Cognitive reserve (CR) is a potential mechanism to cope with brain damage. The aim of this study was to evaluate the effect of CR on a cognitive training (CT) in a group of patients with dementia. Eighty six participants with mild to moderate dementia were identified by their level of CR quantified by the CR Index questionnaire (CRIq) and underwent a cycle of CT. A global measure of cognition mini mental state examination (MMSE) was obtained before (T0) and after (T1) the training. Multiple linear regression analyses highlighted CR as a significant factor able to predict changes in cognitive performance after the CT. In particular, patients with lower CR benefited from a CT program more than those with high CR. These data show that CR can modulate the outcome of a CT program and that it should be considered as a predictive factor of neuropsychological rehabilitation training efficacy in people with dementia.

Neurological deficits following stroke are traditionally described as syndromes related to damage of a specific area or vascular territory. Recent studies indicate that, at the population level, post-stroke neurological impairments cluster in three sets of correlated deficits across different behavioral domains. To examine the reproducibility and specificity of this structure, we prospectively studied first-time stroke patients (n = 237) using a bedside, clinically applicable, neuropsychological assessment and compared the behavioral and anatomical results with those obtained from a different prospective cohort studied with an extensive neuropsychological battery. The behavioral assessment at one-week post stroke included the Oxford Cognitive Screen (OCS) and the National Institutes of Health Stroke Scale (NIHSS). A principal component analysis was used to reduce variables and describe behavioral variance across patients. Lesions were manually segmented on structural scans. The relationship between anatomy and behavior was analyzed using multivariate regression models. Three principal components (PC) explained ≈50% of the behavioral variance across subjects. PC1 loaded on language, calculation, praxis, right side neglect, and memory deficits; PC2 loaded on left motor, visual, and spatial neglect deficits; PC3 loaded on right motor deficits. These components matched those obtained with a more extensive battery. The underlying lesion anatomy was also similar. Neurological deficits following stroke are correlated in a low dimensional structure of impairment, related neither to the damage of a specific area or vascular territory. Rather they reflect widespread network impairment caused by focal lesions. These factors showed consistency across different populations, neurobehavioral batteries and, most importantly, can be described using a combination of clinically applicable batteries (NIHSS and OCS). They represent robust behavioral biomarkers for future stroke population studies.

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When looking at visual images, the eyes move to the most salient and behaviourally relevant objects. Saliency and semantic information significantly explain where people look. Less is known about the spatiotemporal properties of eye movements (i.e., how people look). We show that three latent variables explain 60% of eye movement dynamics of more than a hundred observers looking at hundreds of different natural images. The first component explaining 30% of variability loads on fixation duration, and it does not relate to image saliency or semantics; it approximates a power-law distribution of gaze steps, an intrinsic dynamic measure, and identifies observers with two viewing styles: static and dynamic. Notably, these viewing styles were also identified when observers look at a blank screen. These results support the importance of endogenous processes such as intrinsic dynamics to explain eye movement spatiotemporal properties.