Maureen van Dam

Background: Cognitive impairment in multiple sclerosis (MS) is related to abnormal structural and functional brain network changes. As both modalities have mostly been studied separately, structure connectivity-function coupling (SC-FC) may elucidate how function is constrained by structure. Objectives: We examine how changes in SC-FC and its dynamics SC-FC (dSC-FC) may underlie MS-related cognitive impairment. Methods: We classified 266 people with MS (PwMS) as cognitively impaired (CI; z < −2 on ≥2/7 cognitive abilities compared to healthy controls [HC]) or preserved (CP; z > −1.5 on ≥2/7 abilities). Derived from diffusion-weighted and functional magnetic resonance imaging, SC-FC reflected the correlation coefficient between structural and functional connectivity, while dSC-FC reflected its variability. Whole-brain, within-network, and between-network (d)SC-FC were compared between 95 HC, 197 CP, and 69 CI. Results: Compared to CP and HC, CI showed higher SC-FC for connections extending from the dorsal attention (DAN; p ≤ 0.006) and somatomotor networks ( p ≤ 0.024), and higher dSC-FC within the visual network ( p ≤ 0.003) and deep grey matter ( p ≤ 0.006). SC-FC in connections extending from the DAN predicted CP/CI status in PwMS ( β = 0.069, OR = 1.072 [95% CI = 1.009–1.139], p = 0.025). Conclusions: In MS-related CI, deterioration of structural pathways is paired with loss of functional strength in connections extending from the DAN. This may hinder DAN-mediated stimulus selection, possibly contributing to CI.

Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-specific cognitive functioning over 10 years in people with MS and assesses the influence of cortical lesion load and formation on these trajectories. In this prospectively collected study, people with MS underwent 3T MRI (T1 and fluid-attenuated inversion recovery) at 3 study visits between 2008 and 2022. Cognitive functioning was evaluated based on neuropsychological assessment reflecting 7 cognitive functions: attention; executive functioning (EF); information processing speed (IPS); verbal fluency; and verbal, visuospatial, and working memory. Cortical lesions were manually identified on artificial intelligence-generated double-inversion recovery images. Linear mixed models were constructed to assess the temporal evolution between cortical lesion load and function-specific cognitive decline. In addition, analyses were stratified by MS disease stage: early and late relapsing-remitting MS (cutoff disease duration at 15 years) and progressive MS. The study included 223 people with MS (mean age, 47.8 ± 11.1 years; 153 women) and 62 healthy controls. All completed 5-year follow-up, and 37 healthy controls and 94 with MS completed 10-year follow-up. At baseline, people with MS exhibited worse functioning of IPS and working memory. Over 10 years, cognitive decline was most severe in attention, verbal memory, and EF. At baseline, people with MS had a median cortical lesion count of 7 (range 0-73), which was related to subsequent decline in attention (B[95% CI] = -0.22 [-0.40 to -0.03]) and verbal fluency (B[95% CI] = -0.23[-0.37 to -0.09]). Over time, cortical lesions increased by a median count of 4 (range -2 to 71), particularly in late and progressive disease, and was related to decline in verbal fluency (B [95% CI] = -0.33 [-0.51 to -0.15]). The associations between (change in) cortical lesion load and cognitive decline were not modified by MS disease stage. Cognition worsened over 10 years, particularly affecting attention, verbal memory, and EF, while preexisting impairments were worst in other functions such as IPS. Worse baseline cognitive functioning was related to baseline cortical lesions, whereas baseline cortical lesions and cortical lesion formation were related to cognitive decline in functions less affected at baseline. Accumulating cortical damage leads to spreading of cognitive impairments toward additional functions.

Background: Assessment of cognitive decline in the earliest stages of Alzheimer disease (AD) is important but challenging. AD is a neurodegenerative disease characterized by gradual cognitive decline. Disease stages range from preclinical AD, in which individuals are cognitively unimpaired, to mild cognitive impairment (MCI) and dementia. Digital technologies promise to enable detection of early, subtle cognitive changes. Although the field of digital cognitive biomarkers is rapidly evolving, a comprehensive overview of the reporting of psychometric properties (ie, validity, reliability, responsiveness, and clinical meaningfulness) is missing. Insight into the extent to which these properties are evaluated is needed to identify the validation steps toward implementation. Objective: This scoping review aimed to identify the reporting on quality characteristics of smartphone- and tablet-based cognitive tools with potential for remote administration in individuals with preclinical AD or MCI. We focused on both psychometric properties and practical tool characteristics. Methods: This scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. In total, 4 databases (PubMed, Embase, Web of Science, and PsycINFO) were systematically searched from January 1, 2008, to January 5, 2023. Studies were included that assessed the psychometric properties of cognitive smartphone- or tablet-based tools with potential for remote administration in individuals with preclinical AD or MCI. In total, 2 reviewers independently screened titles and abstracts in ASReview, a screening tool that combines manual and automatic screening using an active learning algorithm. Thereafter, we manually screened full texts in the web application Rayyan. For each included study, 2 reviewers independently explored the reported information on practical and psychometric properties. For each psychometric property, examples were provided narratively. Results: In total, 11,300 deduplicated studies were identified in the search. After screening, 50 studies describing 37 different digital tools were included in this review. Average administration time was 13.8 (SD 10.1; range 1-32) minutes, but for 38% (14/37) of the tools, this was not described. Most tools (31/37, 84%) were examined in 1 language. The investigated populations were mainly individuals with MCI (34/37, 92%), and fewer tools were examined in individuals with preclinical AD (8/37, 22%). For almost all tools (36/37, 97%), construct validity was assessed through evaluation of clinical or biological associations or relevant group differences. For a small number of tools, information on structural validity (3/37, 8%), test-retest reliability (12/37, 32%), responsiveness (6/37, 16%), or clinical meaningfulness (0%) was reported. Conclusions: Numerous smartphone- and tablet-based tools to assess cognition in early AD are being developed, whereas studies concerning their psychometric properties are limited. Often, initial validation steps have been taken, yet further validation and careful selection of psychometrically valid outcome scores are required to demonstrate clinical usefulness with regard to the context of use, which is essential for implementation.

Background: Literature on the intricate relationship between self-reported and objectively assessed cognitive functioning suggests a discrepancy between self-reported cognitive complaints (SCC) and actual test performance. Objectives: To investigate the interplay between patient-reported outcome measures (PROMs) and objective cognitive functioning using network analysis in people with multiple sclerosis (PwMS). Methods: We collected PROMs on anxiety, depression, fatigue and SCC, and cognitive functioning across six domains ( n = 703 PwMS; 71% female, mean age = 46.3 ± 11.2 years). We constructed cognitive symptom networks using Gaussian Graphical Models, in which the aforementioned variables were presented as nodes linked by regularized partial correlations. We compared global network strength between relevant subgroups. Results: The networks primarily showed clustering of PROMs and cognitive domains into two separate modules, with weaker links connecting both modules. Global network strength was lower for PwMS with impaired information processing speed (IPS; indicating lower symptom interrelatedness) compared to those with preserved IPS (3.57 versus 4.51, p = 0.001), but not when comparing SCC subgroups ( p = 0.140). Conclusions: Cognitive symptom networks deepen our understanding of the discrepancy between self-reported and objectively assessed cognitive functioning. Lower symptom interrelatedness in PwMS with impaired IPS might suggest a nonlinear relation between PROMs and cognitive domains, which depends on the cognitive status.

Patients with multiple sclerosis (MS) often experience cognitive impairment, and this is related to structural disconnection and subsequent functional reorganization. It is unclear how specific patterns of functional reorganization might make it harder for cognitively impaired (CI) patients with MS to dynamically adapt how brain regions communicate, which is crucial for normal cognition. We aimed to identify dynamic functional network patterns that are relevant to cognitive impairment in MS and investigate whether these patterns can be explained by altered energy costs. Resting-state functional and diffusion MRI was acquired in a cross-sectional design, as part of the Amsterdam MS cohort. Patients with clinically definitive MS (relapse-free) were classified as CI (≥2/7 domains Z < -2), mildly CI (MCI) (≥2/7 domains Z < -1.5), or cognitively preserved (CP) based on an expanded Brief Repeatable Battery of Neuropsychological Tests. Functional connectivity states were determined using k-means clustering of moment-to-moment cofluctuations (i.e., edge time series), and the resulting state sequence was used to characterize the frequency of transitions. Control energy of the state transitions was calculated using the structural network with network control theory. Imaging and cognitive data were available for 95 controls and 330 patients (disease duration: 15 years; 179 CP, 65 MCI, and 86 CI). We identified a "visual network state," "sensorimotor network state," "ventral attention network state," and "default mode network state." CI patients transitioned less frequently between connectivity states compared with CP (β = -5.78; p = 0.038). Relative to the time spent in a state, CI patients transitioned less from a "default mode network state" to a "visual network state" (β = -0.02; p = 0.004). The CI patients required more control energy to transition between states (β = 0.32; p = 0.007), particularly for the same transition (β = 0.34; p = 0.049). This study showed that it costs more energy for MS patients with cognitive impairment to dynamically change the functional network, possibly explaining why these transitions occur less frequently. In particular, transitions from a default mode network state to a visual network state were relevant for cognition in these patients. To further study the order of events leading to these network disturbances, future work should include longitudinal data across different disease stages.

BACKGROUND Assessment of cognitive decline in the earliest stages of Alzheimer disease (AD) is important but challenging. AD is a neurodegenerative disease characterized by gradual cognitive decline. Disease stages range from preclinical AD, in which individuals are cognitively unimpaired, to mild cognitive impairment (MCI) and dementia. Digital technologies promise to enable detection of early, subtle cognitive changes. Although the field of digital cognitive biomarkers is rapidly evolving, a comprehensive overview of the reporting of psychometric properties (ie, validity, reliability, responsiveness, and clinical meaningfulness) is missing. Insight into the extent to which these properties are evaluated is needed to identify the validation steps toward implementation. OBJECTIVE This scoping review aimed to identify the reporting on quality characteristics of smartphone- and tablet-based cognitive tools with potential for remote administration in individuals with preclinical AD or MCI. We focused on both psychometric properties and practical tool characteristics. METHODS This scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. In total, 4 databases (PubMed, Embase, Web of Science, and PsycINFO) were systematically searched from January 1, 2008, to January 5, 2023. Studies were included that assessed the psychometric properties of cognitive smartphone- or tablet-based tools with potential for remote administration in individuals with preclinical AD or MCI. In total, 2 reviewers independently screened titles and abstracts in ASReview, a screening tool that combines manual and automatic screening using an active learning algorithm. Thereafter, we manually screened full texts in the web application Rayyan. For each included study, 2 reviewers independently explored the reported information on practical and psychometric properties. For each psychometric property, examples were provided narratively. RESULTS In total, 11,300 deduplicated studies were identified in the search. After screening, 50 studies describing 37 different digital tools were included in this review. Average administration time was 13.8 (SD 10.1; range 1-32) minutes, but for 38% (14/37) of the tools, this was not described. Most tools (31/37, 84%) were examined in 1 language. The investigated populations were mainly individuals with MCI (34/37, 92%), and fewer tools were examined in individuals with preclinical AD (8/37, 22%). For almost all tools (36/37, 97%), construct validity was assessed through evaluation of clinical or biological associations or relevant group differences. For a small number of tools, information on structural validity (3/37, 8%), test-retest reliability (12/37, 32%), responsiveness (6/37, 16%), or clinical meaningfulness (0%) was reported. CONCLUSIONS Numerous smartphone- and tablet-based tools to assess cognition in early AD are being developed, whereas studies concerning their psychometric properties are limited. Often, initial validation steps have been taken, yet further validation and careful selection of psychometrically valid outcome scores are required to demonstrate clinical usefulness with regard to the context of use, which is essential for implementation.

Background: Multiple sclerosis (MS) frequently gives rise to depressive and anxiety symptoms, but these are often undertreated. This study investigated the effect of mindfulness-based cognitive therapy (MBCT) and cognitive rehabilitation therapy (CRT) on psychological outcomes and quality of life (QoL), and whether they mediate treatment effects on MS-related cognitive problems.Methods: This randomized controlled trial included MS patients with cognitive complaints (n = 99) and compared MBCT (n = 32) and CRT (n = 32) to enhanced treatment as usual (n = 35). Baseline, post-treatment and 6-months follow-up assessments included patient-reported outcome measures (PROMS) and cognitive outcomes (self-reported and neuropsychological assessment). PROMS concerned psychological symptoms, well-being, QoL, and daily life function. Linear mixed models indicated intervention effects on PROMS and mediation effects of PROMS on cognitive outcomes.Results: MBCT positively affected depressive symptoms (Cohen’sd(d) = −0.46), fatigue (d = −0.39), brooding (d = −0.34), mindfulness skills (d = 0.49), and mental QoL (d = −0.73) at post-treatment. Effects on mindfulness skills remained significant 6 months later (d = 0.42). CRT positively affected depressive symptoms (d = −0.46), mindfulness skills (d = 0.37), and mental QoL (d = −0.45) at post-treatment, but not at 6-month follow-up. No effects on anxiety, well-being, self-compassion, physical QoL, and daily life function were found. Treatment effects on self-reported, but not objective, cognition were mediated by psychological symptoms and mindfulness skills.Conclusions: MBCT and CRT reduced a wide array of psychological symptoms and improved mental QoL. These improvements seemed to impact self-reported cognitive problems after both treatments, whereas objective cognitive improvements after MBCT seemed independent of improvement in psychological symptoms. Future studies should investigate long-term sustainability of these beneficial effects.Trial registration: The trial was prospectively registered in the Dutch Trial registry on 31 May 2017 (NL6285;https://trialsearch.who.int/Trial2.aspx?TrialID=NTR6459).

Background and objectives: Patients with multiple sclerosis (MS) often experience cognitive impairment, and this is related to structural disconnection and subsequent functional reorganization. It is not clear how specific patterns of functional reorganization might make it harder for cognitively impaired (CI) MS patients to dynamically adapt how brain regions communicate, which is crucial for normal cognition. To identify patterns relevant to cognitive impairment in MS, we performed a temporally detailed analysis of connectivity state transitions and quantified the effort associated with such dynamic alterations. Methods: Resting-state functional and diffusion MRI was acquired from 95 controls and 330 MS patients (mean disease duration: 15 years) in a cross-sectional design, of whom 86 were classified as CI (≥2/7 domains Z < −2) and 65 as mildly CI (≥2/7 domains Z < −1.5) based on the performance on an expanded Brief Repeatable Battery of Neuropsychological Tests. Four functional connectivity states were determined using K -means clustering of moment-to- moment co-fluctuations (i.e., edge time series), and the resulting state sequence was used to characterize the frequency of transitions between network configurations. The control energy associated with the transitions between states was then calculated using the structural network of each subject with network control theory. Results: CI patients transition less frequently between connectivity states. Relative to the time spent in a particular state, CI patients specifically transition less from a weakly connected and highly modular state (i.e., the weakly connected state ) to a more integrated state that featured strong involvement of the visual network (i.e., the visual network state ), but more in the opposite direction. CI patients also required more control energy to transition between states. Discussion: This study showed that it became more effortful for MS patients with cognitive impairment to dynamically change the organization of the functional network, providing an intuitive understanding of why these transitions occur less frequently in some patients. In particular, transitions between the weakly connected state and the more integrated visual network state were relevant for cognition in these patients. The findings highlight a possible underpinning of disturbed cognition in MS patients and also provide novel avenues for studying and possibly improving network dynamics.

Background: The heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired). Methods: We included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing–remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ − 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification. Results: Six profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997). Conclusions: This study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.