Cognitive Test Data Research Articles

Validation of the Updated "LIfestyle for BRAin health" (LIBRA) Index in the English Longitudinal Study of Ageing and Maastricht Aging Study.

The "LIfestyle for BRAin health" (LIBRA) index was recently updated with three new modifiable factors: hearing impairment, social contact, and sleep (LIBRA2), but has not yet been validated. Comparison of the performance of both LIBRA versions in predicting dementia risk. Longitudinal data from the English Longitudinal Study of Ageing (ELSA) and the Maastricht Aging Study (MAAS) were used. The weighted LIBRA (11/12 factors available) and LIBRA2 (14/15 factors available) scores were calculated, with higher scores representing an unhealthier lifestyle. Dementia diagnoses were based on self- or informant reported physician diagnosis, an informant-based cognitive screening tool, registry data or test data. Cox-proportional hazards regression was used to investigate the association between LIBRA(2) scores and dementia risk. Model fit and predictive accuracy were determined using the Akaike information criterion and Harrell's C index. Over an average follow-up of 8.3 years in ELSA and 17.9 years in MAAS, 346 (4.6%) and 120 (8.5%) individuals developed dementia, respectively. In ELSA, a one-point increase in LIBRA2 was associated with an 8% (1.06-1.11) higher dementia risk (LIBRA: 13%, 1.09-1.16). In MAAS, a one-point increase in LIBRA2 was associated with a 6% (1.01-1.12) higher dementia risk (LIBRA: 8%, 0.99-1.16). In ELSA, LIBRA (Harrell's C = 0.68) and LIBRA2 (Harrell's C = 0.67) performed similarly. In MAAS, LIBRA2 (Harrell's C = 0.62) performed better compared to LIBRA (Harrell's C = 0.52). LIBRA2 is a better model for identifying individuals at increased dementia risk and for public health initiatives aimed at dementia risk reduction.

The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT-The Graphical Brain Association Tool.

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain.

Cognitive performance in functional seizures compared with epilepsy and healthy controls: a systematic review and meta analysis

Cognition is a core component of functional seizures, but the literature on cognition in this disorder has been heterogeneous, with no clear unifying profile emerging from individual studies. The aim of this study was to do a systematic review and meta-analysis of cognitive performance in adults with functional seizures compared with epilepsy (including left temporal lobe epilepsy) and compared with healthy non-seizure cohorts. In this systematic review and meta-analysis, starting Feb 6, 2023, replicated and updated on Oct 31, 2023, a medical librarian searched MEDLINE, Embase, PsycINFO, and Web of Science. Inclusion criteria were full reports documenting raw or standardised cognitive test data in adults with functional seizures compared with adults with epilepsy, prospectively recruited healthy comparisons, or published norms. Grey literature was retained and there were no language or date restrictions. We excluded studies only reporting on mixed functional seizures and epilepsy, or mixed functional neurological samples, with no pure functional seizures group. Risk of bias was evaluated using a modified version of the Newcastle-Ottawa Scale. People with lived experiences were not involved in the design or execution of this study. This study is registered as CRD42023392385 in PROSPERO. Of 3834 records initially identified, 84 articles were retained, including 8654 participants (functional seizures 4193, epilepsy 3638, and healthy comparisons 823). Mean age was 36 years (SD 12) for functional seizures, 36 years (12) for epilepsy, and 34 years (10) for healthy comparisons, and the proportion of women per group was 72% (range 18-100) for functional seizures, 59% (range 15-100) for epilepsy, and 69% (range 34-100) for healthy comparisons. Data on race or ethnicity were rarely reported in the individual studies. Risk of bias was moderate. Cognitive performance was better in people with functional seizures than those with epilepsy (Hedges' g=0·17 [95% CI 0·10-0·25)], p<0·0001), with moderate-to-high heterogeneity (Q[56]=128·91, p=0·0001, I2=57%). The functional seizures group performed better than the epilepsy group on global cognition and intelligence quotient (g=0·15 [0·02-0·28], p=0·022) and language (g=0·28 [0·14-0·43], p=0·0001), but not other cognitive domains. A larger effect was noted in language tests when comparing functional seizures with left temporal lobe epilepsy (k=5; g=0·51 [0·10 to 0·91], p=0·015). The functional seizures group underperformed relative to healthy comparisons (g=-0·61 [-0·78 to -0·44], p<0·0001), with significant differences in all cognitive domains. Meta regressions examining effects of multiple covariates on global cognition were not significant. Patients with functional seizures have widespread cognitive impairments that are likely to be clinically meaningful on the basis of moderate effect sizes in multiple domains. These deficits might be slightly less severe than those seen in many patients with epilepsy but nevertheless argue for consideration of clinical assessment and treatment. Department of Veterans Affairs, Veterans Health Administration.

A comparison of PM2.5 exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes

BackgroundReported associations between particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. ObjectivesTo assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes. MethodsWe used Visit 5 (2011–2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000–2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. ResultsExposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. DiscussionPM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Examining a Preclinical Alzheimer's Cognitive Composite for Telehealth Administration for Reliability Between In-Person and Remote Cognitive Testing with Neuroimaging Biomarkers.

The preclinical Alzheimer's cognitive composite (PACC) was developed for in-person administration to capture subtle cognitive decline. At the outset of the COVID-19 pandemic, cognitive testing was increasingly performed remotely by telephone or video administration. It is desirable to have a harmonized composite measurement derived from both in-person and remote assessments for identifying cognitive changes and to examine its relationship with common neuroimaging biomarkers. We defined a telehealth compatible PACC (tPACC) and examined its relationship with neuroimaging biomarkers related to neurodegeneration, brain function and perfusion, white matter integrity, and amyloid-β. We examined 648 participants' neuroimaging and in-person and remote cognitive testing data from the Wake Forest Alzheimer's Disease Research Center's Clinical Core cohort (observational study) to calculate a modified PACC (PACC5-RAVLT) score and tPACC scores (in-person and remote). We performed Spearman/intraclass correlation coefficient (ICC) analyses for reliability of tPACC scores and linear regression models to evaluate associations between tPACC and neuroimaging. Bland-Altman plots for agreement were constructed across cognitively normal and impaired (mild cognitive impairment and dementia) participants. There was a significant positive relationship between tPACCin-person and PACC5-RAVLT (Overall group: r2 = 0.94, N = 648), and tPACCin-person and tPACCremote (validation subgroup: ICC = 0.82, n = 53). Overall, tPACC showed significant associations with brain thickness/volume, gray matter perfusion, white matter free water, and amyloid-β deposition. There is a good agreement between tPACCand PACC5-RAVLTfor cognitively normal and impaired individuals. The tPACC is associated with common neuroimaging markers of Alzheimer's disease.

The association between sleep duration, bedtime, and cognitive ability in Chinese adults: Evidence from the China family panel studies

IntroductionDementia is marked by a steady decline or worsening in cognitive abilities, affecting memory, logic, and social competencies. While many studies suggest a potential link between the amount of sleep and dementia risk, the outcomes are not yet consistent. This research delved into the relationship between sleep length and bedtime on cognitive abilities using an extensive dataset from the China Family Panel Studies (CFPS) from 2014 to 2020. MethodsData from 175,702 observations were collected, including cognitive function test data from 22,848 participants. Various cognitive tests were used to assess cognitive function. Restricted cubic spline (RCS) models were used for data analysis. ResultsThe optimal sleep duration for cognitive function was found to be 6–7 h, and the optimal bedtime was generally between 22:00–23:00. Longitudinal analysis revealed that sleep duration four years prior had a significant impact on current cognitive function. After accounting for various factors, those who slept for 7–8 h and over 8 h displayed lower cognitive function scores. Conversely, individuals sleeping less than 6 h had higher scores on the Vocabulary Test. Bedtime before 22:00 was associated with lower scores on the Vocabulary Test and Mathematical Test. Subgroup analyses based on age, gender, and urban residence showed variations in optimal sleep duration for different populations. Propensity Score Matching (PSM) analysis supported the findings. ConclusionsMaintaining a sleep duration of 6–7 h and a regular bedtime between 22:00–23:00 is important for optimizing cognitive performance.

Smooth Information Criterion for Regularized Estimation of Item Response Models

Item response theory (IRT) models are frequently used to analyze multivariate categorical data from questionnaires or cognitive test data. In order to reduce the model complexity in item response models, regularized estimation is now widely applied, adding a nondifferentiable penalty function like the LASSO or the SCAD penalty to the log-likelihood function in the optimization function. In most applications, regularized estimation repeatedly estimates the IRT model on a grid of regularization parameters λ. The final model is selected for the parameter that minimizes the Akaike or Bayesian information criterion (AIC or BIC). In recent work, it has been proposed to directly minimize a smooth approximation of the AIC or the BIC for regularized estimation. This approach circumvents the repeated estimation of the IRT model. To this end, the computation time is substantially reduced. The adequacy of the new approach is demonstrated by three simulation studies focusing on regularized estimation for IRT models with differential item functioning, multidimensional IRT models with cross-loadings, and the mixed Rasch/two-parameter logistic IRT model. It was found from the simulation studies that the computationally less demanding direct optimization based on the smooth variants of AIC and BIC had comparable or improved performance compared to the ordinarily employed repeated regularized estimation based on AIC or BIC.

A Genome-Wide Interaction Study of Erythrocyte ω-3 Polyunsaturated Fatty Acid Species and Memory in the Framingham Heart Study Offspring Cohort

BackgroundCognitive decline, and more specifically Alzheimer’s disease, continues to increase in prevalence globally, with few, if any, adequate preventative approaches. Several tests of cognition are utilized in the diagnosis of cognitive decline that assess executive function, short- and long-term memory, cognitive flexibility, and speech and motor control. Recent studies have separately investigated the genetic component of both cognitive health, using these measures, and circulating fatty acids. ObjectivesWe aimed to examine the potential moderating effect of main species of ω-3 polyunsaturated fatty acids (PUFAs) on an individual’s genetically conferred risk of cognitive decline. MethodsThe Offspring cohort from the Framingham Heart Study was cross-sectionally analyzed in this genome-wide interaction study (GWIS). Our sample included all individuals with red blood cell ω-3 PUFA, genetic, cognitive testing (via Trail Making Tests [TMTs]), and covariate data (N = 1620). We used linear mixed effects models to predict each of the 3 cognitive measures (TMT A, TMT B, and TMT D) by each ω-3 PUFA, single nucleotide polymorphism (SNP) (0, 1, or 2 minor alleles), ω-3 PUFA by SNP interaction term, and adjusting for sex, age, education, APOE ε4 genotype status, and kinship (relatedness). ResultsOur analysis identified 31 unique SNPs from 24 genes reaching an exploratory significance threshold of 1×10-5. Fourteen of the 24 genes have been previously associated with the brain/cognition, and 5 genes have been previously associated with circulating lipids. Importantly, 8 of the genes we identified, DAB1, SORCS2, SERINC5, OSBPL3, CPA6, DLG2, MUC19, and RGMA, have been associated with both cognition and circulating lipids. We identified 22 unique SNPs for which individuals with the minor alleles benefit substantially from increased ω-3 fatty acid concentrations and 9 unique SNPs for which the common homozygote benefits. ConclusionsIn this GWIS of ω-3 PUFA species on cognitive outcomes, we identified 8 unique genes with plausible biology suggesting individuals with specific polymorphisms may have greater potential to benefit from increased ω-3 PUFA intake. Additional replication in prospective settings with more diverse samples is needed.

Cognitive Testing in Diverse Populations to Further the Objective and Clinical Understanding Study ‐ FOCUS

AbstractBackgroundOne of the great challenges facing clinical trial recruitment is to have a representative sample reflective of the diversity of the US population. While racial and ethnic minorities compromise 39% of the United States population, they only account for 2%‐16% of clinical trial participants.1 The aim of the FOCUS study was to collect cognitive testing data from a diverse population and develop normative ranges for Cognivue, the first FDA‐cleared computerized cognitive assessment device based on modern cognitive neuroscience. Cognivue Thrive provides a 5‐minute cognitive screen while Cognivue Clarity provides a 10‐minute comprehensive assessment, allowing both physicians and non‐physician clinicians to objectively and quantitatively access brain health beyond traditional paper and pencil cognitive tests.MethodCognivue partnered with Velocity Clinical Research to lead the recruitment efforts for the FOCUS study. The enrollment goal included an objective to enroll a group resembling the racial, ethnic, gender, and educational makeup recorded in the 2020 U.S. census data. Study subjects were recruited through local community outreach, participant referrals, and advertising. Recruitment was stopped once goals for specific sub‐groups were reached, to model real‐world outcomes. Cognivue Thrive and Clarity were administered to assess scoring and normative ranges and compared against performance on other neuropsychological test batteries within the diverse study cohort.ResultThe Cognivue/Velocity partnership resulted in recruitment of more than 1,500 subjects from 14 sites in 11 states with a mean age of 50.2±16.3y (range 18‐89), 59.2% female, and 51.8% with 12 years or less of education. Over 28% of subjects identified their race as Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Pacific Islander, or other non‐white, and over 12% of participants identified as Hispanic or Latino.ConclusionWorking in collaboration with Velocity, a clinical research partner with study sites throughout the United States, Cognivue was able to reach a 37% research participation rate of historically underserved and underrepresented populations in the national FOCUS study. 1Clin Pharmacol Ther. 2015 Mar;97(3):263‐73. https://doi.org/10.1002/cpt.61.

6 A review of neuropsychological measures of executive functioning in the Japanese and Japanese-American population

Objective:There are approximately 1.5 million Japanese and Japanese Americans in the United States, with the Japanese population increasing steadily over the past two decades. Given the growing number of the Japanese population, it is likely that a clinical neuropsychologist may encounter a Japanese patient, particularly for neurocognitive disorder evaluations given the aging population. Literature has reported that cross-cultural bias in neuropsychological testing and cultural factors affect individuals’ test performance. In order to conduct and interpret neuropsychological assessments for this population, it is important to use normative data and consider the impact of various factors such as acculturation, language, and generation in the U.S. Availability of normative cognitive test data for Japanese-Americans is limited. Tests with most extensive use, adaptation, validation, and norming were identified. Many clinically used measures of executive functioning (EF) have been translated into Japanese and studied in multiple clinical populations. We present information on tests in this domain given their appropriateness for use in cross-linguistic and cross-cultural evaluations.Participants and Methods:Available studies of neuropsychological tests measuring EF that have been translated and normed in the Japanese and/or Japanese-American patient population are reported. Review of the literature was conducted by authors of Japanese descent familiar with neuropsychological assessment and Japanese and Japanese-American culture. We prioritized studies published in both English and Japanese and those that included commonly utilized tests in the U.S, allowing for maximum accessibility and utility for Western-based neuropsychologists. Additionally, inclusion priority was given to studies published in English which report the clinical diagnoses, age range, and gender characteristics of the sample population. The Wisconsin card sorting test (WCST) and Trail Making Test (TMT) were reviewed.Results:The WCST and the TMT, with its variant, was the most normed EF cognitive test currently available. The Keio version Japanese-Trail Making Test (J-TMT) and a simplified version of the Trail Making Test (S-TMT) has been utilized in Japan, however norms are still lacking. Of the available studies, the S-TMT and J-TMT were found to be moderately correlated with the TMT. The Keio version WCST (KWCST) (Kao et al., 2012) was correlated to education level (Abe et al., 2004), appropriately differentiating severity of social anxiety disorder (Fujii et al., 2013), patients with schizophrenia (Banno et al., 2012), and cognitive impairment in Parkinson’s disease (Yoshii et al., 2019).Conclusions:Information regarding translated and normed tests are presented to assist clinical neuropsychologists provide competent services to Japanese-Americans. The J-TMT and the S-TMT may be clinically useful as an evaluation of attention for the Japanese population. The KWCST has also been found to be an appropriate tool for this population. However, publicly available norms for these assessments are still sparse, and there is very limited information about administration of these tests by English-speaking neuropsychologists with the use of interpreters. Further work is needed to increase access to and awareness of linguistically and culturally appropriate versions of clinical measures to better serve the Japanese and Japanese-American population.

Which Information Matters? Using Policy Capturing to Understand Psychological Recommendations of Civil Competency

ABSTRACT Courts rely heavily on the recommendations of mental health evaluators when making decisions about competency (e.g., Zapf, Hubbard, Cooper, Wheeles, & Ronan, 2004), including civil competency (e.g., Quickel, Demakis, & Reeve, 2017); however, very little is known about how evaluators arrive at their opinions regarding an individual’s capacity. The current study assessed clinical decision-making using a policy capturing methodology. An ecologically valid sample (N = 47) of predominantly white (87.23%) and female (55.30%) clinicians who were eligible to conduct civil competency evaluations in North Carolina were recruited to examine the degree to which five key factors (functional test data, cognitive test data, personality test data, hospitalization history, and/or medication compliance) influenced clinician competency determinations. Personal insight into one’s decision-making process was also measured. Consistent with previous research, functional test data was weighted most heavily in evaluator decisions, though all five factors were considered. Further analysis suggested variable levels of self-awareness of one’s decision-making policies by participants depending on the factor. In addition, there was high agreement among clinicians when cases were straightforward, but perfect disagreement (half recommending competency, half recommending incompetency) among clinicians when cases were more complex. Implications for civil competency assessment and decision-making are discussed.

SARS-CoV-2-Specific Immune Responses in Patients With Postviral Syndrome After Suspected COVID-19.

Millions of Americans were exposed to SARS-CoV-2 early in the pandemic but could not get diagnosed with COVID-19 due to testing limitations. Many have developed a postviral syndrome (PVS) including neurologic manifestations similar to those with postacute sequelae of SARS-CoV-2 infection (Neuro-PASC). Owing to those circumstances, proof of SARS-CoV-2 infection was not required for evaluation at Northwestern Medicine's Neuro COVID-19 clinic. We sought to investigate clinical and immunologic findings suggestive of SARS-CoV-2 exposure in patients with PVS. We measured SARS-CoV-2-specific humoral and cell-mediated immune responses against Nucleocapsid and Spike proteins in 29 patients with PVS after suspected COVID-19, 32 confirmed age-matched/sex-matched Neuro-PASC (NP) patients, and 18 unexposed healthy controls. Neurologic symptoms and signs, comorbidities, quality of life, and cognitive testing data collected during clinic visits were studied retrospectively. Of 29 patients with PVS, 12 (41%) had detectable humoral or cellular immune responses consistent with prior exposure to SARS-CoV-2. Of 12 PVS responders (PVS+), 75% harbored anti-Nucleocapsid and 50% harbored anti-Spike responses. Patients with PVS+ had similar neurologic symptoms as patients with NP, but clinic evaluation occurred 5.3 months later from the time of symptom onset (10.7 vs 5.4 months; p = 0.0006). Patients with PVS+ and NP had similar subjective impairments in quality of life measures including cognitive function and fatigue. Patients with PVS+ had similar results in objective cognitive measures of processing speed, attention, and executive function and better results in working memory than patients with NP. Antibody and T-cell assays showed evidence of prior SARS-CoV-2 exposure in approximately 40% of the PVS group. Three-quarters of patients with PVS+ had detectable anti-Nucleocapsid and one-half anti-Spike responses, highlighting the importance of multitargeted COVID-19 immunologic evaluation and the limitations of commercially available diagnostic tests. Despite their persistent symptoms, lack of COVID-19 diagnosis likely delayed clinical care in patients with PVS. Our data suggest that millions of Americans presenting with PVS resembling Neuro-PASC were indeed exposed to SARS-CoV-2 at the beginning of the pandemic, and they deserve the same access to care and inclusion in research studies as patients with NP with confirmed COVID-19 diagnosis.

SDPS-23 CUMULATIVE TUMOR VOLUME THRESHOLD CORRELATES WITH NEUROCOGNITIVE IMPAIRMENT IN PATIENTS WITH NEWLY DIAGNOSED BRAIN METASTASES

Abstract OBJECTIVE To explore the basic situation of cognitive function in patients with initial state of brain metastasis and the potential factors affecting cognitive function, so as to find the critical value of cumulative tumor volume leading to cognitive dysfunction. METHODS A total of 284 patients who were newly diagnosed with brain metastases and underwent cognitive testing before radiotherapy in Guangdong Sanjiu Brain Hospital from 2016 to 2022 were retrospectively analyzed. The basic demographic information of the patients, KPS at the time of initial diagnosis, the number of brain metastases, the cumulative tumor volume, and the cognitive function test data before treatment were organized. RESULTS The cognitive impairment occurred in 100/284 patients (the criteria for cognitive impairment is that at least two of the eight sub-tests are less than 1.5 standard deviation or at least one is less than 2 standard deviations). Multivariate analysis showed that the number of tumors was not a factor in cognitive dysfunction. Age, gender, KPS, educational level, and cumulative tumor volume were risk factors affecting cognitive function. The cumulative tumor volume cut-off value for MOCA, HVLT-R immediate memory, HVLT-R delayed memory, VFT, TMT-A, and TMT-B cognitive impairment were 13.608, 13.125, 11.070, 14.523, 11.070, and 11.113 cc, respectively, while cut-off value for SDMT and TOL were 5.435 and 4.528 cc, respectively. CONCLUSIONS Before treatment, cognitive impairment of brain metastases had no significant correlation with the number of metastases but had a significant correlation with the cumulative tumor volume. The cumulative tumor volume cut-off value involving overall cognitive dysfunction, memory dysfunction, speech dysfunction, and decreased thinking speed is between 11-14.5 cc, and the cumulative tumor volume critical threshold involving executive dysfunction and computational dysfunction is between 4.5-5.5 cc.

Neuropsychology of cognitive aging in rhesus monkeys

Aged rhesus monkeys, like aged humans, show declines in cognitive function. We present cognitive test data from a large sample of male and female rhesus monkeys, 34 young (aged 3.5–13.6 years) and 71 aged (aged 19.9–32.5 years at the start of cognitive testing). Monkeys were tested on spatiotemporal working memory (delayed response), visual recognition memory (delayed nonmatching to sample), and stimulus-reward association learning (object discrimination), tasks with an extensive evidence base in nonhuman primate neuropsychology. On average, aged monkeys performed worse than young on all 3 tasks. Acquisition of delayed response and delayed nonmatching to sample was more variable in aged monkeys than in young. Performance scores on delayed nonmatching to sample and object discrimination were associated with each other, but neither was associated with performance on delayed response. Sex and chronological age were not reliable predictors of individual differences in cognitive outcome among the aged monkeys. These data establish population norms for multiple cognitive tests in young and aged rhesus monkeys in the largest sample reported to date. They also illustrate independence of cognitive aging in task domains dependent on the prefrontal cortex and medial temporal lobe.

Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade.

Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects. This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data. We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data. Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories. Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.

Association of Liver Fibrosis with Cognitive Test Performance and Brain Volume Changes in the UK Biobank Study

AbstractBackgroundLiver fibrosis is a chronic liver condition that, though frequently subclinical, has widespread systemic effects. We hypothesized that liver fibrosis is associated with worse cognitive performance and corresponding brain imaging changes.MethodWe examined the association of liver fibrosis with cognition and brain volumes among adults in the UK Biobank study, which prospectively enrolled approximately 500,000 people starting in 2007 and subsequently collected cognitive test and brain MRI data for some participants. We included participants with available liver fibrosis, cognitive test, and brain imaging data. Liver fibrosis was defined at baseline using validated cutoffs of the Fibrosis‐4 (FIB‐4) liver fibrosis score. The primary cognitive test outcome was the Digit Symbol Substitution Test (DSST), a multidomain test. Secondary cognitive test outcomes were executive function tests (Trails A, Trails B, Reaction Time) and memory tests (Numeric Memory, Pairs Matching). The primary imaging outcome was white matter hyperintensity volume; secondary outcomes were hippocampal volume and total brain volume. We used multiple linear regression models to evaluate the association of liver fibrosis with cognitive test performance and brain volumes while adjusting for potential confounders.ResultsAmong 105,313 participants with cognitive test data, the mean age was 56.1 years and 56% were women. Standard liver chemistries were largely in the normal range. However, 2.0% (95% CI, 1.9‐2.1%) had liver fibrosis based on FIB‐4 scores. Cognitive tests were completed a median of 5.8 years after baseline liver fibrosis assessment. After adjusting for demographics, socioeconomics, education, body mass index, metabolic syndrome, hypertension, diabetes, dyslipidemia, and tobacco and alcohol use, liver fibrosis was associated with worse performance on the DSST (β = ‐0.40; 95% CI, ‐0.60, ‐0.20; P&lt;0.001) (Figure). Liver fibrosis was associated with worse executive function but not memory test performance (Table). We included 34,730 participants with brain MRI, obtained a median of 9.3 years after baseline. In adjusted models, liver fibrosis was associated with lower hippocampal volume (β = ‐58.8; 95% CI, ‐94.7, ‐22.9; P = 0.001) and higher white matter hyperintensity volumes (β = 1142.8; 95% CI, 311.6, 1973.9; P = 0.007) (Table, Figure).ConclusionLiver fibrosis is associated with worse cognitive performance, perhaps explained by hippocampal volume loss and white matter hyperintensity burden.

Association of liver fibrosis with cognitive test performance and brain imaging parameters in the UK Biobank study.

We hypothesized that liver fibrosis is associated with worse cognitive performance and corresponding brain imaging changes. We examined the association of liver fibrosis with cognition and brain imaging parameters in the UK Biobank study. Liver fibrosis was assessed using the Fibrosis-4 (FIB-4) score. The primary cognitive outcome was the digit symbol substitution test (DSST); secondary outcomes were additional executive function/processing speed and memory tests. Imaging outcomes were hippocampal, total brain, and white matter hyperintensity (WMH) volumes. We included 105,313 participants with cognitive test data, and 41,982 with magnetic resonance imaging (MRI). In adjusted models, liver fibrosis was associated with worse performance on the DSST and tests of executive function but not memory. Liver fibrosis was associated with lower hippocampal and total brain volumes, without compelling association with WMH volume. Liver fibrosis is associated with worse performance on select cognitive tests and lower hippocampal and total brain volumes. It is increasingly recognized that chronic liver conditions impact brain health. We performed an analysis of data from the UK Biobank prospective cohort study. Liver fibrosis was associated with worse performance on executive function tests. Liver fibrosis was not associated with memory impairment. Liver fibrosis was associated with lower hippocampal and total brain volumes.

Efficacy of several statistical methods in differentiating TBI and co-occurring conditions: A replication study

Much historical controversy has surrounded TBI criteria especially associated with milder injuries. Lack of sufficient injury documentation underlies problems in the diagnosis of TBI as does variability across multiple expert consensus criteria for diagnosing TBI. The efficacy of diagnostic classification utilizing test data sets with comparison group methodology increases diagnostic accuracy. Five statistical comparisons utilized here improved differential diagnostic accuracy compared with PCS and somatization with neuropsychological testing. Objectives (1) Cross-validation of neuropsychological test data sets of moderate-severe TBI (N = 30) with test data from moderate-severe (N = 74); somatization (N = 24) and PCS (N = 22) cases in a database, (2) Determine if cognitive test data sets alone differentiated TBI from other groups, and (3) Evaluate the efficacy of measures in comparisons: Kullback-Leibler, Correlation, Patterns, Cohen’s d, and MNB. Materials and methods Meyer’s Neuropsychological System; Comparison groups -TBI sample with structural evidence of brain injury (CT/MRI); comparison of 5 statistical measures’ efficacy in test data analysis comparing a community sample of moderate TBI (N=30) with a data base containing moderate-severe TBI (N = 74) + co-occurring groups (PCS N = 22) + Somatization (N = 24). Measures utilized: Correlation, Kullbeck-Leibler divergence, Cohen’s d, MNB code, Configuration. Results Combining the five measures most accurately matched the TBI sample (30/30 cases) with MNB comparison groups of similar TBI severity while differentiating those cases from PCS and Somatoform cognitive testdata. Both Kullback Leibler & Cohens’ d reduced false positive errors in comparison with the other measures.

Chemotherapy-induced functional brain abnormality in colorectal cancer patients: a resting-state functional magnetic resonance imaging study.

IntroductionChemotherapy-induced cognitive impairment (i.e., “chemobrain”) is a common neurotoxic side-effect experienced by many cancer survivors who undergone chemotherapy. However, the central mechanism underlying chemotherapy-related cognitive impairment is still unclear. The purpose of this study was to investigate the changes of intrinsic brain activity and their associations with cognitive impairment in colorectal cancer (CRC) patients after chemotherapy.MethodsResting‐state functional magnetic resonance imaging data of 29 CRC patients following chemotherapy and 29 matched healthy controls (HCs) were collected in this study, as well as cognitive test data including Mini Mental State Exam (MMSE), Montreal Cognitive Assessment (MoCA) and Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog). The measure of fractional amplitude of low-frequency fluctuation (fALFF) was calculated and compared between groups. The correlations between the fALFF of impaired brain region and cognitive performance were also analyzed.ResultsCompared with HCs, CRC patients following chemotherapy showed decreased fALFF values in the left anterior cingulate gyrus (ACG) and middle frontal gyrus, as well as increased fALFF values in the left superior frontal gyrus (orbital part) and middle occipital gyrus. Moreover, positive associations were identified between fALFF values of the left ACG and the total scores of MMSE, MoCA and FACT-Cog in the patient group.ConclusionThese findings indicated that CRC patients after chemotherapy had decreased intrinsic brain activity in the left ACG, which might be vulnerable to the neurotoxic side-effect of chemotherapeutic drugs and related to chemotherapy-induced cognitive impairment.

Differential diagnosis of schizophrenia using decision tree analysis based on cognitive testing

Background and objectivesTo explore the discriminatory ability of a decision tree model based on cognitive testing data for the differential diagnosis of schizophrenia. MethodsThis study enrolled 82 patients with schizophrenia and 82 patients with affective disorders. The cognitive function of the two groups of participants was assessed based on learning, symbol coding, digital span, trail making, and category fluency tests. The logistic regression model in the sklearn package in Python was applied to discriminate and analyse the data for all 11 variables in the MATRICS Consensus Cognitive Battery (MCCB). ResultsThe recognition rate for schizophrenia and affective disorder using all 11 variables of the MCCB was 82%. ConclusionThe logistics model based on cognitive data distinguished patients with schizophrenia from those with affective disorder.