Our results suggest that ACE-III is a useful neuropsychological test for assessing the cognitive domains of attention, language, memory, and visuospatial function. It also enables detection of Alzheimer's disease in early stages.

BackgroundCognitive impairment is frequent and disabling in multiple sclerosis (MS). Changes in information processing speed constitute the most important cognitive deficit in MS. However, given the clinical and topographical variability of the disease, cognitive impairment may vary greatly and appear in other forms in addition to slower information processing speed. Our aim was to determine the frequency of cognitive impairment, the principal cognitive domains, and components involved in MS and to identify factors associated with presence of cognitive impairment in these patients in a large series of patients.MethodsCross-sectional study of 311 patients with MS [236 with relapsing-remitting MS (RRMS), 52 with secondary progressive MS (SPMS), and 23 with primary progressive MS (PPMS)]. Patients’ cognitive function was assessed with a comprehensive neuropsychological assessment protocol. Patients displaying deficits in 2 or more cognitive domains were considered to have cognitive impairment associated with MS. We conducted a principal component analysis to detect different cognitive patterns by identifying clusters of tests highly correlated to one another.ResultsCognitive impairment was detected in 41.5% of the sample, and it was more frequent in patients with SPMS and PPMS (P = 0.002). Expanded Disability Status Scale scores and education were independent predictors of cognitive impairment. Principal component analysis identified seven clusters: attention and basic executive function (including information processing speed), planning and high-level executive function, verbal memory and language, executive and visuospatial performance time, fatigue-depression, visuospatial function, and basic attention and verbal/visual working memory. Mean scoring of components 2 (high-order executive functioning) and 3 (verbal memory-language) was higher in patients with RRMS than in those with PPMS (component 2) and SPMS (component 3).ConclusionMS is linked to multiple cognitive profiles and disturbances in different domains. This suggests that cognitive alterations in MS are heterogeneous and affect other domains in addition to information processing speed.

Background: Addenbrooke's Cognitive Examination III (ACE-III) is a cognitive test that has been validated for the diagnosis of cognitive disorders. The aim of this study was to provide normative data for the ACE-III for age, education and gender. Methods: The Spanish version of the ACE-III was administered to a group of 273 healthy subjects in a multicenter study in Spain. Correlation and determination coefficients for age, education and gender were estimated. The overlapping interval strategy and linear regression analyses were used to provide adjusted norms for demographic factors and to explore the potential influence of these factors in the performance of the test. Results: Age and education correlated significantly with the total score and with all the domains. Gender correlated only with the domains of attention and visuospatial skills. Norms for the total score and for cognitive domains (attention, memory, fluency, language, and visuospatial skills) are provided. Conclusion: This study confirms the influence of demographic factors (especially age and education) on the performance in the ACE-III and provides normative data for the Spanish version of the ACE-III.

Our conversion table between ACE-III and MMSE suggests that MMSE may be estimated based on the ACE-III score, which could be useful for clinical and research purposes.

Objective: Cognitive impairment is an important feature in multiple sclerosis (MS) and has been associated to several Magnetic Resonance Imaging (MRI) markers, but especially brain atrophy. However, the relationship between specific neuropsychological tests examining several cognitive functions and brain volumes has been little explored. Furthermore, because MS frequently damage subcortical regions, it may be an interesting model to examine the role of subcortical areas in cognitive functioning. Our aim was to identify correlations between specific brain regions and performance in neuropsychological tests evaluating different cognitive functions in a large series of patients with MS.Methods: A total of 375 patients were evaluated with a comprehensive neuropsychological battery and with MRI. Voxel-based morphometry was conducted to analyse the correlation between cognitive performance and gray matter damage, using Statistical Parametric Mapping with the toolboxes VBM8 and Lesion Segmentation Tool.Results: The following correlations were found: Corsi block-tapping test with right insula; Trail Making Test with caudate nucleus, thalamus, and several cortical regions including the posterior cingulate and inferior frontal gyrus; Symbol Digit Modalities Test with caudate nucleus, thalamus, posterior cingulate, several frontal regions, insula, and cerebellum; Stroop Color and Word Test with caudate nucleus and putamen; Free and Cued Selective Reminding Test and Rey-Osterrieth Complex Figure with thalamus, precuneus, and parahippocampal gyrus; Boston Naming Test with thalamus, caudate nucleus, and hippocampus; semantic verbal fluency with thalamus and phonological verbal fluency with caudate nucleus; and Tower of London test with frontal lobe, caudate nucleus, and posterior cingulate.Conclusion: Our study provides valuable data on the cortical and subcortical basis of cognitive function in MS. Neuropsychological tests mainly assessing attention and executive function showed a stronger association with caudate volume, while tests primarily evaluating memory were more strongly correlated with the thalamus. Other relevant regions were the posterior cingulate/precuneus, which were associated with attentional tasks, and several frontal regions, which were found to be correlated with planning and higher order executive functioning. Furthermore, our study supports the brain vertical organization of cognitive functioning, with the participation of the cortex, thalamus, basal ganglia, and cerebellum.

BackgroundThe Paced Auditory Serial Addition Test (PASAT) is a useful cognitive test in patients with multiple sclerosis (MS), assessing sustained attention and information processing speed. However, the neural underpinnings of performance in the test are controversial. We aimed to study the neural basis of PASAT performance by using structural magnetic resonance imaging (MRI) in a series of 242 patients with MS.MethodsPASAT (3-s) was administered together with a comprehensive neuropsychological battery. Global brain volumes and total T2-weighted lesion volumes were estimated. Voxel-based morphometry and lesion symptom mapping analyses were performed.ResultsMean PASAT score was 42.98 ± 10.44; results indicated impairment in 75 cases (31.0%). PASAT score was correlated with several clusters involving the following regions: bilateral precuneus and posterior cingulate, bilateral caudate and putamen, and bilateral cerebellum. Voxel-based lesion symptom mapping showed no significant clusters. Region of interest–based analysis restricted to white matter regions revealed a correlation with the left cingulum, corpus callosum, bilateral corticospinal tracts, and right arcuate fasciculus. Correlations between PASAT scores and global volumes were weak.ConclusionPASAT score was associated with regional volumes of the posterior cingulate/precuneus and several subcortical structures, specifically the caudate, putamen, and cerebellum. This emphasises the role of both cortical and subcortical structures in cognitive functioning and information processing speed in patients with MS.Electronic supplementary materialThe online version of this article (10.1186/s12883-018-1223-0) contains supplementary material, which is available to authorized users.

Background: Verbal fluency (VF) has been associated with several cognitive functions, but the cognitive processes underlying verbal fluency deficits in Multiple Sclerosis (MS) are controversial. Further knowledge about VF could be useful in clinical practice, because these tasks are brief, applicable, and reliable in MS patients. In this study, we aimed to evaluate the cognitive processes related to VF and to develop machine-learning algorithms to predict those patients with cognitive deficits using only VF-derived scores.Methods: Two hundred participants with MS were enrolled and examined using a comprehensive neuropsychological battery, including semantic and phonemic fluencies. Automatic linear modeling was used to identify the neuropsychological test predictors of VF scores. Furthermore, machine-learning algorithms (support vector machines, random forest) were developed to predict those patients with cognitive deficits using only VF-derived scores.Results: Neuropsychological tests associated with attention-executive functioning, memory, and language were the main predictors of the different fluency scores. However, the importance of memory was greater in semantic fluency and clustering scores, and executive functioning in phonemic fluency and switching. Machine learning algorithms predicted general cognitive impairment and executive dysfunction, with F1-scores over 67–71%.Conclusions: VF was influenced by many other cognitive processes, mainly including attention-executive functioning, episodic memory, and language. Semantic fluency and clustering were more explained by memory function, while phonemic fluency and switching were more related to executive functioning. Our study supports that the multiple cognitive components underlying VF tasks in MS could serve for screening purposes and the detection of executive dysfunction.

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