Distinctive Pattern of Cognitive Disorders During Multiple Sclerosis Relapse and Recovery Based on Computerized CANTAB Tests

Human energetic stress associated with upregulation of spatial cognition

OBJECTIVES

Evolutionary life history theory has a unique potential to shed light on human adaptive capabilities. Ultra-endurance challenges are a valuable experimental model allowing the direct testing of phenotypic plasticity via physiological trade-offs in resource allocation. This enhances our understanding of how the body prioritizes different functions when energetically stressed. However, despite the central role played by the brain in both hominin evolution and metabolic budgeting, cognitive plasticity during energetic deficit remains unstudied.

MATERIALS

We considered human cognitive plasticity under conditions of energetic deficit by evaluating variability in performance in three key cognitive domains. To achieve this, cognitive performance in a sample of 48 athletes (m = 29, f = 19) was assessed before and after competing in multiday ultramarathons.

RESULTS

We demonstrate that under conditions of energetic deficit, performance in tasks of spatial working memory (which assessed ability to store location information, promoting landscape navigation and facilitating resource location and calorie acquisition) increased. In contrast, psychomotor speed (reaction time) remained unchanged and episodic memory performance (ability to recall information about specific events) decreased.

DISCUSSION

We propose that prioritization of spatial working memory performance during conditions of negative energy balance represents an adaptive response due to its role in facilitating calorie acquisition. We discuss these results with reference to a human evolutionary trajectory centred around encephalisation. Encephalisation affords great plasticity, facilitating rapid responses tailored to specific environmental conditions, and allowing humans to increase their capabilities as a phenotypically plastic species.

The effect of age-related macular degeneration on cognitive test performance

The reliable assessment of cognitive functioning is critical to the study of brain-behaviour relationships. Yet conditions that are synchronous which ageing, including visual decline, are easily overlooked when interpreting cognitive test scores. The purpose of this study was to demonstrate the negative consequences of visual impairments on cognitive tests performance. Moderate to severe levels of age-related macular degeneration were simulated, with a set of goggles, in a sample of twenty-four normally sighted participants while they completed two cognitive tasks: a vision-dependent reaction time task and a vision-independent verbal fluency test. Performance on the reaction time task significantly decreased (p < 0.001) in the simulated age-related macular degeneration condition, by as much as 25 percentile ranks. In contrast, performance on the verbal fluency test were not statistically different between the simulated and normal vision conditions (p = 0.78). The findings highlight the importance of considering visual functioning when assessing cognitive function. When vision is not accounted for, low test scores may inaccurately indicate poor cognition. Such false attributions may have significant ramification for diagnosis and research on cognitive functioning.

Feasibility and Validity of Cambridge Neuropsychological Test Automated Battery in Mild Cognitive Impairment Screening for Patients with Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is associated with the worsening of cognitive function. Strategies that are both convenient and reliable for cognitive screening of AF patients remain underdeveloped. We aimed to analyze the sensitivity and specificity of computerized cognitive screening strategies using subtests from Cambridge Neuropsychological Test Automated Battery (CANTAB) in AF patients.

METHODS

The Multitasking Test (MTT), Rapid Visual Information Processing (RVP), and Paired Associates Learning (PAL) subtests from CANTAB were performed in 105 AF patients. Traditional standard neuropsychological tests were used as a reference standard. Cognitive screening models using different CANTAB subtests were established using multivariable logistic regression. Further stepwise regression using the Akaike Information Criterion (AIC) was applied to optimize the models. Receiver operating characteristic curve analyses were used to study the sensitivity and specificity of these models.

RESULTS

Fifty-eight (55%) patients were diagnosed with mild cognitive impairment (MCI). MTT alone had reasonable sensitivity (82.8%) and specificity (74.5%) for MCI screening, while RVP (sensitivity 72.4%, specificity 70.2%) and PAL (sensitivity 70.7%, specificity 57.4%) were less effective. Stepwise regression of all available variables revealed that a combination of MTT and RVP brought about higher specificity (sensitivity 82.8%, specificity 85.8%), while PAL was not included in the optimal model. Moreover, adding education to the models did not result in improved validity for MCI screening.

CONCLUSION

The CANTAB subtests are feasible and effective strategies for MCI screening among AF patients independent of patients' education levels. Hence, they are practical for cardiologists or general practitioners.

Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review

OBJECTIVES

Persons with multiple sclerosis (MS) can face a number of potential healthcare-related barriers, for which mobile health (mHealth) technology can be potentially beneficial. This review aimed to understand the frequency, current uses, and potential barriers with mHealth usage among persons with MS.

METHODS

A query string was used to identify articles on PubMed, MEDLINE, CINAHL, and IEEE Xplore that were published in English between January 2010 and December 2019. Abstracts were reviewed and selected based on a priori inclusion and exclusion criteria. Fifty-nine peer-reviewed research studies related to the study questions are summarized.

RESULTS

The majority of persons with MS were reported as using smartphones, although rates of mHealth utilization varied widely. mHealth usage was grouped into 3 broad categories: (1) disability and symptom measurement; (2) interventions and symptom management; and (3) tracking and promoting adherence. While there have been an increasing number of mHealth options, certain limitations associated with MS (eg, poor dexterity, memory problems) may affect usage, although including persons with MS in the design process can address some of these issues.

DISCUSSION

Given the increased attention to mHealth in this population and the current need for telehealth and at home devices, it is important that persons with MS and healthcare providers are involved in the development of new mHealth tools to ensure that the end product meets their needs. Considerations for addressing the potential mHealth use barriers in persons with MS are discussed.

Neurocognitive impairment and social cognition in multiple sclerosis

PURPOSE/AIM OF THE STUDY

The impairment of neurocognitive functions occurs in all subtypes of multiple sclerosis, even from the earliest stages of the disease. Commonly reported manifestations of cognitive impairment include deficits in attention, conceptual reasoning, processing efficiency, information processing speed, memory (episodic and working), verbal fluency (language), and executive functions. Multiple sclerosis patients also suffer from social cognition impairment, which affects their social functioning. The objective of the current paper is to assess the effect of neurocognitive impairment and its potential correlation with social cognition performance and impairment in multiple sclerosis patients.

MATERIALS AND METHODS

An overview of the available-to-date literature on neurocognitive impairment and social cognition performance in multiple sclerosis patients by disease subtype was performed.

RESULTS

It is not clear if social cognition impairment occurs independently or secondarily to neurocognitive impairment. There are associations of variable strengths between neurocognitive and social cognition deficits and their neural basis is increasingly investigated.

CONCLUSIONS

The prompt detection of neurocognitive predictors of social cognition impairment that may be applicable to all multiple sclerosis subtypes and intervention are crucial to prevent further neural and social cognition decline in multiple sclerosis patients.

Quantifying cognition and fatigue to enhance the sensitivity of the EDSS during relapses

BACKGROUND

Cognition is affected by relapses in persons with multiple sclerosis (PwMS), yet the Expanded Disability Status Scale (EDSS) does not readily detect cognitive changes.

OBJECTIVE

The objective of this study is to improve the detection of cognitive decline during relapses, by incorporating the Symbol Digit Modalities Test (SDMT) into the cerebral Functional System Score (CFSS) of the EDSS.

METHODS

This prospective study recruited PwMS from three dedicated MS centers. All subjects had EDSS, SDMT, and Fatigue Severity Scale (FSS) administered. Subjects experiencing a relapse were assigned to the relapse group (RG). Matched controls from the larger cohort were assigned to the stable group (SG). RG and SG subjects underwent the same evaluation at relapse and 3 months later. Our main outcomes were a modified CFSS (m-CFSS) and modified EDSS (m-EDSS), incorporating SDMT and FSS, accounting for cognitive performance and fatigue rating, during relapse.

RESULTS

The full cohort included 592 subjects; 80 qualified for RG and 72 were matched to the SG. The m-CFSS was significantly higher than CFSS at baseline (median = 2 vs. median = 0, p < 0.001) and relapse (median = 2 vs. median = 1, p < 0.001). The m-EDSS was higher than EDSS (median 3.0 vs. 2.5, p = 0.02) at relapse, where 35 RG subjects (43.8%) had higher m-EDSS than EDSS at relapse.

CONCLUSION

This study demonstrates that incorporating the SDMT and FSS improves the accuracy of the EDSS, by accounting for cognitive changes, during relapse activity.

Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues

Multiple sclerosis is a chronic, demyelinating disease of the CNS. Cognitive impairment is a sometimes neglected, yet common, sign and symptom with a profound effect on instrumental activities of daily living. The prevalence of cognitive impairment in multiple sclerosis varies across the lifespan and might be difficult to distinguish from other causes in older age. MRI studies show that widespread changes to brain networks contribute to cognitive dysfunction, and grey matter atrophy is an early sign of potential future cognitive decline. Neuropsychological research suggests that cognitive processing speed and episodic memory are the most frequently affected cognitive domains. Narrowing evaluation to these core areas permits brief, routine assessment in the clinical setting. Owing to its brevity, reliability, and sensitivity, the Symbol Digit Modalities Test, or its computer-based analogues, can be used to monitor episodes of acute disease activity. The Symbol Digit Modalities Test can also be used in clinical trials, and data increasingly show that cognitive processing speed and memory are amenable to cognitive training interventions.

A Computerized Assessment of Verbal and Visuospatial Memory (Dys)functions in Patients with Rheumatoid Arthritis

Purpose

Rheumatoid arthritis (RA) is a chronic inflammatory systemic disease associated with various degrees of impairment across different cognitive domains. We aimed to provide a detailed computerized investigation of verbal and visuospatial short-term and working memory (dys)functions in RA patients, assessing both accuracy and response speed, while relating them to age, disease-related activity, affective problems, psychomotor speed and other clinical parameters.

Patients and Methods

The study included 29 RA patients (mean age 50.6 ± 12.3 years, 79% female) and 30 controls (matched according to age, gender and education), assessed with short-term and working memory tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB) and the Automated Working Memory Assessment (AWMA).

Results

RA patients were significantly slower on the basic processing speed test (Motor Screening Test, p =0.003). Their short-term information storage (verbal and visuospatial) was comparable to controls, yet this similar accuracy came at the expense of a longer response time to retain information correctly (on spatial span, p = 0.04). On tasks with higher executive demands, both visuospatial and verbal working memory were compromised, as RA patients took longer (p = 0.004) and had a higher number of total errors (p = 0.02) when conducting a strategic memory-guided search (Spatial Working Memory), and had a significantly lower verbal working memory span on the backwards digit recall test (p = 0.02).

Conclusion

The findings of this study emphasize the usefulness of performing computerized tests to detect subtle signs of cognitive impairment and of intact performance, which can inform memory training protocols for this vulnerable population.

Recovery of cognitive function after relapse in multiple sclerosis

BACKGROUND

Cognitive impairment is common in multiple sclerosis (MS) but its manifestation as acute disease activity is underappreciated.

OBJECTIVE

The aim of this study is to examine recovery after MS relapse on multiple tests of cognitive and motor function and explore correlates of change with Expanded Disability Status Scale (EDSS), magnetic resonance imaging (MRI), and cognitive reserve.

METHODS

Fifty relapsing group (RG) and matched stable participants were examined at baseline, during relapse, and at 3-month follow-up. Tests of cognitive processing speed (Symbol Digit Modalities Test (SDMT)) and consensus opinion measures of memory, ambulation, and manual dexterity were administered. All RG patients were treated with a 5-day course of Acthar Gel (5 mL/80 IU).

RESULTS

In RG patients, SDMT declined from 55.2 to 44.6 at relapse and recovered to 51.7, a slope differing from stable controls (p = 0.001). A statistical trend (p = 0.07) for the same effect was observed for verbal memory and was significant for ambulation (p = 0.03). The Cerebral Function Score from the EDSS also changed in the RG and recovered incompletely relative to controls (p = 0.006).

CONCLUSION

These results replicate earlier reports of cognitive worsening during relapse in MS. Clinically meaningful improvements followed relapse on SDMT and ambulation. Cognitive decline during relapse can be appreciated on neurological exam but not patient-reported outcomes.

Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions –Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)– across three different countries (>200 participants). We use machine-learning tools integrating multimodal measures such as cognitive scores (executive functions and cognitive screening) and brain atrophy volume (voxel based morphometry from fronto-temporo-insular regions in bvFTD, and temporo-parietal regions in AD) to identify the most relevant features in predicting the incidence of the diseases. In the Country-1 cohort, predictions of AD and bvFTD became maximally improved upon inclusion of cognitive screenings outcomes combined with atrophy levels. Multimodal training data from this cohort allowed predicting both AD and bvFTD in the other two novel datasets from other countries with high accuracy (>90%), demonstrating the robustness of the approach as well as the differential specificity and reliability of behavioral and neural markers for each condition. In sum, this is the first study, across centers and countries, to validate the predictive power of cognitive signatures combined with atrophy levels for contrastive neurodegenerative conditions, validating a benchmark for future assessments of reliability and reproducibility.