Stimulus-related modulation in the 1/f spectral slope suggests an impaired inhibition during a working memory task in people with multiple sclerosis.

BACKGROUND: An imbalance of excitatory and inhibitory synaptic transmission in multiple sclerosis (MS) may lead to cognitive impairment, such as impaired working memory. The 1/f slope of electroencephalography/magnetoencephalography (EEG/MEG) power spectra is shown to be a non-invasive proxy of excitation/inhibition balance. A flatter slope is associated with higher excitation/lower inhibition. OBJECTIVES: To assess the 1/f slope modulation induced by stimulus and its association with behavioral and cognitive measures. METHODS: We analyzed MEG recordings of 38 healthy controls (HCs) and 79 people with multiple sclerosis (pwMS) while performing an n-back task including target and distractor stimuli. Target trials require an answer, while distractor trials do not. We computed the 1/f spectral slope through the fitting oscillations and one over f (FOOOF) algorithm within the time windows 1 second before and after each stimulus presentation. RESULTS: We observed a flatter 1/f slope after distractor stimuli in pwMS compared to HCs. The 1/f slope was significantly steeper after stimulus for both HCs and pwMS and was significantly correlated with reaction times. This modulation in 1/f slope was significantly correlated with visuospatial memory assessed by the BVMT-R test. CONCLUSION: Our results suggest possible inhibitory mechanism deficits in pwMS during a working memory task.

The Finger Dexterity Test: Validation study of a smartphone-based manual dexterity assessment.

BACKGROUND: The Nine-Hole Peg Test (9HPT) is the golden standard to measure manual dexterity in people with multiple sclerosis (MS). However, administration requires trained personnel and dedicated time during a clinical visit. OBJECTIVES: The objective of this study is to validate a smartphone-based test for remote manual dexterity assessment, the icompanion Finger Dexterity Test (FDT), to be included into the icompanion application. METHODS: A total of 65 MS and 81 healthy subjects were tested, and 20 healthy subjects were retested 2 weeks later. RESULTS: The FDT significantly correlated with the 9HPT (dominant: ρ = 0.62, p < 0.001; non-dominant: ρ = 0.52, p < 0.001). MS subjects had significantly higher FDT scores than healthy subjects (dominant: p = 0.015; non-dominant: p = 0.013), which was not the case for the 9HPT. A significant correlation with age (dominant: ρ = 0.46, p < 0.001; non-dominant: ρ = 0.40, p = 0.002), Expanded Disability Status Scale (EDSS, dominant: ρ = 0.36, p = 0.005; non-dominant: ρ = 0.31, p = 0.024), and disease duration for the non-dominant hand (ρ = 0.31, p = 0.016) was observed. There was a good test-retest reliability in healthy subjects (dominant: r = 0.69, p = 0.001; non-dominant: r = 0.87, p < 0.001). CONCLUSIONS: The icompanion FDT shows a moderate-to-good concurrent validity and test-retest reliability, differentiates between the MS subjects and healthy controls, and correlates with clinical parameters. This test can be implemented into routine MS care for remote follow-up of manual dexterity.

Clinical effectiveness of coronavirus disease 2019 vaccination in patients with multiple sclerosis stratified by disease-modifying treatment.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) vaccination has been associated with a dampened humoral and/or cellular immune response in patients with multiple sclerosis (MS) who were concurrently on disease-modifying treatment (DMT) with B-cell depleting agents or sphingosine-1-phosphate receptor modulators (S1PRMs). Our main goal was to investigate the impact of these DMT classes on the clinical effectiveness of COVID-19 vaccination. METHODS: Since March 2020, demographics and clinical data of patients with MS who developed COVID-19 have been collected at the Belgian National MS Centre in Melsbroek. Patients were considered to be 'protected by vaccination' if they were (i) fully vaccinated and (ii) tested positive for COVID-19 in the period ranging from 14 days to 6 months after the last administered vaccine. RESULTS: On 19 December 2022, 418 COVID-19 cases were retrospectively identified in 389 individual patients. Hospitalization and mortality rates resulting from the infection were 10.8% and 2.4%, respectively. Being 'unprotected by vaccination' was significantly associated with a worse COVID-19 outcome (i.e., hospitalization and/or death) in the total cohort (N = 418, odds ratio [OR] 3.96), in patients on ongoing DMT other than anti-CD20 agents or S1PRMs (N = 123, OR 31.75) and in patients without DMT (N = 182, OR 5.60), but not in those receiving anti-CD20 agents (N = 91, OR 0.39); the S1PRMs subgroup was considered too small (22 infections) for any meaningful analysis. CONCLUSIONS: Coronavirus disease 2019 vaccination protects against severe infection in patients with MS but it was not possible to confirm this effect in those on DMT with B-cell depleting agents.

Neurophysiological avenues to better conceptualizing adaptive cognition.

We delve into the human brain's remarkable capacity for adaptability and sustained cognitive functioning, phenomena traditionally encompassed as executive functions or cognitive control. The neural underpinnings that enable the seamless navigation between transient thoughts without detracting from overarching goals form the core of our article. We discuss the concept of "metacontrol," which builds upon conventional cognitive control theories by proposing a dynamic balancing of processes depending on situational demands. We critically discuss the role of oscillatory processes in electrophysiological activity at different scales and the importance of desynchronization and partial phase synchronization in supporting adaptive behavior including neural noise accounts, transient dynamics, phase-based measures (coordination dynamics) and neural mass modelling. The cognitive processes focused and neurophysiological avenues outlined are integral to understanding diverse psychiatric disorders thereby contributing to a more nuanced comprehension of cognitive control and its neural bases in both health and disease.

Electrophysiological impact of mental fatigue on brain activity during a bike task: A wavelet analysis approach.

This study explored how mental fatigue affects brain activity during a low-intensity bike task utilising a continuous wavelet transformation in electroencephalography (EEG) analysis. The aim was to examine changes in brain activity potentially linked to central motor commands and to investigate their relationship with ratings of perceived exertion (RPE). In this study, sixteen participants (age: 21 ± 6 y, 7 females, 9 males) underwent one familiarization and two experimental trials in a randomised, blinded, cross-over study design. Participants executed a low-intensity bike task (9 min; 45 rpm; intensity (W): 10 % below aerobic threshold) after performing a mentally fatiguing (individualized 60-min Stroop task) or a control (documentary) task. Physiological (heart rate, EEG) and subjective measures (self-reported feeling of mental fatigue, RPE, cognitive load, motivation) were assessed prior, during and after the bike task. Post-Stroop, self-reported feeling of mental fatigue was higher in the intervention group (EXP) (74 ± 16) than in the control group (CON) (37 ± 17; p < 0.001). No significant differences in RPE during the bike task were observed between conditions. EEG analysis revealed significant differences (p < 0.05) in beta frequency (13-30 Hz) during the bike task, with EXP exhibiting more desynchronization during the pedal push phase and synchronization during the pedal release phase. These results suggest that mental fatigue, confirmed by both subjective and neurophysiological markers, did not significantly impact RPE during the bike task, possibly due to the use of the CR100 scale or absence of a performance outcome. However, EEG data did reveal significant beta band alterations during the task, indicating increased neural effort under mental fatigue. These findings reveal, for the first time, how motor-related brain activity at the motor cortex is impacted during a low-intensity bike task when mentally fatigued.

Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease.

Alzheimer's Disease (AD) is the leading cause of dementia. It results in cortical thickness changes and is associated with a decline in cognition and behaviour. Such decline affects multiple important day-to-day functions, including memory, language, orientation, judgment and problem-solving. Recent research has made important progress in identifying brain regions associated with single outcomes, such as individual AD status and general cognitive decline. The complex projection from multiple brain areas to multiple AD outcomes, however, remains poorly understood. This makes the assessment and especially the prediction of multiple AD outcomes - each of which may unveil an integral yet different aspect of the disease - challenging, particularly when some are not strongly correlated. Here, uniting residual learning, partial least squares (PLS), and predictive modelling, we develop an explainable, generalisable, and reproducible method called the Residual Partial Least Squares Learning (the re-PLS Learning) to (1) chart the pathways between large-scale multivariate brain cortical thickness data (inputs) and multivariate disease and behaviour data (outcomes); (2) simultaneously predict multiple, non-pairwise-correlated outcomes; (3) control for confounding variables (e.g., age and gender) affecting both inputs and outcomes and the pathways in-between; (4) perform longitudinal AD disease status classification and disease severity prediction. We evaluate the performance of the proposed method against a variety of alternatives on data from AD patients, subjects with mild cognitive impairment (MCI), and cognitively normal individuals (n=1,196) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results unveil pockets of brain areas in the temporal, frontal, sensorimotor, and cingulate areas whose cortical thickness may be respectively associated with declines in different cognitive and behavioural subdomains in AD. Finally, we characterise re-PLS' geometric interpretation and mathematical support for delivering meaningful neurobiological insights and provide an open software package (re-PLS) available at https://github.com/thanhvd18/rePLS.

Brain age as a biomarker for pathological versus healthy ageing - a REMEMBER study.

OBJECTIVES: This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions. METHODS: The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict 'brain age' and 'brain predicted age difference' (BPAD = brain age-chronological age) for every subject. RESULTS: MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p < .001) and BPAD (r = -0.26,p < .001). Noticeable trends, but no significant correlations, were found between BPAD and incidence of conversion from MCI to ADD, nor between BPAD and conversion time from MCI to ADD. BPAD was increased in heavy alcohol drinkers compared to non-/sporadic (p = .014) and moderate (p = .040) drinkers. CONCLUSIONS: Brain age and associated BPAD have the potential to serve as indicators for, and to evaluate the impact of lifestyle modifications or interventions on, brain health.

Subclinical epileptiform activity in the Alzheimer continuum: association with disease, cognition and detection method.

BACKGROUND: Epileptic seizures are an established comorbidity of Alzheimer's disease (AD). Subclinical epileptiform activity (SEA) as detected by 24-h electroencephalography (EEG) or magneto-encephalography (MEG) has been reported in temporal regions of clinically diagnosed AD patients. Although epileptic activity in AD probably arises in the mesial temporal lobe, electrical activity within this region might not propagate to EEG scalp electrodes and could remain undetected by standard EEG. However, SEA might lead to faster cognitive decline in AD. AIMS: 1. To estimate the prevalence of SEA and interictal epileptic discharges (IEDs) in a well-defined cohort of participants belonging to the AD continuum, including preclinical AD subjects, as compared with cognitively healthy controls. 2. To evaluate whether long-term-EEG (LTM-EEG), high-density-EEG (hd-EEG) or MEG is superior to detect SEA in AD. 3. To characterise AD patients with SEA based on clinical, neuropsychological and neuroimaging parameters. METHODS: Subjects (n = 49) belonging to the AD continuum were diagnosed according to the 2011 NIA-AA research criteria, with a high likelihood of underlying AD pathophysiology. Healthy volunteers (n = 24) scored normal on neuropsychological testing and were amyloid negative. None of the participants experienced a seizure before. Subjects underwent LTM-EEG and/or 50-min MEG and/or 50-min hd-EEG to detect IEDs. RESULTS: We found an increased prevalence of SEA in AD subjects (31%) as compared to controls (8%) (p = 0.041; Fisher's exact test), with increasing prevalence over the disease course (50% in dementia, 27% in MCI and 25% in preclinical AD). Although MEG (25%) did not withhold a higher prevalence of SEA in AD as compared to LTM-EEG (19%) and hd-EEG (19%), MEG was significantly superior to detect spikes per 50 min (p = 0.002; Kruskall-Wallis test). AD patients with SEA scored worse on the RBANS visuospatial and attention subset (p = 0.009 and p = 0.05, respectively; Mann-Whitney U test) and had higher left frontal, (left) temporal and (left and right) entorhinal cortex volumes than those without. CONCLUSION: We confirmed that SEA is increased in the AD continuum as compared to controls, with increasing prevalence with AD disease stage. In AD patients, SEA is associated with more severe visuospatial and attention deficits and with increased left frontal, (left) temporal and entorhinal cortex volumes. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04131491. 12/02/2020.

The roles, challenges, and merits of the p value.

Since the 18th century, the p value has been an important part of hypothesis-based scientific investigation. As statistical and data science engines accelerate, questions emerge: to what extent are scientific discoveries based on p values reliable and reproducible? Should one adjust the significance level or find alternatives for the p value? Inspired by these questions and everlasting attempts to address them, here, we provide a systematic examination of the p value from its roles and merits to its misuses and misinterpretations. For the latter, we summarize modest recommendations to handle them. In parallel, we present the Bayesian alternatives for seeking evidence and discuss the pooling of p values from multiple studies and datasets. Overall, we argue that the p value and hypothesis testing form a useful probabilistic decision-making mechanism, facilitating causal inference, feature selection, and predictive modeling, but that the interpretation of the p value must be contextual, considering the scientific question, experimental design, and statistical principles.