Brain microstructure is linked to cognitive fatigue in early multiple sclerosis.

Cognitive fatigue is a major symptom of Multiple Sclerosis (MS), from the early stages of the disease. This study aims to detect if brain microstructure is altered early in the disease course and is associated with cognitive fatigue in people with MS (pwMS) compared to matched healthy controls (HC). Recently diagnosed pwMS (N = 18, age < 45 years old) with either a Relapsing-Remitting or a Clinically Isolated Syndrome course of the disease, and HC (N = 19) matched for sex, age and education were analyzed. Quantitative multiparameter maps (MTsat, PD, R1 and R2*) of pwMS and HC were calculated. Parameters were extracted within the normal appearing white matter, cortical grey matter and deep grey matter (NAWM, NACGM and NADGM, respectively). Bayesian T-test for independent samples assessed between-group differences in brain microstructure while associations between score at a cognitive fatigue scale and each parameter in each tissue class were investigated with Generalized Linear Mixed Models. Patients exhibited lower MTsat and R1 values within NAWM and NACGM, and higher R1 values in NADGM compared to HC. Cognitive fatigue was associated with PD measured in every tissue class and to MTsat in NAWM, regardless of group. Disease-specific negative correlations were found in pwMS in NAWM (R1, R2*) and NACGM (R1). These findings suggest that brain microstructure within normal appearing tissues is already altered in the very early stages of the disease. Moreover, additional microstructure alterations (e.g. diffuse and widespread demyelination or axonal degeneration) in pwMS may lead to disease-specific complaint of cognitive fatigue.

Using quantitative magnetic resonance imaging to track cerebral alterations in multiple sclerosis brain: A longitudinal study.

INTRODUCTION: Quantitative MRI quantifies tissue microstructural properties and supports the characterization of cerebral tissue damages. With an MPM protocol, 4 parameter maps are constructed: MTsat, PD, R1 and R2*, reflecting tissue physical properties associated with iron and myelin contents. Thus, qMRI is a good candidate for in vivo monitoring of cerebral damage and repair mechanisms related to MS. Here, we used qMRI to investigate the longitudinal microstructural changes in MS brain. METHODS: Seventeen MS patients (age 25-65, 11 RRMS) were scanned on a 3T MRI, in two sessions separated with a median of 30 months, and the parameters evolution was evaluated within several tissue classes: NAWM, NACGM and NADGM, as well as focal WM lesions. An individual annual rate of change for each qMRI parameter was computed, and its correlation to clinical status was evaluated. For WM plaques, three areas were defined, and a GLMM tested the effect of area, time points, and their interaction on each median qMRI parameter value. RESULTS: Patients with a better clinical evolution, that is, clinically stable or improving state, showed positive annual rate of change in MTsat and R2* within NAWM and NACGM, suggesting repair mechanisms in terms of increased myelin content and/or axonal density as well as edema/inflammation resorption. When examining WM lesions, qMRI parameters within surrounding NAWM showed microstructural modifications, even before any focal lesion is visible on conventional FLAIR MRI. CONCLUSION: The results illustrate the benefit of multiple qMRI data in monitoring subtle changes within normal appearing brain tissues and plaque dynamics in relation with tissue repair or disease progression.

Pupil response speed as a marker of cognitive fatigue in early Multiple Sclerosis☆.

CONTEXT: Cognitive fatigue (CF) is a disabling symptom frequently reported by patients with Multiple Sclerosis (pwMS). Whether pwMS in the early disease stages present an increased sensitivity to fatigue induction remains debated. Objective measures of CF have been validated neither for clinical nor research purposes. This study aimed at (i) assessing how fatigue induction by manipulation of cognitive load affects subjective fatigue and behavioural performance in newly diagnosed pwMS and matched healthy controls (HC); and (ii) exploring the relevance of eye metrics to describe CF in pwMS. METHODS: Nineteen pwMS with disease duration < 5 years and 19 matched HC participated to this study. CF was induced with a dual-task in two separate sessions with varying cognitive load (High and Low cognitive load conditions, HCL and LCL). Accuracy, reaction times (RTs), subjective fatigue and sleepiness states were assessed. Bayesian Analyses of Variance for repeated measures (rmANOVA) explored the effects of time, group and load condition on the assessed variables. Eye metrics (number of long blinks, pupil size and pupil response speed: PRS) were obtained during the CF task for a sub-sample (16 pwMS and 15 HC) and analysed with Generalized Linear Mixed Models (GLMM). RESULTS: Performance (accuracy and RTs) was lower in the HCL condition and accuracy decreased over time (BFsincl > 100) while RTs did not significantly vary. Performance over task and conditions followed the same pattern of evolution across groups (BFsincl < 0.08) suggesting that pwMS did not show increased alteration of performance during fatigue induction. Regarding subjective state, both fatigue and sleepiness increased following the task (BFsincl > 15), regardless of condition and group (BFsincl < 3). CF in pwMS seems to be associated with PRS, as PRS decreased during the task amongst pwMS only and especially in the HCL condition (all p < .05). A significant Condition*Group interaction was observed regarding long blinks (p < .0001) as well as an expected effect of cognitive load condition on pupil diameter (p < .01). CONCLUSION: These results suggest that newly diagnosed pwMS and HC behave similarly during fatigue induction, in terms of both performance decrement and accrued fatigue sensation. Eye metric data further reveal a susceptibility to CF in pwMS, which can be objectively measured.

Shared event memory in aging: Across-participants similarity of vividness judgements decreases with age.

When they remember the same events, humans recollect common episodic traces. For making vividness judgements, older adults rely less than young adults on retrieved episodic details. Here, we examined the similarity of the subjective experience of remembering and the associated memory content across participants and we investigated age-effects. Young and older adults studied pictures associated with labels. At retrieval, participants judged the vividness of their memories and recalled pictures details. We examined the similarity of vividness judgements and memory recall across-participants. Across-participants similarity in vividness judgements was higher in young than in older adults, while no age-difference in the similarity of the richness of memory recall between participants was found. Together, these findings suggest that older adults' vividness ratings are less similar from one participant to another than those of young adults, which may be explained by how older adults use memory details to frame their sense of memory vividness.

Early brainstem [18F]THK5351 uptake is linked to cortical hyperexcitability in healthy aging.

BACKGROUNDNeuronal hyperexcitability characterizes the early stages of Alzheimer's disease (AD). In animals, early misfolded tau and amyloid-ß (Aß) protein accumulation - both central to AD neuropathology - promote cortical excitability and neuronal network dysfunction. In healthy humans, misfolded tau and Aß aggregates are first detected, respectively, in the brainstem and frontomedial and temporobasal cortices, decades prior to the onset of AD cognitive symptoms. Whether cortical excitability is related to early brainstem tau - and its associated neuroinflammation - and cortical Aß aggregations remains unknown.METHODSWe probed frontal cortex excitability, using transcranial magnetic stimulation combined with electroencephalography, in a sample of 64 healthy late-middle-aged individuals (50-69 years; 45 women and 19 men). We assessed whole-brain [18F]THK5351 PET uptake as a proxy measure of tau/neuroinflammation, and we assessed whole-brain Aß burden with [18F]Flutemetamol or [18F]Florbetapir radiotracers.RESULTSWe found that higher [18F]THK5351 uptake in a brainstem monoaminergic compartment was associated with increased cortical excitability (r = 0.29, P = 0.02). By contrast, [18F]THK5351 PET signal in the hippocampal formation, although strongly correlated with brainstem signal in whole-brain voxel-based quantification analyses (P value corrected for family-wise error [PFWE-corrected] < 0.001), was not significantly associated with cortical excitability (r = 0.14, P = 0.25). Importantly, no significant association was found between early Aß cortical deposits and cortical excitability (r = -0.20, P = 0.11).CONCLUSIONThese findings reveal potential brain substrates for increased cortical excitability in preclinical AD and may constitute functional in vivo correlates of early brainstem tau accumulation and neuroinflammation in humans.TRIAL REGISTRATIONEudraCT 2016-001436-35.FUNDINGF.R.S.-FNRS Belgium, Wallonie-Bruxelles International, ULiège, Fondation Simone et Pierre Clerdent, European Regional Development Fund.

Validation of an Automatic Arousal Detection Algorithm for Whole-Night Sleep EEG Recordings.

Arousals during sleep are transient accelerations of the EEG signal, considered to reflect sleep perturbations associated with poorer sleep quality. They are typically detected by visual inspection, which is time consuming, subjective, and prevents good comparability across scorers, studies and research centres. We developed a fully automatic algorithm which aims at detecting artefact and arousal events in whole-night EEG recordings, based on time-frequency analysis with adapted thresholds derived from individual data. We ran an automated detection of arousals over 35 sleep EEG recordings in healthy young and older individuals and compared it against human visual detection from two research centres with the aim to evaluate the algorithm performance. Comparison across human scorers revealed a high variability in the number of detected arousals, which was always lower than the number detected automatically. Despite indexing more events, automatic detection showed high agreement with human detection as reflected by its correlation with human raters and very good Cohen's kappa values. Finally, the sex of participants and sleep stage did not influence performance, while age may impact automatic detection, depending on the human rater considered as gold standard. We propose our freely available algorithm as a reliable and time-sparing alternative to visual detection of arousals.