Cognitive Tests Research Articles

B - 99 Timely Matters: Processing Speed and Other Cognitive Corelates of Identi-Fi Accuracy and Time to Completion

Abstract Objective The Identi-Fi is a test of visuospatial organization with overall performance represented by the Visual Organization Index (VOI). Though untimed, the Professional Manual indicates administration takes ~10 minutes in the standardization sample. We examined Identi-Fi time of completion (TOC) in a mixed clinical sample and explored whether TOC and VOI are differentially associated with other neuropsychological measures. Method Participants were 240 adults referred for clinical neuropsychological evaluation, 78.3% being aged 60+ (M = 64.50 ± 12.38 years, range = 21–79), male (54.6%), with 14.80 ± 2.89 years of education (range = 7–21). They completed the Identi-Fi and other cognitive tests (WAIS-IV Block Design and Digit Span; Trail Making Test; Boston Naming Test; D-KEFS Color-Word Interference). Correlation and linear regression were used to examine relationships. Results Overall, VOI was low average (M = 85.61 ± 19.00, range = 40–125). TOC was slightly longer (M = 12.92 ± 6.04 minutes, range = 4.07–47.78) than reported in the manual. VOI was correlated with visuoconstruction, confrontation naming, attention, processing speed and executive functions (all p ≤ 0.001), as well as TOC (r = −0.195, p = 0.002) and education (r = 0.136, p = 0.035). TOC was corelated with age (r. = 384, p < 0.001), education (r = 0.141, p = 0.029), processing speed (TMT-A: r = −0.329, p < 0.001; CW1: r = −0.171, p = 0.014), cognitive flexibility (r = −0.230, p = 0.001), and response inhibition (r = −0.269, p < 0.001). TOC was predicted by processing speed (β = −4.986, p = 0.049) even after accounting for age and education. Conclusion TOC may be longer in clinical populations, though this may reflect the older age of this sample. Although time and accuracy on the Identi-Fi correlated with processing speed, accuracy was also associated with other cognitive abilities. Further research into the clinical utility of Identi-Fi TOC is warranted.

B - 38 Concussion Clinical Outcomes and Recovery Time in Individuals with Pre-Existing Anxiety and/or Depression

Abstract Objective Post-injury anxiety and mood difficulties are common symptoms following concussion. However, limited research has explored the impact of anxiety and/or depression history on individuals’ clinical outcomes and recovery time post- concussion. This study aims to determine the influence of anxiety and/or depression history on individuals’ clinical outcomes and examine outcomes of those with both anxiety and depression history. Method We conducted a retrospective review of 297 concussed patients. All participants completed a clinical interview, Immediate Post-Concussion Assessment and Cognitive Test (ImPACT), Clinical Profile Screen (CP-Screen), and Vestibular/Ocular-Motor Screening (VOMS). Participants were categorized into one of three anxiety-depression subgroups — no anxiety or depression history (NONE), anxiety or depression history (EITHER), or anxiety and depression history (BOTH)— based on clinical interviews. Results The BOTH group reported higher symptom burden (CP Screen Total Score; p < 0.001) and performed worse on ImPACT Visual Memory (p = 0.03) compared to NONE and EITHER groups. Overall, recovery time differed significantly between groups (p = 0.006). The NONE group recovered significantly faster than the EITHER group (p = 0.04), and the BOTH group (p = 0.03). However, no significant difference in recovery time was noted between the EITHER and BOTH groups (p = 0.58). Conclusions Our results suggest that anxiety/depression history is associated with more severe post-concussion symptoms, worse visual memory, and longer recovery times when compared to those with no history of anxiety or depression. These findings highlight the importance of screening for anxiety and depression history in clinical settings and exploring ways to improve concussion recovery for individuals with anxiety and/or depression history.

A - 116 A Neuropsychological Testing Protocol for Assessing Lecanemab Eligibility for Alzheimer’s Disease: the First Fifty Patients

Abstract Objective Since the FDA approved lecanemab for Alzheimer’s disease (ad) treatment in 2023, neuropsychology’s role in the treatment eligibility determination process has become increasingly important. Not only is objective evidence of cognitive impairment required for the diagnosis of mild cognitive impairment (MCI) and mild dementia, but testing can be used to measure treatment efficacy and monitor for adverse effects. Our center developed a specialized protocol to assess cognitive and behavioral functioning for assisting in the eligibility determination process. Method Fifty adults (Mean Age = 73.8 years) underwent neuropsychological testing, including the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), as a part of their eligibility workup. Caregiver questionnaires were used to assess behavioral functioning. Test scores and patient outcomes were explored. Results Thirteen patients (26%) were prescribed lecanemab. Another 13 patients were deemed ineligible (five due to their cognitive results), eight patients (16%) were undecided, and 16 patients (32%) had not yet completed their workup. Of those who initiated lecanemab, eight patients (62%) had a diagnosis of MCI and six were diagnosed with mild dementia. Of these patients, eight (82%) showed an amnestic pattern on testing (RBANS Delayed Recall Standard Score Mean = 46.8). Additional analyses involving ad biomarkers, neuroimaging, and APOE status, were conducted. Conclusion Over one quarter of patients referred for neuropsychological testing as a part of their eligibility determination initiated lecanemab treatment for ad. Cognitive testing was directly related to determining ineligibility in 10% of patients. This review of an initial lecanemab treatment cohort highlights the importance of neuropsychology in the eligibility determination process.

A - 12 Neuropsychological Test Best Fit for Identifying on-the-Road Driving Behaviors in Normal and Abnormal Aging Populations: a Systematic Review

Abstract Objective This systematic review’s purpose is to identify neuropsychological assessments that are accurate at predicting driving behaviors in geriatric populations. The population included normal aging, mild cognitive impairment (MCI), and dementia. Data Selection PubMed and APA PsycNet databases were searched using two separate keyword searches: cognitive evaluation and driving behaviors and aging; neuropsychological test and driving behaviors and aging. The databases were searched March 10, 2024, and again on April 26, 2024. This yielded 278 articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used to identify articles. Articles were excluded if they did not have on-road driving behaviors or simulated driving behaviors, neuropsychological test, if the average participant age was not geriatric, or if it was a non-peer reviewed article. Data Synthesis After following PRISMA selections, eight articles were included, creating a combined sample size of 927 (Mean age = 74.16, SD = 2.38; mean years of education = 14.17, SD = 1.09; female percentage = 40.78). The test deemed most correlated were Neuropsychological Assessment Battery: Driving Scene Test, Clock Drawing, Useful Field of View, Trail making task, Mini-Mental State Exam, verbal and visual memory components from the Wechsler Memory Scale, Rey-Osterrieth Complex Figure, and Maze Navigation Task. Conclusion General cognitive screening tests as well as visuomotor, visual–spatial, visual attention and verbal and non-verbal memory tests highly correlate with real driving behaviors and accurately predict on-the-road driving behaviors. This indicates the cognitive and behavioral complexity of driving. Though these tests accurately predict driving behaviors, their abilities to do so may differ depending on cultural groups.

A - 83 Concordance between Informant Measures, Executive Functioning, and Functional Ability in an Older Adult Population

Abstract Objective Informant-report measures often do not correlate with neuropsychological tests measuring the same cognitive construct, yet they may offer insight into everyday difficulties not captured by objective tests. Performance-based measures of functional ability, developed to capture real-world skills, may better align with informant-report measures. Clarifying the relationship between subjective and objective assessment tools in older adults could enhance precision in selecting the most appropriate measures. Method As part of a comprehensive neuropsychological battery, community-dwelling older adults who were cognitively unimpaired or who presented with subjective cognitive decline or mild cognitive impairment completed tests of executive functioning (EF), (D-KEFS Trail Making Test 4, Letter Fluency, WCST, WAIS-Comprehension) and financial capacity, Financial Capacity Instrument (FCI-SF). Informants responded to measures of functional ability, Amsterdam Instrumental Activities of Daily Living Questionnaire Short Version (A-IADL-Q-SV) and Assessment of Functional Capacity Interview (AFCI) and items capturing EF on the Brief Informant Form of Neurobehavioral Symptomatology (BINS). Results Participants’ (N = 97, Mage = 74.64 ± 7.42 years; Meducation = 15.76 ± 2.42 years; 74.2% female) FCI-SF performance significantly correlated with higher A-IADL-Q-SV (r = 0.403, p < 0.01) and AFCI (r = −0.294, p < 0.01) scores, whereas there was no significant correlation between a composite Z-score for traditional neuropsychological tests and select EF items from the BINS, (r = −0.119, p = 0.252). Conclusion We found greater alignment between objective and subjective measures of functional ability than EF, possibly due to the observable nature of functional tasks. Objective and informant measures of EF do not align, potentially targeting different aspects of cognition in non-demented older adults. This should be considered when selecting instruments measuring specific constructs of interest.

A - 100 Who Is at the Door? Clinical Presentations and Predictors of Dementia Diagnosis in a Specialist Dementia Service

Abstract Objective This service audit aimed to identify predictors associated with a dementia diagnosis and the diagnostic base rate in a UK-based, specialist Younger People with Dementia (YPWD) Service. Method All patients referred between July 2022 and 2023 to the YPWD service were included in the study. All 191 patients were under 65 years at the time of referral. 69 patients were excluded from analysis (e.g., if the patient withdrew from the service prior to assessment or if the referral was deemed inappropriate based on service guidelines). A quasi-experimental design was used, investigating the relative predictive value of factors such as demographics, presenting cognitive symptoms, comorbidities, or mental health to receiving a dementia diagnosis. Following definition, raters reviewed client case notes to establish the presence or absence of each criterion. Results Significant predictors of a dementia diagnosis in YPWD were functional change (p < 0.001), behavior change (p < 0.001), being accompanied to assessment (p < 0.001), diminished insight (p < 0.001), executive functioning difficulties (p < 0.05), cognitive screening test score below cut-off (p < 0.05) and previous radiological investigation prior to referral (p < 0.001). The diagnostic rate for YPWD was 15%. Conclusions Memory problems alone are an insufficient predictor for a dementia diagnosis in YPWD, unless accompanied by additional factors. Overreliance on the presence of subjective memory complaints in primary care as a percipient to referral for specialist assessment contributes to a low diagnostic rate for the service The presence of insight and attending appointments alone contraindicate the presence of an organic disorder. Results indicate that factors beyond diagnostic criteria may be clinically significant.

A - 13 Cognitive Correlates of Technology-Based Instrumental Activities of Daily Living Performance in Older Adults Presenting for Cognitive Evaluations

Abstract Objective Rapid advances in technology have altered how daily activities are performed. Accumulating evidence suggests technology-based instrumental activities of daily living (iADLs) are increasingly common in older adults’ lives, and assessing these skills may improve diagnostic identification of individuals with Alzheimer’s disease and related dementias (ADRD). While iADLs are complex tasks reliant on multiple cognitive processes, prior work suggests memory and executive functioning are the cognitive processes most strongly predictive of iADL performance in ADRD. However, whether similar associations exist with technology-based iADLs has not been established. The goal of the present study was to evaluate the cognitive correlates of technology-based compared to traditional iADL items. Method One hundred seventy-eight individuals (mean age: 75.35 ± 7.30) presenting for evaluation of cognitive status completed tests of memory, executive functioning, language, and processing speed. Care partners completed the Functional Activities Questionnaire (FAQ) and 11 technology-based iADL items. Associations between cognition and traditional and technology-based FAQ items were examined through Pearson’s correlations and multiple regression analyses. Results Cognition was significantly correlated with both traditional and technology-based iADLs (|r’s| > 0.30, p’s.44). In multiple regression models, executive functioning and processing speed but not memory were the strongest predictors of traditional iADL performance (p’s < 0.02), but for independence with technology-based iADLs, executive functioning alone (p < 0.001) emerged. Conclusions Relations between cognition and daily functioning are similar for both traditional and technology-based FAQ items, with executive functioning particularly relevant for both types of tasks. Implications for clinical practice and technology-based interventions are discussed.

Mild cognitive impairment prediction based on multi-stream convolutional neural networks

BackgroundMild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Current methods of MCI detection include cognitive tests to screen for executive function impairments, possibly followed by neuroimaging tests. However, these methods are expensive and time-consuming. Several studies have demonstrated that MCI and dementia can be detected by machine learning technologies from different modality data. This study proposes a multi-stream convolutional neural network (MCNN) model to predict MCI from face videos.ResultsThe total effective data are 48 facial videos from 45 participants, including 35 videos from normal cognitive participants and 13 videos from MCI participants. The videos are divided into several segments. Then, the MCNN captures the latent facial spatial features and facial dynamic features of each segment and classifies the segment as MCI or normal. Finally, the aggregation stage produces the final detection results of the input video. We evaluate 27 MCNN model combinations including three ResNet architectures, three optimizers, and three activation functions. The experimental results showed that the ResNet-50 backbone with Swish activation function and Ranger optimizer produces the best results with an F1-score of 89% at the segment level. However, the ResNet-18 backbone with Swish and Ranger achieves the F1-score of 100% at the participant level.ConclusionsThis study presents an efficient new method for predicting MCI from facial videos. Studies have shown that MCI can be detected from facial videos, and facial data can be used as a biomarker for MCI. This approach is very promising for developing accurate models for screening MCI through facial data. It demonstrates that automated, non-invasive, and inexpensive MCI screening methods are feasible and do not require highly subjective paper-and-pencil questionnaires. Evaluation of 27 model combinations also found that ResNet-50 with Swish is more stable for different optimizers. Such results provide directions for hyperparameter tuning to further improve MCI predictions.

The Association of Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease with Cognitive Intra-Individual Variability

Abstract Objective Cognitive intra-individual variability (IIV) is a sensitive predictor of cognitive decline and disease severity in Alzheimer’s disease (AD). Despite its sensitivity, whether IIV is merely a psychometric artifact or disease pathology biomarker remains unknown. The present study evaluated the association between IIV and cerebrospinal fluid (CSF) biomarkers of AD. Method Participants included 422 individuals from the National Alzheimer’s Coordinating Center Unified Dataset 3.0 who completed baseline neuropsychological assessment and had CSF data. All participants were adult monolingual English speakers. Participants with vision or hearing impairments were excluded. Cases were stratified into cognitively normal (n = 267) and AD groups (n = 155; mild cognitive impairment = 50, dementia = 105). Cross-sectional IIV was calculated by obtaining the individual standard deviation (iSD) of ten cognitive tests. Finally, the coefficient of variation (CoV) was computed by dividing iSD by the participant’s overall test battery mean. Non-parametric Spearman-rank correlations were used to assess the relation between CoV and CSF biomarkers, including beta-amyloid 1–42, total tau (t-tau), and phosphorylated tau (p-tau181). Results In the AD group, CoV was positively correlated with p-tau181 (r = 0.285, p = 0.003) and t-tau (r = 0.241, p = 0.009), and negatively correlated with beta-amyloid 1–42 (r = −0.314, p < 0.001). Correlations between CoV and CSF biomarkers were not significant in the cognitively normal group for beta-amyloid 1–42 (r = 0.076, p = 0.215), p-tau181 (r = −0.014, p = 0.840), and t-tau (r = −0.046, p = 0.485). Conclusions In people with mild cognitive impairment and dementia of presumed AD etiology, cognitive IIV is associated with CSF biomarkers. These findings provide preliminary evidence that IIV is not merely a statistical artifact, but is associated with AD neuropathology.

A - 4 The Potential Applications of Software Supporting the Early Detection of Cognitive Disorders and Dementia in Diagnostics and Prevention

Abstract Objective In Hungary, the process of diagnosing dementia is slow and time-consuming. Currently, there are no well-developed systems and strategies at the local level for screening, and there is no artificial intelligence algorithm that could determine early signs of dementia based on the patient’s digital behavioral patterns. Methods Two PILOTs were conducted using the PreDem platform. Over the PILOTs’ duration (2021.09.01.-2024.04.09), 61,902 test data were analyzed. The 259 participants completed SDMT-type tests, Stroop tests, and memory/word games. Results We established a unified system for task evaluation, facilitating cross-test result comparisons. Participants (n = 43,902) were grouped into three categories: 1st - presumed dementia patients (13,932), 2nd - diagnosed MS patients (16,175), and 3rd - presumably normal population (13,795). Comparing the first two groups to the normal population revealed significant differences, vividly illustrated by density functions. A key finding is the substantial improvement in individuals dealing with memory disorders and forgetfulness through regular cognitive game performance. Conclusion Study results reveal the PreDem platform’s potential as a valuable tool for early dementia detection and prevention. Combining cognitive tests and artificial intelligence, the platform can successfully identify early signs of dementia and cognitive impairment (90% accuracy), potentially leading to early diagnosis, treatment, and improved quality of life for patients and families.

Brain hemodynamic responses and fall prediction in older adults with multiple sclerosis.

We examined whether brain hemodynamic responses, gait, and cognitive performances under single- and dual-task conditions predict falls during longitudinal follow-up in older adults with multiple sclerosis (OAMS) with relapsing-remitting and progressive subtypes. Participants with relapsing-remitting (n = 53, mean age = 65.02 ± 4.17 years, %female = 75.5) and progressive (n = 28, mean age = 64.64 ± 4.31 years, %female = 50) multiple sclerosis (MS) subtypes completed a dual-task-walking paradigm and reported falls during longitudinal follow-up using a monthly structured telephone interview. We used functional near-infrared spectroscopy (fNIRS) to assess oxygenated hemoglobin (HbO) in the prefrontal cortex during active walking and while performing a cognitive test under single- and dual-task conditions. Adjusted general estimating equations models indicated that higher HbO under dual-task walking was significantly associated with a reduction in the odds of reporting falls among participants with relapsing-remitting (odds ratio (OR) = 0.472, p = 0.004, 95% confidence interval (CI) = 0.284-0.785), but not progressive (OR = 1.056, p = 0.792, 95% CI = 0.703-1.588) MS. In contrast, faster stride velocity under dual-task walking was significantly associated with a reduction in the odds of reporting falls among progressive (OR = 0.658, p = 0.004, 95% CI = 0.495-0.874), but not relapsing-remitting (OR = 0.998, p = 0.995, 95% CI = 0.523-1.905) MS. Findings suggest that higher prefrontal cortex activation levels during dual-task walking, which may represent compensatory reallocation of brain resources, provide protection against falls for OAMS with relapsing-remitting subtype.

Exploring the Relationship between Cortical Thickness and Cognitive Abilities: A Multi-Modal Imaging Approach

Background: Cortical thickness has been associated with cognitive abilities in prior research, but the specific relationships remain unclear. Objectives: This study aimed to further examine associations between cortical thickness in various brain regions and performance on tests of intelligence and executive function. Methods: Structural MRI scans were obtained from 65 healthy adults aged 18-35. Cortical thickness was estimated across the cortex using Free Surfer software. Participants completed standard tests measuring IQ, working memory, cognitive flexibility, and inhibitory control. Correlation and regression analyses were used to relate regional cortical thickness to cognitive scores. Results: This study showed cortical thickness in prefrontal regions positively correlated with IQ, working memory, and cognitive flexibility. No significant associations were found between cortical thickness and response inhibition. Conclusions: The findings provide evidence for links between PFC thickness and higher cognitive abilities. A multi-modal neuroimaging approach combining structural MRI and cognitive testing is useful for elucidating brain-behavior relationships. Further research with larger samples is needed to fully characterize these associations.

Outcome measures used in adolescent sport-related concussion research: a scoping review

ObjectivesTo provide an overview of the outcome measures currently used after sports-related concussion (SRC) in adolescents, categorising by the constructs they assess, follow-up duration and their feasibility of use.DesignScoping review.Data...

Does the stress axis mediate behavioural flexibility in a social cichlid, Neolamprologus pulcher?

Behavioural flexibility plays a major role in the way animals cope with novel situations, and physiological stress responses are adaptive and highly efficient mechanisms to cope with unpredictable events. Previous studies investigating the role of stress responses in mediating behavioural flexibility were mostly done in laboratory rodents using stressors and cognitive challenges unrelated to the ecology of the species. To better understand how stress mediates behavioural flexibility in a natural context, direct manipulations of the stress response and cognitive tests in ecologically relevant contexts are needed. To this aim, we pharmacologically blocked glucocorticoid receptors (GR) in adult Neolamprologus pulcher using a minimally invasive application of a GR antagonist. GR blockade prevents the recovery after a stressful event, which we predicted to impair behavioural flexibility. After the application of the GR antagonist, we repeatedly exposed fish to a predator and tested their behavioural flexibility using a detour task, i.e. fish had to find a new, longer route to the shelter when the shortest route was blocked. While the latencies to find the shelter were not different between treatments, GR blocked fish showed more failed attempts during the detour tasks than control fish. Furthermore, weak performance during the detour tasks was accompanied by an increase of fear related behaviours. This suggests that blocking GR changed the perception of fear and resulted in an impaired behavioural flexibility. Therefore, our results support a potential link between the capacity to recover from stressors and behavioural flexibility in N. pulcher with potential consequences for an effective and adaptive coping with changing environments.

Modelling the joint accuracy of two diagnostic tests using evidence synthesis methods incorporating linked electronic health records

Background and ObjectivesTo compare the accuracy of different diagnostic pathways comprising of multiple diagnostic tests, statistical methods that evaluate combined or sequential test accuracy are required. This can only be achieved through joint synthesis of diagnostic accuracy data on all tests of interest, using models that account for dependencies between multiple tests. The aim of this research is to develop joint models to assess the diagnostic accuracy of two tests, using real-world evidence to inform within-study dependencies between tests. ApproachUsing a case study in Alzheimer’s disease dementia (ADD), we will develop Bayesian meta-analysis models to evaluate the combined diagnostic accuracy of two tests. A novel application of trivariate copulas will be used to capture within-study dependencies between two tests assessed in the same patients. Individual participant data from Dementias Platform UK (DPUK) Data Portal – a repository of linked electronic health record data optimised for dementia research – will be used to estimate dependencies between diagnostic tests for ADD. ResultsThe DPUK Data Portal includes records of over 3 million people from 51 long-term cohort studies, including individual-level test results for ADD verified against confirmed diagnoses. Analysis will focus on modelling the diagnostic accuracy of different testing strategies for ADD, combining cognitive function, imaging, and biomarker tests. Conclusions and ImplicationsResults of this study have the potential to inform healthcare decision-making regarding optimal diagnostic pathways by enabling the comparison of different testing strategies. The incorporation of real-world data from the DPUK Data Portal makes better use of the available evidence.

Implementation of automated cognitive testing systems for socially housed rhesus (Macaca mulatta) and squirrel (Saimiri spp.) monkeys: Age differences in learning.

Utilizing Automated Cognitive Testing Systems (ACTS) with group-housed nonhuman primates offers a number of advantages over manual testing and computerized testing of singly housed subjects. To date, ACTS usage has been limited to great apes or African monkeys. Here, we detail what we have learned while implementing ACTS with socially housed squirrel monkeys and rhesus macaques and provide information about the training process. In addition, we examined the effects of age on learning acquisition. We found age differences in learning for both squirrel monkeys and rhesus monkeys. Older monkeys were not as proficient as younger monkeys on learning to use the touch screens (squirrel monkeys only), discrimination learning (rhesus monkeys only; note: squirrel monkeys were not trained to criterion on this task), and recognition learning (both species). Overall, ACTS provide a number of advantages for studying cognition in socially living nonhuman primates and can be used to further investigate cognitive decline whether related to natural aging processes or disease pathology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Investigating Noun and Verb Naming in Behavioral Variant of Frontotemporal Dementia and Non-Patients Persian-Speaking

Introduction: Due to the prevalence of cognitive disorders, such as the behavioral variant of frontotemporal dementia (bvFTD) and the consequences that these disorders follow, early diagnosis and awareness of the deficiencies of these people in the cognitive and language areas is essential. Given that language is dependent on culture, examining the linguistic characteristics of such patients in different languages can provide valuable findings. Therefore, this study compares noun and verb naming abilities in individuals with bvFTD and non-patients Persian-speaking. Materials and Methods: In this cross-sectional study, 3 cognitive tests, including frontal assessment battery (FAB), Montreal cognitive assessment, and mini-mental state examination (MMSE), along with 2 noun naming and verb naming tests were performed on 15 patients with bvFTD and 30 homogeneous non-patient individuals. Results: The bvFTD group had significantly different scores for both noun and verb naming compared to the non-patient group (P<0.05). Meanwhile, the bvFTD group was more impaired in naming verbs than nouns, with the largest difference between groups in the verb naming task. Conclusion: the results showed that bvFTD patients have poorer noun and verb naming abilities than non-patients. In particular, in verb naming, they showed more deficits than nouns. One possible explanation is that the processing of verbs is more complicated than nouns and involves a more complex neural system and cognitive processes than noun processing. Another possibility is that verbs rely more heavily on frontal and temporal regions of the brain, which are typically affected by bvFTD.

Loss of the APP regulator RHBDL4 preserves memory in an Alzheimer's disease mouse model.

Characteristic cerebral pathological changes of Alzheimer's disease (AD) such as glucose hypometabolism or the accumulation of cleavage products of the amyloid precursor protein (APP), known as Aβ peptides, lead to sustained endoplasmic reticulum (ER) stress and neurodegeneration. To preserve ER homeostasis, cells activate their unfolded protein response (UPR). The rhomboid-like-protease 4 (RHBDL4) is an enzyme that participates in the UPR by targeting proteins for proteasomal degradation. We demonstrated previously that RHBLD4 cleaves APP in HEK293T cells, leading to decreased total APP and Aβ. More recently, we showed that RHBDL4 processes APP in mouse primary mixed cortical cultures as well. Here, we aim to examine the physiological relevance of RHBDL4 in the brain. We first found that brain samples from AD patients and an AD mouse model (APPtg) showed increased RHBDL4 mRNA and protein expression. To determine the effects of RHBDL4's absence on APP physiology in vivo, we crossed APPtg mice to a RHBDL4 knockout (R4-/-) model. RHBDL4 deficiency in APPtg mice led to increased total cerebral APP and amyloidogenic processing when compared to APPtg controls. Contrary to expectations, as assessed by cognitive tests, RHBDL4 absence rescued cognition in 5-month-old female APPtg mice. Informed by unbiased RNAseq data, we demonstrated in vitro and in vivo that RHBDL4 absence leads to greater levels of active β-catenin due to decreased proteasomal clearance. Decreased β-catenin activity is known to underlie cognitive defects in APPtg mice and AD. Our work suggests that RHBDL4's increased expression in AD, in addition to regulating APP levels, leads to aberrant degradation of β-catenin, contributing to cognitive impairment.

Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. A diagnosis of ASD is provided by a clinician following cognitive and behavioral evaluations, but there is currently no biomarker associating these metrics with neurological changes. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, we can evaluate which tests most reveal changes in the brain. Analyzing 273 participants (148 with ASD) ages 8-to-17 (49% female) through an NIH-sponsored Autism Centers of Excellence (ACE) network (Grant#: MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics. Analyzing data from all participants, conduction velocity but not g-ratio was significantly associated with many behavioral metrics. However, this pattern was reversed when looking solely at ASD participants. This reversal may suggest that the mechanism underlying differences between autistic and non-autistic individuals may be distinct from the mechanism underlying ASD behavioral severity. Two additional machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. By associating neuroimaging metrics with ASD, it may be possible to measure and identify individuals at high risk of ASD before behavioral tests can detect them.

Adaptation of the Cognitive Screening Test (Triagem Cognitiva – TRIACOG) for computer-mediated assessments: TRIACOG-Online

This study aims to present the adaptation, evidence of content validity and results of a pilot study of the Cognitive Screening Test - Online (TRIACOG-Online) in a clinical sample of patients after stroke. The process comprised four stages: 1) Adaptation of the instructions, stimulus and responses; 2) Seven experts analyzed the equivalence between the previous printed version and the online version; 3) A pilot study was carried out with seven adults who had experienced a stroke in order to check the comprehension and feasibility of the items; and 4) The development of the final version of TRIACOG-Online. Expert validity testing of the questionnaire yielded a content validity index (CVI) of 100% for correspondence and construct in 13 items, and a CVI of 87.71% in four items. In the pilot study, problems related to the internet led to the decision to use a single section form. No difficulties were observed in carrying out the tasks and understanding the instructions. Participants reported being able to adequately visualize the stimuli and remain motivated to complete the tasks presented. It was shown that TRIACOG-Online evaluated the same constructs as the pencil-and-paper version, can be used in remote neuropsychological assessments and face-to-face settings.