Rehabilitation of face-processing skills in an adolescent with prosopagnosia: Evaluation of an online perceptual training programme

In this paper we describe the case of EM: a female adolescent who acquired prosopagnosia following encephalitis at the age of eight. Initial neuropsychological and eye-movement investigations indicated that EM had profound difficulties in face perception as well as face recognition. EM underwent 14 weeks of perceptual training in an online programme that attempted to improve her ability to make fine-grained discriminations between faces. Following training, EM’s face perception skills had improved, and the effect generalized to untrained faces. Eye-movement analyses also indicated that EM spent more time viewing the inner facial features post-training. Examination of EM’s face recognition skills revealed an improvement in her recognition of personally-known faces when presented in a laboratory-based test, although the same gains were not noted in her everyday experiences with these faces. In addition, EM did not improve on a test assessing the recognition of newly encoded faces. One month after training, EM had maintained the improvement on the eye-tracking test, and to a lesser extent, her performance on the familiar faces test. This pattern of findings is interpreted as promising evidence that the programme can improve face perception skills, and with some adjustments, may at least partially improve face recognition skills

Reward components of feeding behavior are preserved during mouse aging

Eating behavior depends on associations between the sensory and energetic properties of foods. Healthful balance of these factors is a challenge for industrialized societies that have an abundance of food, food choices and food-related cues. Here, we were interested in whether appetitive conditioning changes as a function of age. Operant and pavlovian conditioning experiments (rewarding stimulus was a palatable food) in male mice (aged 3, 6, and 15 months) showed that implicit (non-declarative) memory remains intact during aging. Two other essential components of eating behavior, motivation and hedonic preference for rewarding foods, were also found not to be altered in aging mice. Specifically, hedonic responding by satiated mice to isocaloric foods of differing sensory properties (sucrose, milk) was similar in all age groups; importantly, however, this paradigm disclosed that older animals adjust their energy intake according to energetic need. Based on the assumption that the mechanisms that control feeding are conserved across species, it would appear that overeating and obesity in humans reflects a mismatch between ancient physiological mechanisms and today's cue-laden environment. The implication of the present results showing that aging does not impair the ability to learn stimulus-food associations is that the risk of overeating in response to food cues is maintained through to old age.This work was partly supported by European Commission's FP7 Initial Training Network NINA (Early Stage Researcher Fellowship to Mazen R. Harb) and Collaborative Project SwitchBox (to Osborne F. X. Almeida, Nuno Sousa and Joseph Zihl). The funding agencies had no influence over the design of experiments, interpretation of results or writing of the paper

Mood is a key determinant of cognitive performance in community-dwelling older adults: a cross-sectional analysis

First Online: 06 October 2012Identification of predictors of cognitive trajectories through the establishment of composite or single-parameter dimensional categories of cognition and mood may facilitate development of strategies to improve quality of life in the elderly. Participants (n = 487, aged 50+ years) were representative of the Portuguese population in terms of age, gender, and educational status. Cognitive and mood profiles were established using a battery of neurocognitive and psychological tests. Data were subjected to principal component analysis to identify core dimensions of cognition and mood, encompassing multiple test variables. Dimensions were correlated with age and with respect to gender, education, and occupational status. Cluster analysis was applied to isolate distinct patterns of cognitive performance and binary logistic regression models to explore interrelationships between aging, cognition, mood, and socio-demographic characteristics. Four main dimensions were identified: memory, executive function, global cognitive status, and mood. Based on these, strong and weak cognitive performers were distinguishable. Cluster analysis revealed further distinction within these two main categories into very good, good, poor, and very poor performers. Mood was the principal factor contributing to the separation between very good and good, as well as poor and very poor, performers. Clustering was also influenced by gender and education, albeit to a lesser extent; notably, however, female gender × lower educational background predicted significantly poorer cognitive performance with increasing age. Mood has a significant impact on the rate of cognitive decline in the elderly. Gender and educational level are early determinants of cognitive performance in later life.This work was funded by the European Commission (FP7) “SwitchBox” (Contract HEALTH-F2-2010-259772). NCS is supported by a SwitchBox post-doctoral fellowship. We are thankful to all study participants. The authors would like to acknowledge all colleagues who assisted with participant recruitment and evaluation

Patterns of Cognitive Performance in Healthy Ageing in Northern Portugal: A Cross-Sectional Analysis

Background: The Minho Integrative Neuroscience Database (MIND)-Ageing project aims to identify predictors of healthy cognitive ageing, including socio-demographic factors. In this exploratory analysis we sought to establish baseline cohorts for longitudinal assessment of age-related changes in cognition. Methods: The population sample (472 individuals) was strictly a convenient one, but similar to the Portuguese population in the age profile. Participants older than 55 years of age were included if they did not present defined disabling pathologies or dementia. A standardized clinical interview was conducted to assess medical history and a battery of neuropsychological tests was administered to characterize global cognition (Mini Mental State Examination), memory and executive functions (Selective Reminding Test; Stroop Color and Word Test; and Block Design subtest of the Wechsler Adult Intelligence Scale). Cross-sectional analysis of the neuropsychological performance with individual characteristics such as age, gender, educational level and setting (retirement home, senior university, day care center or community), allowed the establishment of baseline clusters for subsequent longitudinal studies. Results: Based on different socio-demographic characteristics, four main clusters that group distinctive patterns of cognitive performance were identified. The type of institution where the elders were sampled from, together with the level of formal education, were the major hierarchal factors for individual distribution in the four clusters. Of notice, education seems to delay the cognitive decline that is associated with age in all clusters. Conclusions: Social-inclusion/engagement and education seem to have a protective effect on mental ageing, although this effect may not be effective in the eldest elders

Demographic and social characteristics of the clusters identified by the multivariate regression tree analysis (T-cluster).

a<p>Only participants with no missing values in all variables were considered in the analysis (n = 327).</p>b<p>The mean age is not different between clusters 1 and 2 and between clusters 3 and 4 after a t-test.</p

Mini Mental State Examination test scores.

<p>Fitted and observed values on cognitive decay for the fifth percentile of the MMSE scores as function of age and level of education.</p

Cross-table with the number of elders (and row percentages) classified in the four clusters originated by the multivariate regression tree (T-cluster) and by the K-means clustering (C-cluster) analysis.

<p>Cross-table with the number of elders (and row percentages) classified in the four clusters originated by the multivariate regression tree (T-cluster) and by the K-means clustering (C-cluster) analysis.</p

Parameters estimated from the quasipoisson model fit.

<p>An age coefficient is shown for each T-cluster's cognitive test indicating if the scores on each test decrease or increase with age. Negative coefficients represent a decrease trend with age and positive coefficients a positive trend with age, as long as these coefficients are statistically significant.</p>a<p>A p-value below 0.05 means that the trend slope was statistically significant.</p

Neurocognitive assessments test scores.

<p>Overall (bold horizontal line) and cluster-specific (bars) geometric mean scores for each neurocognitive test. Clusters were identified by the multivariate regression tree analysis. The 95% confidence interval was estimated for the geometric mean for each cluster. Colors, Words and Word/Color indicate the Stroop conditions color naming, word reading and words in colors, respectively. Blocks designates the Block Design subtest of the Wechsler Intelligence. CLTR and LTS, both Selective Reminding Test assessments, refer to the total recalled items in the Consistent Long Term Retrieval and in the Long Term Storage, respectively.</p