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The study of biological point-light displays (PLDs) has fascinated researchers for more than 40 years. However, the mechanisms underlying PLD perception remain unclear, partly due to difficulties with precisely controlling and transforming PLD sequences. Furthermore, little agreement exists regarding how transformations are performed. This article introduces a new free-access program called PLAViMoP (Point-Light Display Visualization and Modification Platform) and presents the algorithms for PLD transformations actually included in the software. PLAViMoP fulfills two objectives. First, it standardizes and makes clear many classical spatial and kinematic transformations described in the PLD literature. Furthermore, given its optimized interface, PLAViMOP makes these transformations easy and fast to achieve. Overall, PLAViMoP could directly help scientists avoid technical difficulties and make possible the use of PLDs for nonacademic applications.

The objective of this study was to examine age-related effects on behavioral performance and metabolic activity of the prefrontal cortex (PFC) in a dual-task paradigm involving fine-motor control and executive-function control. Thirty-one adults (20 ± 1.1 years) and 33 older adults (70.7 ± 5.1 years) performed, separately and then concurrently, a modified Fitts task on targets of different sizes (Index of Difficulty: ID = 3; 4; 5 bits) and the random number generation task (RNG). Movement time (MT) and count score (CS) were the dependent variables for the modified Fitts task and the RNG task, respectively. Relative changes in concentrations of oxyhemoglobin [HbO2] and deoxyhemoglobin [HHb] were recorded continuously on the left and right PFCs, with near-infrared spectroscopy (Oxymon MkIII-Artinis) with an acquisition rate of 10 Hz. Our results showed large motor dual-task cost in seniors compared to young adults. Regarding hemodynamic activity, we have observed a prominent activation of the PFC in the young adults compared to the seniors during the dual-task condition.

International audience; Background:The brain-derived neurotrophic factor (BDNF) concentration is highest in the hippocampus comparedwith that in other brain structures and affects episodic memory, a cognitive function that is impaired in olderadults. According to the neurotrophic hypothesis, BDNF released during physical activity enhances brain plasticity andconsequently brain health. However, even if the physical activity level is involved in the secretion of neurotrophin, thisprotein is also under the control of a specific gene. The aim of the present study was to examine the effect of theinteraction between physical activity and BDNF Val66Met(rs6265), a genetic polymorphism, on episodic memory.Methods:Two hundred and five volunteers aged 55 and older with a Mini Mental State Examination score≥24participated in this study. Four groups of participants were established according to their physical activity level andpolymorphism BDNF profile (Active Val homozygous, Inactive Val homozygous, Active Met carriers, Inactive Met carriers).Episodic memory was evaluated based on the delayed recall of the Logical Memory test of the MEM III battery.Results:As expected, the physical activity level interacted with BDNF polymorphism to affect episodic memoryperformance (p< .05). The active Val homozygous participants significantly outperformed the active Met carriers andinactive Val homozygous participants.Conclusion:This study clearly demonstrates an interaction between physical activity andBDNF Val66Metpolymorphismthat affects episodic memory in the elderly and confirms that physical activity contributes to the neurotrophic mechanismimplicated in cognitive health. The interaction shows that only participants with Val/Val polymorphism benefited fromphysical activity

The serial analysis of gene expression (SAGE) is a powerful method to compare gene expression of mRNA populations. To provide quantitative expression levels on a genome-wide scale, the Cancer Genome Anatomy Project (CGAP) uses SAGE. Over 7 million SAGE tags, from 171 human cell types have been assembled. The growing number of laboratories involved in SAGE research necessitates the use of software that provides statistical analysis of raw data, allowing the rapid visualization and interpretation of results. We have created the first simple tool that performs statistical analysis on SAGE data, identifies the tags differentially expressed and shows the results in a scatter plot. It is freely available and accessible at http://bioserv.rpbs.jussieu.fr/websage/index.php.