim of this study is to obtain knowledge that contributes to the prediction of accidents by observing the seasonal variation in cognitive function and driving using the same subjects.MethodA cognitive function test, a driving skill test at a driving school and an observation 1‐month survey of driving behaviour on public open roads were conducted on 40 drivers aged 70 years or older who drive their cars daily. The survey was conducted twice on the same subjects, once between April and June and once between October and December. From the data obtained, seasonal differences were verified.ResultIt is said that elderly drivers often drive short distances in their neighbourhood, but in reality they also make long trips. Comparing spring/summer and autumn/winter, autumn/winter drivers are more likely to be in a state of cognitive decline and drive more unevenly.ConclusionCognitive function and driving behaviour of older drivers differ depending on the season. As the passage of time and more short‐term fluctuations may have an impact, it is important to systematise the fluctuating changes in various cycles and link them to safe driving support.

Cohort heterogeneity and AD biomarkers in older adults without significant cognitive impairment: A comparison of U.S. POINTER and ADNI

AbstractBackgroundA key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.MethodTo examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aß and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aß‐negative individuals <70yrs and with global CDR = 0).ResultU.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aß+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.ConclusionHeterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.

Cohort heterogeneity and AD biomarkers in older adults without significant cognitive impairment: A comparison of U.S. POINTER and ADNI

AbstractBackgroundA key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.MethodTo examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aβ and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aβ‐negative individuals <70yrs and with global CDR = 0).ResultU.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aβ+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.ConclusionHeterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.

Naturalistic Assessment of Reaction Time Variability in Older Adults at Risk for Alzheimer’s Disease

AbstractBackgroundBreakdowns in attentional control may underscore cognitive changes seen in the earliest stages of Alzheimer’s disease (AD). One way to measure these changes is to assess variability in cognitive performance. Variability in cognition may be most evident when repeatedly sampled over hours or days and in different environmental contexts or at different times of day. We analyzed data from an ongoing smartphone‐based study of cognition in AD which utilizes extremely brief cognitive tests taken remotely over several days in natural environments.MethodOlder adults (N = 319, aged 75 +/‐ 5 years) completed repeated cognitive testing on the Ambulatory Research in Cognition (ARC) platform and had CSF or PET amyloid biomarkers and APOE genotype available. RTSD was assessed in a brief processing speed task by taking the SD of correct RTs. All models adjusted for baseline age, education, and gender.ResultAveraging across sessions, symptomatic participants (indicated by Clinical Dementia Rating® (CDR®) > 0) showed more variability than asymptomatic (CDR 0) participants (p = 0.009). APOE ε4 carriers showed more variability than non‐carriers, although this was not significant (p = 0.067). More fine‐grained models considered RTSD within each session (e.g. from trial‐to‐trial) using mixed effects models. Symptomatic participants exhibited greater trial‐to‐trial RTSD compared to asymptomatic participants (p = 0.001). APOE ε4 carriers also exhibited greater trial‐to‐trial RTSD compared to non‐carriers (p = 0.004). When limiting the sample to asymptomatic participants to determine if there were changes in the preclinical stage of AD, there remained a strong APOE ε4 effect, with carriers exhibiting greater trial‐to‐trial RTSD than non‐carriers (p = 0.005). Interestingly, amyloid was not significant in any models.ConclusionOlder adults at risk for AD show increased RTSD even in brief assessments. These subtle fluctuations in attention were most evident in APOE e4 carriers at very short time intervals, and less so when averaged across trials and sessions. Overall, these findings suggest that fluctuations in attention in preclinical AD are most evident from moment to moment, highlighting the need for fine‐grained and repeated assessment of attentional control.

Cognitive and Exercise Training Improves Intraindividual Variability in Cognitive Performance in Older Adults: Secondary Findings of A Randomized Controlled Trial

AbstractBackgroundIncreased intraindividual variability of cognitive performance is a marker of cognitive decline. Whether computerized cognitive training (CCT) and aerobic exercise counteracts cognitive decline by reducing intraindividual variability is unknown. We investigated the effects of CCT with or without aerobic exercise on reaction time intraindividual variability in older adults.MethodThis was a secondary analysis of an 8‐week randomized controlled trial. Older adults (aged 65‐85 years) were randomized to CCT alone (n = 41), CCT with aerobic exercise (n = 41), or an active control group (n = 42). The CCT group trained using the Fit Brains® platform 3×/week for 1 hour (plus 3×/week of home‐based training). The CCT with aerobic exercise group received 15 min of walking plus 45 min of Fit Brains® 3×/week (plus 3×/week of home‐based training). The control group received sham exercise and cognitive training (3×/week for 1 hour). We extracted reaction times from the Dimensional Change Card Sort Test, Flanker Inhibitory Control and Attention Test (Flanker), and Pattern Comparison Processing Speed Test (PACPS). Intraindividual variability was measured as residual intraindividual standard deviation (residual ISD) of raw reaction time latencies. Residual ISD is an unbiased measure of variability that accounts for within and between participant source of variation that could influence reaction time latencies. We also calculated reaction time intraindividual SD (raw‐score ISD) and intraindividual coefficient of variation (ICV).ResultCompared with the control group, residual ISD improved in a processing speed task (PACPS) following CCT alone (mean difference [95% confidence interval]: ‐0.147 [‐0.230 to ‐0.065], p<0.001) and CCT with aerobic exercise (‐0.111 [‐0.195 to ‐0.027], p<0.01). Also, for processing speed, both CCT (‐0.173 [‐0.261 to ‐0.084], p<0.001) and CCT with aerobic exercise (‐0.122 [‐0.213 to ‐0.032], p<0.01) showed greater reduction in raw‐score ISD compared with controls, while only CCT reduced ICV for this task (‐0.108 [‐0.176 to ‐0.040], p<0.001). Inhibitory attention (Flanker) improved only after CCT with aerobic exercise (congruent = ‐0.128 [‐0.250 to ‐0.006], incongruent = ‐0.121 [‐0.237 to ‐0.005], both p<0.05).ConclusionA CCT program promoted cognitive health via reductions in intraindividual variability of cognitive performance and combining it with aerobic exercise resulted in broader benefits.

PSMD, a novel biomarker of small vessel disease, and its association with cognitive function — A comprehensive clinical validation study

AbstractBackgroundA recent instrumental validation analysis positioned peak‐width of skeletonized mean diffusivity (PSMD) as a biomarker for vascular contributions to cognitive impairment and dementia (VCID) with excellent reliability, repeatability, and reproducibility. As the next step of biomarker development, the current study aimed to (1) perform a clinical validation of PSMD and cognitive function in MarkVCID and three independent replication samples, and (2) assess whether PSMD explains cognitive function above and beyond white matter hyperintensities (WMH).MethodThe clinical validation of PSMD included n = 395 participants from the multi‐site MarkVCID consortium, n = 6172 from population‐based CHARGE cohorts, n = 287 from RUSH, and n = 435 from the UC Davis ADRC cohort spanning diverse ages and racial/ethnic backgrounds. PSMD was derived from DTI using an automated algorithm and further log‐transformed to normalize its distribution. A composite measure of general cognitive function was calculated from neuropsychological tests assessing at least three different cognitive domains. Linear regression models were run to determine the association between PSMD and cognitive function, adjusting for age, sex, and education. A secondary model was adjusted for vascular risk factors: hypertension, diabetes, and smoking. Lastly, both models included WMH volume to evaluate PSMD beyond WMH.ResultHigher PSMD values were associated with lower general cognitive function in the MarkVCID (Beta (95% CI), ‐0.82 (‐1.03, ‐0.61), p<0.001) in primary models, and remained unchanged after additional adjustment for vascular risk factors in secondary model (‐0.87 (‐1.09, ‐0.65), p<0.001). These findings were replicated across the CHARGE, RUSH, and UC Davis ADRC cohorts (Table 1). We further observed that PSMD explained an additional 0.2% of the variance in cognitive function beyond WMH in the youngest cohort (48.1 ±8.9 years), whereas the variance explained rose to 2.51% for the oldest cohort (76.4 ±5.2 years).ConclusionThis comprehensive clinical validation study suggests that PSMD is related to general cognition across diverse samples, potentially explaining more variation in cognitive function than a classic cerebrovascular marker such as WMH. Together, our instrumental and clinical validation studies support using PSMD as a robust biomarker with potential for risk stratification and disease monitoring in multi‐site clinical trials of VCID. Additional longitudinal validation studies are underway.

A neuropsychological investigation of social‐semantic knowledge in frontotemporal dementia

AbstractBackgroundThe loss of semantic memory is a key feature of frontotemporal dementia (FTD), and is associated with atrophy of the anterior temporal lobes (ATLs). The role of the left and right ATLs in supporting social‐semantic knowledge is unclear. To address this, we developed a social‐semantic battery comprising exemplars of social concepts such as person‐specific knowledge, abstract social concepts, and understanding of social norms. Performance on this battery was directly compared with non‐social semantic knowledge, measured using the Cambridge Semantic Test Battery.Method48 people with FTD (behavioural‐variant FTD = 26, semantic dementia = 22), and 19 age‐matched healthy controls were recruited. Participants completed both semantic batteries, alongside tests of general cognition and executive function. Participants also underwent a 3T T1‐weighted structural MRI scan. All neuropsychological tasks were entered into a principal component analysis (with varimax rotation) to explore graded variations in cognitive performance in FTD. Voxel‐based morphometry was conducted to explore grey matter correlates of social and non‐social semantic knowledge. The relative contributions of the left and right ATL to social‐semantic knowledge were tested by including ATL volume and asymmetry indices as predictors in a multiple regression analysis.ResultPeople with SD and bvFTD were impaired in both social‐and non‐social knowledge tasks. The principal component analysis indicated separate components for semantic memory and executive function. Both social and non‐social semantic tasks loaded onto the semantic memory component (Figure 1). People with SD scored significantly worse than bvFTD on the semantic memory component (t = 5.18, p<0.0001), while people with bvFTD scored worse than SD on the executive function component (t = 3.97, p<0.001) (Figure 2). Semantic memory factor scores were correlated with grey matter in the bilateral ATLs (Figure 3). There were no significant clusters associated with scores on the executive function component. Multiple regression revealed that performance on the semantic memory component was predicted by the magnitude but not the asymmetry of ATL atrophy.ConclusionBoth social and non‐social forms of semantic knowledge are impaired by FTD, and this degradation is associated with bilateral ATL atrophy. These results suggest a shared representation for all types of semantic memory across the ATLs.

Tele neuropsychological exploratory assessment of indicators of mild cognitive impairment and autonomy level in Mexican population over 60 years old.

Due to the cognitive decline associated with aging, it is necessary to determine the variables involved in this process to implement preventive actions to avoid or help slow the progression of cognitive decline to dementia in older adults. This is a priority in the current pandemic situation, due to the consequences of periods of confinement due to COVID-19. To address these challenges, this study was conducted through Information and Communication Technologies (ICTs), by adapting an in-person assessment protocol into an online Tele neuropsychological consultation. The correlation between autonomy and cognitive performance variables is analyzed in 47 Mexican subjects over 60 years of age. The results of the statistical analyses suggest a moderate correlation between the level of autonomy and cognitive performance (with MOCA and Clock Drawing Test), significant correlation values are outlined in some of the variables reviewed, and interesting data were found in the correlation of cognitive reserve with cognitive decline and the educational level from the participants. Finally, future analysis is proposed of the sensitivity of screening tests (CDT) to find indicators of Mild Cognitive Impairment (MCI) in this population that is not detected in classical tests (MOCA). Developing ICT-based screening protocols for the elderly may be a key tool in these coronavirus times or under any given circumstances.

Exercise training mitigates the deleterious effects of experimental bed rest on intraindividual variability of executive functioning in older adults: A randomised controlled trial

AbstractBackgroundIn older adults, bed rest can occur because of chronic conditions, injury, surgery, or hospitalization. Extreme levels of physical inactivity due to bed rest initiate a downward spiral in several body systems. Exercise is a countermeasure to many of these changes; nonetheless, little is known about the effect of exercise on older adults’ cognition during bed rest. We thus examined the effects of exercise on the intraindividual variability (IIV) of cognitive performance in older adults exposed to 14 days of experimental 6° head‐down bed rest (HDBR) and whether sex moderates its effects. We chose IIV as our outcome measure because it is more sensitive than traditional summary scores of cognitive performance, albeit no studies have explored exercise effects on older adults’ IIV submitted to bed rest.MethodA non‐blinded, parallel‐group, randomised controlled trial. Twenty‐three healthy older adults aged 55‐65 were randomised to: 1) 14 days of HDBR (CON); or 2) 14 days of HDBR with daily aerobic and strength exercise (EX). Data were collected at baseline, HDBR completion, and end of seven‐day‐recovery. The National Institutes of Health Toolbox Cognitive Battery assessed executive function (Flanker Incongruent and Congruent and Dimensional Change Card Sort) and processing speed (Pattern Comparison). IIV was indexed by intraindividual coefficient of variation (ICV) and residual intraindividual standard deviation (R‐ISD), with R‐ISD as our primary measure of interest. Linear mixed models assessed group differences and the moderator role of sex.ResultAt HDBR completion, EX had significantly lower (better) Flanker incongruent ICV (Estimated mean difference = ‐0.10, 95%CI ‐0.19;‐0.003, p = 0.022) and R‐ISD (Estimated mean difference = ‐3.63, 95%CI ‐6.10;‐1.17, p = 0.005) vs. CON. Sex moderated the effect of exercise; females in EX had significantly lower Flanker incongruent ICV vs. CON (Estimated mean difference = ‐0.23; 95%CI ‐0.34;‐0.12, p<0.001). At the end of the seven‐day recovery, EX had significantly lower Flanker incongruent R‐ISD vs. CON (Estimated mean difference = ‐3.11, 95%CI ‐5.70;‐0.052, p = 0.019). Summary scores and processing speed IIV changes were not statistically significant (ps>0.05).ConclusionExercise during HDBR preserved executive functioning, especially in females. Our findings support the delivery of exercises to older adults during bed rest to preserve their cognitive function.

Mapping cognitive trajectories in older adults with essential tremor

AbstractBackgroundOlder adults with essential tremor (ET) are at increased risk for Alzheimer’s disease (AD) and related disorders. Examining cognitive trajectories within this population will enable better identification of individuals who evidence accelerated rates of change. Here we examine how variability in baseline cognitive performance affects trajectories of cognitive change within three subgroups of cognitively normal older adults: 1) those whose baseline neuropsychological scores were entirely within normal limits (WNL); 2) those with at least one low score considered to have unlikely clinical significance (UCS); and 3) those with at least one low score considered to have possible clinical significance (PCS).MethodOlder adults with ET completed comprehensive neuropsychological testing and clinical interviews, and 159 received a consensus diagnosis of cognitively normal. Participants were then subdivided into one of three categories defined above: WNL (N = 66, 75.38 ± 8.96 years of age), UCS (N = 54, 76.35 ± 10.25 years), and PCS (N = 37, 80.22 ± 9.00 years). Generalized estimating equations (GEE) were used to compare rates of change in global cognition, memory, executive function, attention, visuospatial, and language z‐scores over time across these groups. Participants were seen for two to four visits (24.98 ± 20.29 months). Models were adjusted for age, gender, and years of education.ResultAll three groups, WNL (β = ‐.005, p = .028), UCS (β = ‐.006, p = .011), and PCS (β = ‐.012, p = .002), evidenced decline in their memory performance over time, with the latter groups declining faster than the WNL group. Relative to the WNL and UCS groups, the PCS group also declined faster over time in overall cognition (β = ‐.010, p = .029) and in language (β = ‐.024, p = .035).ConclusionHeterogeneity in cognitive performance among cognitively normal older adults with ET predicts trajectories of cognitive decline longitudinally. Specifically, rates of decline were slowest in those with entirely normal test scores, and greatest in those whose scores were considered to have possible clinical significance. These preliminary results provide a starting point for further inquiry into the role of nuanced cognitive profiles in predicting rates of decline, impairment, and dementia in ET cases who may initially be labeled as “cognitively normal.”

Cognitive impairment after sleep deprivation: The role of precuneus related connectivity on the intra-individual variability changes

ObjectiveIntra-individual variability (IIV) in cognitive performance is thought to reflect the efficiency with which attentional resources are allocated in different circumstances requiring cognitive control. IIV in cognitive performance is associated with the strength of the negative correlation between task-positive network and default mode network (DMN) activity. In this study, we investigated the impact of sleep deprivation (SD) on functional connectivity (FC) between the DMN and psychomotor vigilance task-related network (PVT-RN), and its relationship with IIV in cognitive performance. MethodsTwo analyses, network-level independent component analysis (NL-ICA) and region-level (RL)-ICA, were employed to compare the coefficient of variation (CV) of the PVT between normal sleep and SD conditions across 67 healthy participants. ResultsAfter SD, in NL-ICA, the FC between the PVT-RN and DMN was positively correlated with the CV of the PVT, as well as the changes therein, compared with normal sleep. Using a mask derived from the DMN and PVT-RN, the RL-ICA revealed that 12 edges/connections between DMN and PVT independent components were associated with the CV of the PVT, with nine of these connections involving the precuneus. ConclusionsThese findings suggest that the precuneus may play a crucial role in the interactions of various brain functions during the PVT, with the connections between the precuneus and frontoparietal and somatosensory networks being significantly altered after SD. Moreover, following SD, weakened negative FC between the precuneus and bilateral inferior parietal lobule may disrupt the balance between cognitive and executive control functions, leading to a decline in cognitive performance.

Assessing depression recurrence, cognitive burden, and neurobiological homeostasis in late life: Design and rationale of the REMBRANDT study

BackgroundLate-life depression is characterized by disability, cognitive impairment and decline, and a high risk of recurrence following remission. Aside from past psychiatric history, prognostic neurobiological and clinical factors influencing recurrence risk are unclear. Moreover, it is unclear if cognitive impairment predisposes to recurrence, or whether recurrent episodes may accelerate brain aging and cognitive decline. The purpose of the REMBRANDT study (Recurrence markers, cognitive burden, and neurobiological homeostasis in late-life depression) is to better elucidate these relationships and identify phenotypic, cognitive, environmental, and neurobiological factors contributing to and predictive of depression recurrence. MethodsAcross three sites, REMBRANDT will enroll 300 depressed elders who will receive antidepressant treatment. The goal is to enroll 210 remitted depressed participants and 75 participants with no mental health history into a two-year longitudinal phase focusing on depression recurrence. Participants are evaluated every 2 months with deeper assessments occurring every 8 months, including structural and functional neuroimaging, environmental stress assessments, deep symptom phenotyping, and two weeks of ‘burst’ ecological momentary assessments to elucidate variability in symptoms and cognitive performance. A broad neuropsychological test battery is completed at the beginning and end of the longitudinal study. SignificanceREMBRANDT will improve our understanding of how alterations in neural circuits and cognition that persist during remission contribute to depression recurrence vulnerability. It will also elucidate how these processes may contribute to cognitive impairment and decline. This project will obtain deep phenotypic data that will help identify vulnerability and resilience factors that can help stratify individual clinical risk.

Cognitive Function among Young Women's Football Players in the Summer Heat.

Recently, there has been a growing focus on studies related to women's football. However, the cognitive function of female football players has not been extensively characterized. Thus, we explored how the cognitive function of female football players was altered during a series of matches in summer and examined day-to-day variations in cognitive function with regard to dehydration status. Resting cognitive function was assessed from 17 young women football players during the Japan Club Youth Women's football tournament, which spanned eight consecutive days. Cognitive function initially improved, with this improvement sustained throughout the tournament. It is worth noting that ten participants experienced symptoms of dehydration at least once during the tournament; however, these symptoms were not found to be linked to impaired cognitive function, suggesting that resting cognitive function remains unaffected during summer matches, even in the presence of dehydration symptoms.

Low serum 25‑hydroxy-vitamin D levels are associated with cognitive impairment in multiple sclerosis.

Cognitive impairment frequently affects people with multiple sclerosis (MS). Low vitamin D has been associated with cognitive dysfunction in different neurodegenerative diseases, and, in MS, with motor disability and disease activity. We aim to investigate associations between vitamin D and cognitive status in MS. In this cross-sectional study, we included 181 MS patients, recruited consecutively at the MS Unit of the Policlinico Federico II University Hospital of Naples, Italy, between January and April 2022, with serum 25‑hydroxy (25-OH) vitamin D measurements using Chemiluminescence-ImmunoAssay, and cognitive assessment using the Brief International Cognitive Assessment for MS (BICAMS), which includes Symbol Digit Modalities Test (SDMT), California Verbal Learning Test-II (CVLT-II) and Brief Visuospatial Memory Test-Revised (BVMT-R). We collected demographics (age, sex, education), and clinical variables (disease duration, disease subtype, expanded disability status scale (EDSS), disease modifying treatment, relapses in previous 12 months, vitamin D supplementation, comorbidities). For a subset of patients (n=41, 23.2% of the total sample), we collected Beck Depression Inventory-II, Beck Anxiety Inventory, and Modified Fatigue Impact Scale. At univariable linear regression models, serum 25-OH-vitamin D levels were 0.9ng/mL higher for each unit increase of SDMT adjusted scores (Coeff=0.93; 95%CI=0.81, 1.04; p<0.01), 0.7ng/mL higher for each unit increase of CVLT-II adjusted scores (Coeff=0.68; 95%CI=0.53, 0.83; p<0. 01), 0.6ng/mL higher for each unit increase of BVMT-R adjusted scores (Coeff=0.58; 95%CI=0.43, 0.73; p<0.01), -9.63ng/mL lower for each impaired BICAMS test (Coeff=-9.63; 95%CI=-11.48, -7.79; p<0.01), and -2.2ng/mL lower for each unit increase of EDSS (Coeff=-2.16; 95%CI=-3.57, -0.75; p<0.01). At multivariable linear regression models, we confirmed associations between 25-OH-vitamin D and EDSS (Coeff=-2.09; 95%CI=-4.45, -0.43; p<0.01), SDMT (Coeff=0.75; 95%CI=0.60, 0.90; p<0.01), and CVLT-II (Coeff=0.14; 95%CI=0.01, 0.28; p=0. 04). Results remained unchanged when including depression, anxiety and fatigue scores. Lower serum 25-OH-vitamin D was associated with worse cognitive function in MS. Future studies should consider longitudinal variations in cognitive function in relation to vitamin D supplementation.

34 Variability in RBANS Performance and Neurocognitive Impairment in Older Adults with Cognitive Concerns

Objective:Risk factors that contribute to brain pathology and cognitive decline among older adults include demographic factors (e.g., age, educational attainment), genetic factors, health factors, and depression (Plassman et al., 2010). Variability within an individual’s performance across cognitive tasks is referred to as dispersion (Hultsch et al., 2002), which appears sensitive to subtle cognitive impairments associated with neurodegenerative pathology in older adults (Bangen et al., 2019; Kälin et al., 2014). Thaler and colleagues (2015) found that dispersion across domains of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was a useful indicator of cognitive changes associated with cardiovascular disease and mortality. Also, research by Manning and colleagues (2021) found that elevated ratings of depression and anxiety in older adults was associated with greater dispersion across neuropsychological testing. The present study aimed to replicate findings that greater dispersion in neuropsychological performance is associated with impaired neurocognitive performance and greater self-reported depression among older adults who present for neuropsychological evaluation with cognitive concerns.Participants and Methods:Neuropsychological testing data was obtained from a university hospital. Chart reviews were conducted on 369 participants who met initial criteria (60 years or older with testing data from the RBANS Form A, Wechsler Test of Adult Reading, and Geriatric Depression Scale [GDS]). Retrospective analyses were conducted on a final sample of 293 participants from 60 to 94 years old (Mage = 74.41, SDage = 7.43; 179 females, 114 males). Diagnoses were used for group comparisons between cognitively intact individuals with subjective cognitive complaints (SCC, n = 49), persons with Mild Neurocognitive Disorder (mND, n =137), and persons with Major Neurocognitive Disorder (MND, n = 107).Results:As expected, results indicated that higher dispersion was related to lower Total RBANS Scores (r = -0.54, p &lt; .001) and significant differences across diagnostic groupings (F(2, 289) = 29.19, p &lt; 0.001; SCC, mND, MND) indicated that variability in performance was an indicator of greater neurocognitive impairment. Contrary to expectations, greater dispersion was very weakly associated with lower reported depressive symptomatology (r = -0.13, p = 0.03). A three-stage hierarchical linear regression was conducted with the RBANS Coefficient of Variation (CoV) as the dependent variable and three predictor variables (Age, Total RBANS, Total GDS). The regression analysis results indicated that age was not a significant predictor, but both Total RBANS and GDS Scores were. The most important predictor was Total RBANS Scores which uniquely explained 21% of the variation in dispersion.Conclusions:This study adds to the current literature regarding the clinical utility of dispersion in neuropsychological performance as an indicator of early and subtle neurocognitive impairment. Depressive symptom reporting was expected to help predict the degree of variability, but this factor was only weakly associated with the RBANS CoV.Limitations of this study include its retrospective use of archival data and the restricted range on some variables of interest. Further research is needed to examine the relative utility of different measures of dispersion and why increased cognitive performance variability is related to neurocognitive impairment and decline.

Neuroanatomical Correlates of Cognitive Tests in Young-onset MCI.

Mild Cognitive Impairment (MCI) is a heterogeneous condition characterised by cognitive changes that do not affect everyday functioning and may represent a predementia phase. Research on the neuroanatomical correlates of cognitive tests used to diagnose MCI is heterogeneous and has mainly focused on elderly populations of patients with MCI, usually well above the age of 65. However, the effect of ageing on brain structure is known to be substantial and to affect brain-behaviour associations in older people. We explored the brain correlates of different cognitive tests in a group of young-onset MCI (i.e., with symptoms onset before the age of 65) to minimise the effect of ageing on brain-behaviour associations. Patients with a clinical diagnosis of young-onset MCI underwent extensive cognitive assessment and multimodal Magnetic Resonance Imaging (MRI) including high-resolution T1-weighted and Diffusion Tensor Imaging (DTI) sequences. Their scores on cognitive tests were related to measures of grey matter (GM) density and white matter (WM) integrity using, respectively, Voxel Based Morphometry (VBM) and Tract-Based Spatial Statistics (TBSS). 104 young-onset MCI were recruited. VBM and TBSS whole-brain correlational analyses showed that between-subject variability in cognitive performance was significantly associated with regional variability in GM density and WM integrity. While associations between cognitive scores and focal GM density in our young-onset MCI group reflected the well-known lateralization of verbal and visuo-spatial abilities on the left and right hemispheres respectively, the associations between cognitive scores and WM microstructural integrity were widespread and diffusely involved most of the WM tracts in both hemispheres. We investigated the structural neuroanatomical correlates of cognitive tests in young-onset MCI in order to minimise the effect of ageing on brain-behaviour associations.