75 research outputs found

    Localization of brain networks engaged by the sustained attention to response task provides quantitative markers of executive impairment in amyotrophic lateral sclerosis

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    Objective: To identify cortical regions engaged during the sustained attention to response task (SART) and characterize changes in their activity associated with the neurodegenerative condition amyotrophic lateral sclerosis (ALS). Methods: High-density electroencephalography (EEG) was recorded from 33 controls and 23 ALS patients during a SART paradigm. Differences in associated event-related potential peaks were measured for Go and NoGo trials. Sources active during these peaks were localized, and ALS-associated differences were quantified. Results: Go and NoGo N2 and P3 peak sources were localized to the left primary motor cortex, bilateral dorsolateral prefrontal cortex (DLPFC), and lateral posterior parietal cortex (PPC). NoGo trials evoked greater bilateral medial PPC activity during N2 and lesser left insular, PPC and DLPFC activity during P3. Widespread cortical hyperactivity was identified in ALS during P3. Changes in the inferior parietal lobule and insular activity provided very good discrimination (AUROC > 0.75) between patients and controls. Activation of the right precuneus during P3 related to greater executive function in ALS, indicative of a compensatory role. Interpretation: The SART engages numerous frontal and parietal cortical structures. SART–EEG measures correlate with specific cognitive impairments that can be localized to specific structures, aiding in differential diagnosis

    Cognitive network hyperactivation and motor cortex decline correlate with ALS prognosis

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    We aimed to quantitatively characterize progressive brain network disruption in Amyotrophic Lateral Sclerosis (ALS) during cognition using the mismatch negativity (MMN), an electrophysiological index of attention switching. We measured the MMN using 128-channel EEG longitudinally (2–5 timepoints) in 60 ALS patients and cross-sectionally in 62 healthy controls. Using dipole fitting and linearly constrained minimum variance beamforming we investigated cortical source activity changes over time. In ALS, the inferior frontal gyri (IFG) show significantly lower baseline activity compared to controls. The right IFG and both superior temporal gyri (STG) become progressively hyperactive longitudinally. By contrast, the left motor and dorsolateral prefrontal cortices are initially hyperactive, declining progressively. Baseline motor hyperactivity correlates with cognitive disinhibition, and lower baseline IFG activities correlate with motor decline rate, while left dorsolateral prefrontal activity predicted cognitive and behavioural impairment. Shorter survival correlates with reduced baseline IFG and STG activity and later STG hyperactivation. Source-resolved EEG facilitates quantitative characterization of symptom-associated and symptom-preceding motor and cognitive-behavioral cortical network decline in ALS

    Assessing behavioural changes in ALS: cross-validation of ALS-specific measures

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    Objective: The Beaumont Behavioural Inventory (BBI) is a behavioural proxy report for the assessment of behavioural changes in ALS. This tool has been validated against the FrSBe, a non-ALS specific behavioural assessment, and further comparison of the BBI against a disease-specific tool was considered. This study cross-validates the BBI against the ALS-FTD-Q. Methods: 60 ALS patients, 8% also meeting criteria for FTD, were recruited. All patients were evaluated using the BBI and the ALS-FTD-Q, completed by a carer. Correlational analysis was performed to assess construct validity. Precision, sensitivity, specificity and overall accuracy of the BBI, when compared to the ALS-FTD-Q, were obtained. Results: The mean score of the whole sample on the BBI was 11.45±13.06. ALS-FTD patients scored significantly higher than non-demented ALS patients (31.6±14.64, 9.62±11.38; p<.0001). A significant large positive correlation between the BBI and the ALS-FTD-Q was observed (r=.807, p<.0001), and no significant correlations between the BBI and other clinical/demographic characteristics, indicating good convergent and discriminant validity, respectively. 72% of overall concordance was observed. Precision, sensitivity and specificity for the classification of severely impaired patients were adequate. However, lower concordance in the classification of mild behavioural changes was observed, with higher sensitivity using the BBI, most likely secondary to BBI items which endorsed behavioural aspects not measured by the ALS-FTD-Q. Discussion: Good construct validity has been further confirmed when the BBI is compared to an ALS-specific tool. Furthermore, the BBI is a more comprehensive behavioural assessment for ALS, as it measures the whole behavioural spectrum in this condition

    StrokeCog Markov Model Projected Prevalent and Incident Cases of Stroke and Poststroke Cognitive Impairment to 2035 in Ireland

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    Background and Purpose: Cognitive impairment no dementia (CIND) and dementia are common stroke outcomes, with significant health and societal implications for aging populations. These outcomes are not included in current epidemiological models. We aimed to develop an epidemiological model to project incidence and prevalence of stroke, poststroke CIND and dementia, and life expectancy, in Ireland to 2035, informing policy and service planning. Methods: We developed a probabilistic Markov model (the StrokeCog model) applied to the Irish population aged 40 to 89 years to 2035. Data sources included official population and hospital-episode statistics, longitudinal cohort studies, and published estimates. Key assumptions were varied in sensitivity analysis. Results were externally validated against independent sources. The model tracks poststroke progression into health states characterized by no cognitive impairment, CIND, dementia, disability, stroke recurrence, and death. Results: We projected 69 051 people with prevalent stroke in Ireland in 2035 (22.0 per 1000 population [95% CI, 20.8-23.1]), with 25 274 (8.0 per 1000 population [95% CI, 7.1-9.0]) of those projected to have poststroke CIND, and 12 442 having poststroke dementia (4.0 per 1000 population [95% CI, 3.2-4.8]). We projected 8725 annual incident strokes in 2035 (2.8 per 1000 population [95% CI, 2.7-2.9]), with 3832 of these having CIND (1.2 per 1000 population [95% CI, 1.1-1.3]), and 1715 with dementia (0.5 per 1000 population [95% CI, 0.5-0.6]). Life expectancy for stroke survivors at age 50 was 23.4 years (95% CI, 22.3-24.5) for women and 20.7 (95% CI, 19.5-21.9) for men. Conclusions: This novel epidemiological model of stroke, poststroke CIND, and dementia draws on the best available evidence. Sensitivity analysis indicated that findings were robust to assumptions, and where there was uncertainty a conservative approach was taken. The StrokeCog model is a useful tool for service planning and cost-effectiveness analysis and is available for adaptation to other national contexts.Peer reviewe

    Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis

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    Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome. We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γl-band synchrony) and frontoparietal (γl-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome. Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption

    Dynamic Blood-Brain Barrier Regulation in Mild Traumatic Brain Injury

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    Whereas the diagnosis of moderate and severe traumatic brain injury (TBI) is readily visible on current medical imaging paradigms (magnetic resonance imaging [MRI] and computed tomography [CT] scanning), a far greater challenge is associated with the diagnosis and subsequent management of mild TBI (mTBI), especially concussion which, by definition, is characterized by a normal CT. To investigate whether the integrity of the blood-brain barrier (BBB) is altered in a high-risk population for concussions, we studied professional mixed martial arts (MMA) fighters and adolescent rugby players. Additionally, we performed the linear regression between the BBB disruption defined by increased gadolinium contrast extravasation on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on MRI and multiple biomechanical parameters indicating the severity of impacts recorded using instrumented mouthguards in professional MMA fighters. MMA fighters were examined pre-fight for a baseline and again within 120 h post-competitive fight, whereas rugby players were examined pre-season and again post-season or post-match in a subset of cases. DCE-MRI, serological analysis of BBB biomarkers, and an analysis of instrumented mouthguard data, was performed. Here, we provide pilot data that demonstrate disruption of the BBB in both professional MMA fighters and rugby players, dependent on the level of exposure. Our data suggest that biomechanical forces in professional MMA and adolescent rugby can lead to BBB disruption. These changes on imaging may serve as a biomarker of exposure of the brain to repetitive subconcussive forces and mTBI

    Measuring reliable change in cognition using the Edinburgh Cognitive and Behavioural ALS Screen (ECAS)

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    doi:https://doi.org/10.1080/21678421.2017.1407794Background: Cognitive impairment affects approximately 50% of people with amyotrophic lateral sclerosis (ALS). Research has indicated that impairment may worsen with disease progression. The Edinburgh Cognitive and Behavioural ALS Screen (ECAS) was designed to measure neuropsychological functioning in ALS, with its alternate forms (ECAS-A, B, and C) allowing for serial assessment over time. Objective: The aim of the present study was to establish reliable change scores for the alternate forms of the ECAS, and to explore practice effects and test-retest reliability of the ECAS?s alternate forms. Method: Eighty healthy participants were recruited, with 57 completing two and 51 completing three assessments. Participants were administered alternate versions of the ECAS serially (A-B-C) at four-month intervals. Intra-class correlation analysis was employed to explore test-retest reliability, while analysis of variance was used to examine the presence of practice effects. Reliable change indices (RCI) and regression-based methods were utilized to establish change scores for the ECAS alternate forms. Results: Test-retest reliability was excellent for ALS Specific, ALS Non-Specific, and ECAS Total scores of the combined ECAS A, B, and C (all?>?.90). No significant practice effects were observed over the three testing sessions. RCI and regression-based methods produced similar change scores. Conclusion: The alternate forms of the ECAS possess excellent test-retest reliability in a healthy control sample, with no significant practice effects. The use of conservative RCI scores is recommended. Therefore, a change of ?8, ?4, and ?9 for ALS Specific, ALS Non-Specific, and ECAS Total score is required for reliable chang
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