127 research outputs found

    Rule violation errors are associated with right lateral prefrontal cortex atrophy in neurodegenerative disease

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    Good cognitive performance requires adherence to rules specific to the task at hand. Patients with neurological disease often make rule violation errors, but the anatomical basis for rule violation during cognitive testing remains debated. The current study examined the neuroanatomical correlates of rule violation (RV) errors made on tests of executive functioning in 166 subjects diagnosed with neurodegenerative disease or as neurologically healthy. Specifically, RV errors were voxel-wisely correlated with gray matter volume derived from high-definition MR images using voxel-based morphometry implemented in SPM2. Latent variable analysis showed that rule violation errors tapped a unitary construct separate from repetition errors. This analysis was used to generate factor scores to represent what is common among rule violation errors across tests. The extracted rule violation factor scores correlated with tissue loss in the lateral middle and inferior frontal gyri and the caudate nucleus bilaterally. When a more stringent control for global cognitive functioning was applied using Mini Mental State Exam scores, only the correlations with the right lateral prefrontal cortex remained significant. These data underscore the importance of right lateral prefrontal cortex in behavioral monitoring and highlight the potential of rule violation error assessment for identifying patients with damage to this region

    Cultural adaptation of the brain health assessment for early detection of cognitive impairment in Southeast Nigeria.

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    OBJECTIVE: The aging population in developing countries demands parallel improvements in brain health assessment services to mitigate stigma, promote healthy aging, and diagnose cognitive impairments including dementia in primary health care (PHC) facilities. The lack of culturally appropriate cognitive assessment tools in PHC facilities delays early detection. This study aims to culturally adapt a brief digital cognitive assessment tool for PHC professionals in Southeast Nigeria. METHOD: A total of 30 participants (15 healthcare workers HCW and 15 community members) were selected to be culturally representative of the community. We completed focus groups and pilot testing to evaluate and refine the Brain Health Assessment (BHA) a subset of tools from the Tablet-based Cognitive Assessment Tool (TabCAT) known to be sensitive to cognitive impairment in other settings. We examined BHA subtests across local languages (Pidgin and Igbo) spoken at two geriatric clinics in Anambra State Southeast Nigeria. RESULTS: Following structured approaches in focus groups, adaptations were made to the Favorites (memory) and Line Length (visuospatial) subtests based on their input. Participants found the new adaptations to have good construct validity for the region. CONCLUSIONS: The BHA subtests showed content validity for future work needed to validate the tool for detecting early cognitive changes associated with dementia and Alzheimers disease in PHC settings. The use of culturally adapted and concise digital cognitive assessment tools relevant to healthcare professionals in Southeast Nigerias PHCs is advocated

    Visuospatial Functioning In The Primary Progressive Aphasias

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    Objectives: The aim of this study was to identify whether the three main primary progressive aphasia (PPA) variants would show differential profiles on measures of visuospatial cognition. We hypothesized that the logopenic variant would have the most difficulty across tasks requiring visuospatial and visual memory abilities. Methods: PPA patients (n = 156), diagnosed using current criteria, and controls were tested on a battery of tests tapping different aspects of visuospatial cognition. We compared the groups on an overall visuospatial factor; construction, immediate recall, delayed recall, and executive functioning composites; and on individual tests. Cross-sectional and longitudinal comparisons were made, adjusted for disease severity, age, and education. Results: The logopenic variant had significantly lower scores on the visuospatial factor and the most impaired scores on all composites. The nonfluent variant had significant difficulty on all visuospatial composites except the delayed recall, which differentiated them from the logopenic variant. In contrast, the semantic variants performed poorly only on delayed recall of visual information. The logopenic and nonfluent variants showed decline in figure copying performance over time, whereas in the semantic variant, this skill was remarkably preserved. Conclusions: This extensive examination of performance on visuospatial tasks in the PPA variants solidifies some previous findings, for example, delayed recall of visual stimuli adds value in differential diagnosis between logopenic variant PPA and nonfluent variant PPA variants, and illuminates the possibility of common mechanisms that underlie both linguistic and non-linguistic deficits in the variants. Furthermore, this is the first study that has investigated visuospatial functioning over time in the PPA variants

    Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA

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    Non-fluent/agrammatic primary progressive aphasia (nfvPPA) is caused by neuro-degeneration within the left fronto-insular speech and language production network (SPN). Graph theory is a branch of mathematics that studies network architecture (topology) by quantifying features based on its elements (nodes and connections). This approach has been recently applied to neuroimaging data to explore the complex architecture of the brain connectome, though few studies have exploited this technique in PPA. Here, we used graph theory on functional MRI resting state data from a group of 20 nfvPPA patients and 20 matched controls to investigate topological changes in response to focal neuro-degeneration. We hypothesized that changes in the network architecture would be specific to the affected SPN in nfvPPA, while preserved in the spared default mode network (DMN). Topological configuration was quantified by hub location and global network metrics. Our findings showed a less efficiently wired and less optimally clustered SPN, while no changes were detected in the DMN. The SPN in the nfvPPA group showed a loss of hubs in the left fronto-parietal-temporal area and new critical nodes in the anterior left inferior-frontal and right frontal regions. Behaviorally, speech production score and rule violation errors correlated with the strength of functional connectivity of the left (lost) and right (new) regions respectively. This study shows that focal neurodegeneration within the SPN in nfvPPA is associated with network-specific topological alterations, with the loss and gain of crucial hubs and decreased global efficiency that were better accounted for through functional rather than structural changes. These findings support the hypothesis of selective network vulnerability in nfvPPA and may offer biomarkers for future behavioral intervention

    Brain clocks capture diversity and disparities in aging and dementia

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    Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.</p
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