The influence of learning on evolution: a mathematical framework.

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

Enhanced visuospatial memory following intracerebroventricular administration of nerve growth factor

The present work assessed the effects of intracerebroventricular injections of rh recombined human nerve growth factor (rh NGF) (5 micrograms/2.5 microl) at postnatal days 12 and 13 upon the development of spatial learning capacities. The treated rats were trained at the age of 22 days to escape onto an invisible platform at a fixed position in space in a Morris navigation task. For half of the subjects, the training position was also cued, a procedure aimed at facilitating escape and at reducing attention to the distant spatial cues. Later, at the age of 6 months, all the rats were trained in a radial-arm maze task. Treatment effects were found in both immature and adult rats. The injection of NGF improved the performance in the Morris navigation task in both training conditions. There was a significant reduction in the escape latency and an increased bias toward the training platform quadrant during probe trials. The most consistent effect was the precocious development of an adult-like spatial memory. In the radial-arm maze, the NGF-treated rats made significantly fewer reentries than vehicle rats and this effect was particularly marked in the treated female rats. Taken together, these experiments reveal that the development and the maintenance of an accurate spatial representation are tightly related to the development of brain structures facilitated by the action of NGF. Moreover, these experiments demonstrate that an acute pharmacological treatment that leads to a transient modification in the choline acetyltransferase activity can induce a behavioral change long after the treatment.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Electrical neuroimaging of memory discrimination based on single-trial multisensory learning.

Multisensory experiences influence subsequent memory performance and brain responses. Studies have thus far concentrated on semantically congruent pairings, leaving unresolved the influence of stimulus pairing and memory sub-types. Here, we paired images with unique, meaningless sounds during a continuous recognition task to determine if purely episodic, single-trial multisensory experiences can incidentally impact subsequent visual object discrimination. Psychophysics and electrical neuroimaging analyses of visual evoked potentials (VEPs) compared responses to repeated images either paired or not with a meaningless sound during initial encounters. Recognition accuracy was significantly impaired for images initially presented as multisensory pairs and could not be explained in terms of differential attention or transfer of effects from encoding to retrieval. VEP modulations occurred at 100-130ms and 270-310ms and stemmed from topographic differences indicative of network configuration changes within the brain. Distributed source estimations localized the earlier effect to regions of the right posterior temporal gyrus (STG) and the later effect to regions of the middle temporal gyrus (MTG). Responses in these regions were stronger for images previously encountered as multisensory pairs. Only the later effect correlated with performance such that greater MTG activity in response to repeated visual stimuli was linked with greater performance decrements. The present findings suggest that brain networks involved in this discrimination may critically depend on whether multisensory events facilitate or impair later visual memory performance. More generally, the data support models whereby effects of multisensory interactions persist to incidentally affect subsequent behavior as well as visual processing during its initial stages.

Construire sa vie (Life designing): Un paradigme pour l'orientation au 21e siècle

La nouvelle organisation sociale du travail du début du 21e siècle pose une série de questions et lance de nombreux défis aux spécialistes de l'accompagnement en orientation professionnelle. Compte tenu de la mondialisation du conseil en orientation, c'est dans un cadre international que nous avons décidé d'aborder ces questions, puis de formuler des réponses potentiellement innovantes. Cette approche permet d'éviter les difficultés que soulève la création de modèles et de méthodes dans un pays donné en tentant ensuite de les exporter dans d'autres, où ils doivent être adaptés pour être utilisés. Cet article présente le premier résultat tangible de cette collaboration : un modèle et des méthodes d'accompagnement des personnes. Le modèle « Construire sa vie », destiné à des interventions d'accompagnement en orientation se fonde sur cinq présupposés concernant les personnes et leur vie professionnelle : des possibilités liées aux contextes, des processus dynamiques, une progression non linéaire, des perspectives multiples et des configurations individuelles. En partant de ces présupposés, nous avons bâti un modèle en contexte, se réclamant de l'épistémologie du constructionnisme social, reconnaissant en particulier que les connaissances et l'identité d'un individu sont le produit d'interactions sociales et que le sens est co-construit, via la médiation du discours. Le cadre général « construire sa vie » s'appuie sur les théories de la construction de soi (Guichard, 2005) et de la construction des parcours professionnels (Savickas, 2005), qui décrivent les conduites d'orientation et leurs développements. Ce cadre concerne toute la vie, il est holiste, tient compte des contextes et est préventif.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

L'orientation du patient souffrant d'un syndrome douloureux abdominal aigu a domicile [Hospitalisation criteria for the acute abdominal pain patient seen at home or in an ambulatory setting].

Dealing at patient's home with an acute abdominal pain may be particularly challenging for the primary care physician. In such a clinical situation, the part of laboratory and radiological investigations is increasing in the diagnostic process. The decision to keep the patient at home based on a clinical evaluation alone may represent a great medical responsibility for the physician. Emergency departments (ED) are of course in charge of investigating such patients with a wide panel of investigation techniques. But these structures are chronically overcrowded resulting frequently in long and difficult periods of waiting. Based on a literature review, a description of useful clinical symptoms and signs is summarized and should help the decision process for the orientation of the patient.

Learning ability and longevity: a symmetrical evolutionary trade-off in Drosophila.

Learning ability can be substantially improved by artificial selection in animals ranging from Drosophila to rats. Thus these species have not used their evolutionary potential with respect to learning ability, despite intuitively expected and experimentally demonstrated adaptive advantages of learning. This suggests that learning is costly, but this notion has rarely been tested. Here we report correlated responses of life-history traits to selection for improved learning in Drosophila melanogaster. Replicate populations selected for improved learning lived on average 15% shorter than the corresponding unselected control populations. They also showed a minor reduction in fecundity late in life and possibly a minor increase in dry adult mass. Selection for improved learning had no effect on egg-to-adult viability, development rate, or desiccation resistance. Because shortened longevity was the strongest correlated response to selection for improved learning, we also measured learning ability in another set of replicate populations that had been selected for extended longevity. In a classical olfactory conditioning assay, these long-lived flies showed an almost 40% reduction in learning ability early in life. This effect disappeared with age. Our results suggest a symmetrical evolutionary trade-off between learning ability and longevity in Drosophila.