Symbol Digit Modalities Test Scores Research Articles

Exploring subcortical pathology and processing speed in neuromyelitis optica spectrum disorder with myelin water imaging.

Neuromyelitis optica spectrum disorder (NMOSD) affects the optic nerves and spinal cord but can also cause focal brain inflammation. Subcortical pathology may contribute to the etiology of cognitive deficits in NMOSD. Using myelin water imaging, we investigated cerebral normal-appearing white matter (NAWM) and thalamic metrics and their association with cognition in NMOSD participants compared to healthy controls (HC). Seventeen NMOSD participants and 21 HC were scanned on a 3.0-Tesla MRI scanner using a multicomponent driven-equilibrium single-pulse observation of T1 and T2 protocol. Tissue compartment and thalamic volumes (normalized to intracranial volume), T1 relaxation time, and myelin water fraction (MWF) were reported. Eleven NMOSD participants underwent the Symbol Digit Modalities Test (SDMT) for cognitive evaluation. Group comparisons were performed using Student's t-test. The association between thalamic metrics and SDMT score was assessed using multiple regression analysis with age as a covariate. Compared to HC, NMOSD participants had reduced white matter volume (-14.2%, p<.0001), increased T1 relaxation time (+2.29%, p=.022), and lower MWF (-3.64%, p=.024) in NAWM. NMOSD group had a trend for smaller thalamic volumes than HC (-5.52%, p=.082) and no differences in thalamic MWF (p=.258) or T1 (p=.714). Thalamic T1 predicted SDMT score (adjusted R2=.51, p=.04) when controlling for age. NAWM in NMOSD demonstrates diffuse abnormalities with increased water content and demyelination, suggesting a diffuse disease process overlooked by focal inflammation measures. Increased water content, as a biomarker for diffuse thalamic pathology, may partially explain cognitive impairment in NMOSD.

Improvement of fatigue, depression, and processing speed two weeks post Natalizumab infusion in Multiple Sclerosis: No difference between standard and extended interval dosing schedules

BackgroundFatigue, depression and slow processing speed are debilitating symptoms in people with Relapsing-Remitting Multiple Sclerosis (RRMS) that significantly impacts on the quality of life. Natalizumab, a disease-modifying treatment, improves clinical symptoms but questions remain about the comparative efficacy between its standard interval dosing (SID) and extended interval dosing (EID) schedules. ObjectiveTo examine the impact of short term natalizumab dosing schedules—SID versus EID—on the so called “invisible symptoms”, specifically focusing on symptom exacerbation during the 'wearing-off' phase before infusion and the subsequent relief post-infusion. MethodsForty-two RRMS patients were assessed one week before (T0) and two weeks after pre-and post-natalizumab infusion (T1) for fatigue symptoms using the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Modified Fatigue Impact Scale (MFIS), and the Fatigue Symptoms and Impacts Questionnaire–Relapsing Multiple Sclerosis (FSIQ-RMS). Processing speed and depression were measured by the symbol digit modality test (SDMT), and the Beck Depression Inventory-II (BDI-II). Participants were categorized into either the SID or EID dosing schedules of natalizumab, and their outcomes were compared. ResultsForty-two patients (21 SID; 21 EID) completed the study. Fatigue severity scales, SDMT, and BDI-II scores improved from T0 to T1. No significant differences in fatigue symptoms were found between the SID and EID groups, whether during the "wearing-off" period (T0) or post-infusion (T1). ConclusionsBoth SID and EID dosing regimens of natalizumab are similarly effective in reducing fatigue symptoms, depression and improving processing speed in individuals with RRMS, with no observed differences during the "wearing-off" periods or after re-infusion.

Clinical features of vascular cognitive impairment

Vascular cognitive impairment (VCI) can occur in cerebrovascular disease of varying degree of severity, which requires further investigation.Objective: to identify specific features of attention deficit and executive function (EF) impairment in VCI and to determine the relationship between cognitive, neurological and radiological signs of the disease.Material and methods. The study involved 80 patients (51 with VCI – the main group and 29 healthy volunteers – the control group). All participants underwent clinical and neuropsychological examination and MRI of the brain. VCI was diagnosed according to 2014 VASCOG criteria. The neuropsychological examination included an assessment of the general cognitive function (MoCA test, MMSE); general EF (FAB, EXIT-25); episodic memory (12-word memory test and Benton Visual Retention Test); semantic memory (categorical association method); initiation and productivity of cognitive activity (literal associations); attention [TMT-A, Symbol-Digit Modalities Test (SDMT)]; cognitive flexibility (TMT-B); cognitive control (Stroop test).Results. As a result of the study, three subgroups of patients with VCI were identified: 1) predominantly attention deficit (AD); 2) AD and significant decrease in cognitive flexibility (CFD); 3) AD in combination with a significant cognitive control deficiency (CCD). The TMT-A and SDMT tests were significantly worse in all subgroups of VCI compared to the control group, with the worst SDMT score in subgroup 2. Subgroup 2 also had the longest time to complete the TMT-B test. Subgroup 3 was characterized by the worst Stroop test results, and uncontrolled arterial hypertension was more common in this group. Gait disturbances were significantly more frequent in subgroup 2, and increased reflexes of oral automatism and grasp reflex were observed in subgroup 3. White matter hyperintensity (WMH) was more pronounced in subgroup 2, and lacunar infarcts (LI) were more frequent in subgroup 3. Prevalence of LI and severity of WMH were lowest in subgroup 1.Conclusion. The main features of VCI are attention deficit and EF impairment, characteristics of EF disorders depend on the severity and type of vascular lesions of the brain. Progression of WMH is associated with more pronounced CFD and an increase in the number of LI is associated with CCD. There is a correlation between CFD and gait disturbances and between CCD and lack of primitive reflexes inhibition.

Quantitative synthetic MRI for evaluation of hippocampus in patients with multiple sclerosis

ObjectiveTo identify early changes in hippocampal quantitative parameters in multiple sclerosis (MS) patients using synthetic MRI, and to correlate these changes with clinical variables. Methods45 MS patients and 26 healthy controls (HCs) underwent synthetic MRI and 3D-T1 MRI. The hippocampus volumes were assessed by using voxel-based morphometry. Synthetic MRI parameters (T1, T2, and proton density (PD)) from hippocampus and its subfield were measured and compared, and their associations with the Expanded Disability Status Scale (EDSS), Symbol Digit Modalities Test (SDMT) scores were further investigated. ResultsThere was no significant difference in hippocampal volume between MS patients and HCs. Compared with HCs, the T1, T2 and PD values of hippocampus and its subfield increased in MS patients. T2 values showed positive correlation with EDSS and negative correlation with SDMT. ConclusionsSynthetic MRI can detect subtle quantitative changes of the hippocampus in MS patients with normal hippocampal volume. Specifically, Synthetic MRI parameters may apply as potentially effective imaging biomarker for hippocampus evaluation.

Severe Cognitive Impairment in Trauma-Affected Refugees-Exploring the Impact of Traumatic Brain Injury.

Background/Objectives: This study explores the relationship between cognitive performance measured by the Symbol Digit Modality Test (SDMT) and the severity of self-reported head injury, traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), depression, pain, and psychosocial dysfunction in a population of trauma-affected refugees. Refugees, especially those who have been subjected to torture, often face various difficulties, such as PTSD, depression and somatic disturbances (e.g., pain), which can significantly impact their day-to-day functioning. Methods: Participants included 141 adult refugees (38% women) with a mean age of 45.4 years (SD = 9.4) and 9.7 years (SD = 4.9) of education who were referred for treatment of post-traumatic distress to DIGNITY, Danish Institute Against Torture. Participants completed standardized self-report measures of PTSD, anxiety, depression, pain, and health-related disability and measures of trauma history, physical injuries including head injury and loss of consciousness, and the SDMT, a quick standardized performance-based measure of cognitive impairment. Results: Eighty-eight percent of participants evidenced signs of substantial cognitive impairment as indexed by lower SDMT scores. Those with a self-reported history of TBI, marked by loss of consciousness, exhibited lower SDMT scores and higher health-related disabilities. Severity of PTSD, depression, anxiety, and pain were highly correlated with lower SDMT scores. TBI history was not significantly associated with the severity of PTSD, depression, anxiety, or pain, suggesting a complex interplay among these factors. Conclusions: Cognitive impairments are prevalent in trauma-affected refugees, interacting with symptoms of post-traumatic stress and pain, likely explaining the high disability levels in this population. Further research should employ a broader range of cognitive measures and detailed investigations of head injury/TBI experiences to investigate their impact on overall functioning, treatment response, and longer-term outcomes. This study adds to a small but growing body of studies documenting cognitive impairments in trauma-affected refugees, highlighting the importance of addressing cognitive impairments in treatment for trauma-affected refugees, particularly those with histories of torture and TBI. Clinicians working with trauma-affected refugees should consider the assessment of cognitive difficulties as part of comprehensive care planning.

Radiomics nomograms based on multi-sequence MRI for identifying cognitive impairment and predicting cognitive progression in relapsing-remitting multiple sclerosis

Rationale and ObjectivesTo build radiomics nomograms based on multi-sequence MRI to facilitate the identification of cognitive impairment (CI) and prediction of cognitive progression (CP) in patients with relapsing-remitting multiple sclerosis (RRMS). Materials and MethodsWe retrospectively included two RRMS cohorts with multi-sequence MRI and Symbol Digit Modalities Test (SDMT) data: dataset1 (n=149, for training and validation) and dataset2 (n=29, for external validation). 80 patients of dataset1 had a 2-year follow-up SDMT. CI and CP were evaluated using SDMT scores at baseline and follow-up. The included DIR sequence aided in identifying cortical lesions. Lesion radiomics and structural features were extracted and selected from multi-sequence MRI, followed by the computation of radiomics and structural scores. The nomogram was developed through multivariate logistic regression, integrating clinical data, radiomics and structural scores to identify CI in patients. Moreover, a similar method was employed to further construct a nomogram predicting CP in patients. ResultsThe nomogram demonstrated superior performance in identifying patients with CI, with area under the curve (AUC) values of 0.937 (95% Conf. Interval: 0.898-0.975) and 0.876 (0.810-0.943) in internal and external validation sets, compared to models solely based on clinical data, lesion radiomics, and structural features. Furthermore, another nomogram constructed in predicting CP also exhibited outstanding performance, with an AUC value of 0.969 (0.875-1.000) in the validation set. ConclusionThese nomograms, integrating clinical data, multi-sequence lesions radiomics and structural features, enable more effective identification of CI and early prediction of CP in RRMS patients, providing important support for clinical decision-making.

Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis

BackgroundThe choroid plexus (CP) is suggested to be closely associated with the neuroinflammation of multiple sclerosis (MS). Segmentation based on deep learning (DL) could facilitate rapid and reproducible volume assessment of the CP, which is crucial for elucidating its role in MS. PurposeTo develop a reliable DL model for the automatic segmentation of CP, and further validate its clinical significance in MS. MethodsThe 3D UX-Net model (3D U-Net used for comparison) was trained and validated on T1-weighted MRI from a cohort of 216 relapsing-remitting MS (RRMS) patients and 75 healthy subjects. Among these, 53 RRMS with baseline and 2-year follow-up scans formed an internal test set (dataset1b). Another 58 RRMS from multi-center data served as an external test set (dataset2). Dice coefficient was computed to assess segmentation performance. Compare the correlation of CP volume obtained through automatic and manual segmentation with clinical outcomes in MS. Disability and cognitive function of patients were assessed using the Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). ResultsThe 3D UX-Net model achieved Dice coefficients of 0.875 ± 0.030 and 0.870 ± 0.044 for CP segmentation on dataset1b and dataset2, respectively, outperforming 3D U-Net's scores of 0.809 ± 0.098 and 0.601 ± 0.226. Furthermore, CP volumes segmented by the 3D UX-Net model aligned consistently with clinical outcomes compared to manual segmentation. In dataset1b, both manual and automatic segmentation revealed a significant positive correlation between normalized CP volume (nCPV) and EDSS scores at baseline (manual: r = 0.285, p = 0.045; automatic: r = 0.287, p = 0.044) and a negative correlation with SDMT scores (manual: r = -0.331, p = 0.020; automatic: r = -0.329, p = 0.021). In dataset2, similar correlations were found with EDSS scores (manual: r = 0.337, p = 0.021; automatic: r = 0.346, p = 0.017). Meanwhile, in dataset1b, both manual and automatic segmentation revealed a significant increase in nCPV from baseline to follow-up (p < 0.05). The increase of nCPV was more pronounced in patients with disability worsened than stable patients (manual: p = 0.023; automatic: p = 0.018). Patients receiving disease-modifying therapy (DMT) exhibited a significantly lower nCPV increase than untreated patients (manual: p = 0.004; automatic: p = 0.004). ConclusionThe 3D UX-Net model demonstrated strong segmentation performance for the CP, and the automatic segmented CP can be directly used in MS clinical practice. CP volume can serve as a surrogate imaging biomarker for monitoring disease progression and DMT response in MS patients.

Changes of brain parenchyma free water fraction reflect tissue damage and impaired processing speed in multiple sclerosis.

Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm2, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.

The impact of incident stroke on cognitive trajectories in later life

BackgroundCognitive impairment is common after stroke, and a large proportion of stroke patients will develop dementia. However, there have been few large prospective studies which have assessed cognition both prior to and after stroke. This study aims to determine the extent to which incident stroke impacts different domains of cognitive function in a longitudinal cohort of older community-dwelling individuals.Methods19,114 older individuals without cardiovascular disease or major cognitive impairment were recruited and followed over a maximum 11 years. Stroke included ischaemic and haemorrhagic stroke and was adjudicated by experts. Cognitive function was assessed regularly using Modified Mini-Mental State Examination (3MS), Hopkins Verbal Learning Test–Revised (HVLT-R), Symbol Digit Modalities Test (SDMT), and Controlled Oral Word Association Test (COWAT). Linear mixed models were used to investigate the change in cognition at the time of stroke and decline in cognitive trajectories following incident stroke.ResultsDuring a median follow-up period of 8.4 [IQR: 7.2, 9.6] years, 815 (4.3%) participants experienced a stroke. Over this time, there was a general decline observed in 3MS, HVLT-R delayed recall, and SDMT scores across participants. However, for individuals who experienced a stroke, there was a significantly greater decline across all cognitive domains immediately after the event immediately after the event (3MS: -1.03 [95%CI: -1.45, -0.60]; HVLT-R: -0.47 [-0.70, -0.24]; SDMT: -2.82 [-3.57, -2.08]; COWAT: -0.67 [-1.04, -0.29]) and a steeper long-term decline for three of these domains (3MS -0.62 [-0.88, -0.35]; COWAT: -0.30 [-0.46, -0.14]); HVLT-R: -0.12 [95%CI, -0.70, -0.24]). However individuals with stroke experienced no longer-term decline in SDMT compared to the rest of the participants.ConclusionsThese findings highlight the need for comprehensive neuropsychology assessments for ongoing monitoring of cognition following incident stroke; and potential early intervention.

Reliability and validity of a novel attention assessment scale (broken ring enVision search test) in the Chinese population.

The correct assessment of attentional function is the key to cognitive research. A new attention assessment scale, the Broken Ring enVision Search Test (BReViS), has not been validated in China. The purpose of this study was to assess the reliability and validity of the BReViS in the Chinese population. From July to October 2023, 100 healthy residents of Changzhou were selected and subjected to the BReViS, Digital Cancelation Test (D-CAT), Symbol Digit Modalities Test (SDMT), and Digit Span Test (DST). Thirty individuals were randomly chosen to undergo the BReViS twice for test-retest reliability assessment. Correlation analysis was conducted between age, education level, gender, and various BReViS sub-tests including Selective Attention (SA), Orientation of Attention (OA), Focal Attention (FA), and Total Errors (Err). Intergroup comparisons and multiple linear regression analyses were performed. Additionally, correlation analyses between the BReViS sub-tests and with other attention tests were also analyzed. The correlation coefficients of the BReViS sub-tests (except for FA) between the two tests were greater than 0.600 (p < 0.001), indicating good test-retest reliability. The Cronbach's alpha coefficient was 0.874, suggesting high internal consistency reliability. SA showed a significant negative correlation with the net score of D-CAT (r = -0.405, p < 0.001), and a significant positive correlation with the error rate of D-CAT (r = 0.401, p < 0.001), demonstrating good criterion-related validity. The correlation analysis among the results of each sub-test showed that the correlation coefficient between SA and Err was 0.532 (p < 0.001), and between OA and Err was-0.229 (p < 0.05), whereas there was no significant correlation between SA, OA, and FA, which indicated that the scale had good informational content validity and structural validity. Both SA and Err were significantly correlated with age and years of education, while gender was significantly correlated with OA and Err. Multiple linear regression suggested that Err was mainly affected by age and gender. There were significant differences in the above indexes among different age, education level and gender groups. Correlation analysis with other attention tests revealed that SA negatively correlated with DST forward and backward scores and SDMT scores. Err positively correlated with D-CAT net scores and negatively with D-CAT error rate, DST forward and backward scores, and SDMT scores. OA and FA showed no significant correlation with other attention tests. The BReViS test, demonstrating good reliability and validity, assessing not only selective attention but also gauging capacities in immediate memory, information processing speed, visual scanning, and hand-eye coordination. The results are susceptible to demographic variables such as age, gender, and education level.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

AbstractFunctional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting‐state functional MRI (rs‐fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs‐fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual‐to‐sensorimotor) and a secondary (sensory‐to‐transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory‐transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (, p &lt; .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network‐level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold‐out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs‐fMRI studies across different MS populations.

Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators

Rationale and objectivesTo investigate whether clinical and grey matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine learning model. Materials and methodsOne hundred forty-five and 50 RRMS patients with structural MRI and at least 1-year follow-up Expanded Disability Status Scale (EDSS) results were retrospectively enrolled and placed in the discovery and external test cohorts, respectively. Six clinical and radiomics feature-based machine learning classifiers were trained and tested to predict disability progression in the discovery cohort and validated in the external test set. Partial dependence plot (PDP) analysis and a Shiny web application were conducted to enhance the interpretability and intuitiveness. ResultsIn the discovery cohort, 98 patients had disability stability, and 47 patients were classified as having disability progression. In the external test set, 35 patients were disability stable, and 15 patients had disability progression. Models trained with both clinical and radiomics features (area under the curve (AUC), 0.725-0.950) outperformed those trained with clinical (AUC, 0.600-0.740) or radiomics features only (AUC, 0.615-0.945). Among clinical + radiomics feature models, the logistic regression (LR) classifier-based model performed best, with an AUC of 0.950. Only the radiomics feature-only models were applied in the external test set due to the data collection problem and showed fair performance, with AUCs ranging from 0.617 to 0.753. PDP analysis showed that female patients and those with lower volume, surface area, and symbol digit modalities test (SDMT) scores; greater mean curvature and age; and no disease modifying therapy (DMT) had increased probabilities of disease progression. Finally, a Shiny web application (https://lauralin1104.shinyapps.io/LRshiny/) was developed to calculate the risk of disability progression. ConclusionsInterpretable and intuitive machine learning approaches based on clinical and GM atrophy indicators can help physicians predict disability progression in RRMS patients for clinical decision-making and patient management.

Is impairment of facial emotion recognition independent of cognitive dysfunction in multiple sclerosis?

BackgroundEmotions expressed on the face play a key role in social cognition and communication by providing inner emotional experiences. This study aimed to evaluate facial emotion identification and discrimination and empathy abilities in patients with MS and whether it is related to cognitive dysfunction.MethodsOne hundred twenty patients with relapsing–remitting MS and age- and sex-matched 120 healthy controls were enrolled in the study. All the subjects were evaluated with the Facial Emotion Identification Test (FEIT), Facial Emotion Discrimination Test (FEIDT), and Empathy Quotient (EQ). We used the Beck Depression Inventory (BDI) for depression and detailed cognitive tests, including the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), and the Paced Auditory Serial Addition Test (PASAT). The quality of life was assessed with Multiple Sclerosis Quality of Life-54 (MSQL-54).ResultsPatients with MS were 37.6 ± 9.5 years old, had a mean disease duration of 8.8 ± 6.6 (8–28) years, and a mean EDSS score of 1.6 ± 1.3 (0–4.5). We found significant differences in the identification of facial emotions, discrimination of facial emotions, and empathy in MS patients compared to controls (p < 0.05). Especially the recognition of feelings of sadness, fear, and shame was significantly lower in MS patients. The multivariate logistic regression analysis showed low SDMT and FEIDT scores which showed an independent association with MS.ConclusionsOur findings indicate that facial emotion recognition and identification deficits are remarkable among patients with MS and emotion recognition is impaired together with and independently of cognitive dysfunction in MS patients.

Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds

Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.

Night Screen Time is Associated with Cognitive Function in Healthy Young Adults: A Cross-Sectional Study.

In recent years, a significant shift toward remote work, virtual education, and social distancing measures was witnessed, thereby leading people to increasingly depend on digital devices for communication, work, and entertainment. This increased exposure to screens has raised concerns regarding its potential impact on cognitive function. This study investigated the relationship between screen time and cognitive function among healthy young adults. One hundred forty-five healthy individuals (mean age 21.55 ± 2.84 years) participated in this cross-sectional study. Sociodemographic information including age, sex, height, weight, and level of education were obtained. Participants reported screen time using a screen time questionnaire. Cognitive function tests including, Paced Auditory Serial Addition Task (PASAT), Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were conducted. Multilinear regression analyses were used to examine the associations between age, sex, level of education, screen time, and cognitive function. One hundred thirty-nine participants (76 women) completed the study. Increased night screen time, bachelor's educational level, and women were associated with lower PASAT scores (R2=0.258; p≤0.047). Moreover, increased night screen time was associated with lower MoCA scores (R2=0.029; p=0.035). However, no associations were found between night screen time and SDMT scores. Participants who had higher night screen exposure had lower cognitive scores in the information speed processing, working memory, calculation, and attention domains. Considering these findings, this study emphasizes on the importance of setting a future recommended screen time guidelines for young adults as well as to promote healthy cognitive habits in order to preserve cognitive function and reduce the risk of developing neurodegenerative disease in the future. Future prospective cohort studies involving a more diverse age range is needed.

Cognitive function and brain magnetic resonance imaging profiles in neuromyelitis optica spectrum disorder and multiple sclerosis.

The objective of this study was to investigate cognitive performance and brain volume profile in patients with neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS). In a historical cohort study, 29 MS patients, 31 NMOSD patients, and 20 healthy controls (HCs) underwent neuropsychological assessment using the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS). Patients with MS and NMOSD also underwent a 1.5-tesla magnetic resonance imaging scan and high-resolution three-dimensional T1-weighted MPRAGE sequence. The Symbol Digit Modalities Test scores were significantly lower in MS (mean [standard deviation (SD)] =44.1 [14]) and NMOSD (mean [SD] =45.5 [14.3]) patients compared to HCs (mean [SD] =57 [9.5], P < 0.001). Scores of the Controlled Oral Word Association Test were also lower in MS (mean [SD] =25.9 [9.8]) and NMOSD (mean [SD] =24.6 [10.2]) patients compared to HCs (mean [SD] =36.6 [9.8], P < 0.001). Additionally, the MS group performed worse on the Brief Visuospatial Memory Test (BVMT) compared to the NMOSD group (9.4 ± 3.4 vs. 7.1 ± 3.7 P < 0.001). In MS patients, there was a significant correlation between all cognition scores and total brain lesions, as well as between every test except BVMT-Revised with thalamic volumes. In NMOSD patients, a correlation was found between gray matter volume and the learning phase of the California Verbal Learning Test-II as well as between total lesion percentage and verbal memory and information processing speed. Both NMOSD and MS patients experienced impairment of information processing speed, working memory, and verbal fluency, whereas visuospatial memory impairment was only observed in MS patients. Despite lower total brain lesion and less thalamic atrophy, patients with NMOSD are at risk of cognitive impairment. Microscopic structural abnormalities may be a possible cause.

Clinical features of sleep apnea syndrome and cognitive impairment in multiple sclerosis

Background: Complications of obstructive sleep apnea (OSA) have been reported in patients with multiple sclerosis (MS). Patients with sleep apnea syndrome (SAS) due to OSA also show cognitive decline, with similar clinical characteristics to that manifested in MS. SAS due to OSA is a treatable condition, and the associated cognitive decline is expected to improve. This study investigates clinical features of SAS in people living with MS and contribute to improve cognitive dysfunction of MS.Methods: A case-control study was conducted. Cognitive functions were evaluated by the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test 2 (PASAT-2) and 3 (PASAT-3). The Respiratory Event Index (REI) was measured using Out of Center Sleep Testing (OCST). We defined subjects with REI ≥ 5 as OSA and divided participants into two groups with or without SAS due to OSA. Cognitive and respiratory characteristics were statistically compared between patients with MS and healthy controls.Results: We enrolled 67 people living with MS and 31 age- and sex-matched controls. OCST detected OSA in people living with MS and controls, and the prevalence rates were 28.4 % and 25.8 %, respectively. REI values (5.2 ± 7.9 vs 3.9 ± 5.2, p = 0.509) and number of participants with REI ≥ 5 (19 vs 8, p = 0.793) were similar between the MS and control group. The SDMT, PASAT-2, and PASAT-3 scores were significantly lower in the MS group than the control group (p < 0.001, p = 0.001, and p < 0.001, respectively). The interaction effect of MS and SAS on cognitive function was not significant in the SDMT (p = 0.078), but in the PASAT-2 (p = 0.043) and PASAT-3 (p = 0.020).Conclusion: This study revealed the prevalence rates of SAS in Japanese people living with MS and the usefulness of OCST for detection of SAS. This study also revealed that concomitant SAS can facilitate cognitive decline in people living with MS. These findings suggest that an appropriate intervention for OSA can be beneficial for people living with MS with cognitive decline.

Effects of transcranial alternating current stimulation on cognitive function in people with multiple sclerosis: A randomized controlled trial

BackgroundCognitive impairment is a core symptom that profoundly impacts the lives of people with multiple sclerosis (PwMS). Since the existing disease modifying therapies can only stabilize, but not actively treat, cognition in PwMS, there is an unmet need to expand approaches to treat these cognitive symptoms. Transcranial alternating current stimulation (tACS) permits frequency-specific entrainment of neural oscillations intrinsic to cognitive activity. However, the effects of the tACS on cognitive function in PwMS have not yet been assessed. We aimed to evaluate the potential efficacy of applying frontal theta-tACS to improve information processing speed in PwMS. Methods60 PwMS with cognitive complaints were enrolled in a double-blinded, randomized, controlled trial with three stimulation groups: 2 mA, 1 mA, or sham control. A single session of theta-tACS was applied while participants were engaged in a cognitive program which has shown to improve processing speed in PwMS. tACS effects were examined by the Symbol Digit Modalities Test (SDMT). Tolerability, side effects and acceptability were measured. Results1 mA groups had a significantly higher SDMT score after stimulation compared to their pre-stimulation score, 2 mA group showed a marginally significant improvement of their SDMT score, while the SDMT score in the sham group did not change. Overall, 49% of the stimulation group participants showed a clinically meaningful SDMT improvement (4+-point increase). ConclusiontACS is a well-tolerated, non-pharmacological intervention. Based on the positive effects observed in the current study of a single session of tACS applied during cognitive engagement, the effects of repeated tACS on cognitive function in PwMS merit further research. Trial RegistrationClinicalTrials.gov NCT04466228.

Differences in resting state functional connectivity relative to multiple sclerosis and impaired information processing speed.

Fifty-one percent of individuals with multiple sclerosis (MS) develop cognitive impairment (CI) in information processing speed (IPS). Although IPS scores are associated with health and well-being, neural changes that underlie IPS impairments in MS are not understood. Resting state fMRI can provide insight into brain function changes underlying impairment in persons with MS. We aimed to assess functional connectivity (FC) differences in (i) persons with MS compared to healthy controls (HC), (ii) persons with both MS and CI (MS-CI) compared to HC, (iii) persons with MS that are cognitively preserved (MS-CP) compared to HC, (iv) MS-CI compared to MS-CP, and (v) in relation to cognition within the MS group. We included 107 participants with MS (age 49.5 ± 12.9, 82% women), and 94 controls (age 37.9 ± 15.4, 66% women). Each participant was administered the Symbol Digit Modalities Test (SDMT) and underwent a resting state fMRI scan. The MS-CI group was created by applying a z-score cut-off of -1.5 to locally normalized SDMT scores. The MS-CP group was created by applying a z-score of ≥0. Control groups (HCMS-CI and HCMS-CP) were based on the nearest age-matched HC participants. A whole-brain ROI-to-ROI analysis was performed followed by specific contrasts and a regression analysis. Individuals with MS showed FC differences compared to HC that involved the cerebellum, visual and language-associated brain regions, and the thalamus, hippocampus, and basal ganglia. The MS-CI showed FC differences compared to HCMS-CI that involved the cerebellum, visual and language-associated areas, thalamus, and caudate. SDMT scores were correlated with FC between the cerebellum and lateral occipital cortex in MS. No differences were observed between the MS-CP and HCMS-CP or MS-CI and MS-CP groups. Our findings emphasize FC changes of cerebellar, visual, and language-associated areas in persons with MS. These differences were apparent for (i) all MS participants compared to HC, (ii) MS-CI subgroup and their matched controls, and (iii) the association between FC and SDMT scores within the MS group. Our findings strongly suggest that future work that examines the associations between FC and IPS impairments in MS should focus on the involvement of these regions.

A - 112 Subjective and Objective Cognition in Patients Driving with Multiple Sclerosis.

Multiple sclerosis (MS) is a disease of the central nervous system that results in focal lesions of demyelination, inflammation, and axonal damage to the brain and spinal cord. MS affects nearly one million people in the United States. Drivers with MS have been characterized by shorter disease durations, milder disabilities and greater awareness of their deficits compared to non-drivers. Cognitive function can impact MS patients' driving abilities, specifically their processing speed, attention and visuospatial deficiencies. This study evaluates whether subjective cognitive decline (SCD) can predict objective cognitive functioning to improve identification of patients at risk for impaired driving. All participants were patients at an MS Center, and had a diagnosis of MS based on the McDonald criteria. One hundred and eight MS patients were included in the study, and all participants completed the symbol digit modality test (SDMT). The majority of patients were female (75.9%), and only 19.4% of study participants reported having SCD that impact their driving ability. Participants with poorer processing speed had endorsed cognitive difficulties impacting their driving, U = 503.00, p = 0.001. Results suggest that slower SDMT scores may likely predict SCD. Patients with MS with poorer processing speed were also likely to report a SCD, and had a higher incidence rate of motor vehicle accidents. This relationship needs to be further assessed to aid in the safety of patients of MS and understanding if barriers such as lack of social support or work obligations that require them to continue driving.