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.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

Cardio respiratory activity in high-anxious vs. low-anxious professional music students before and during performance

Questionnaire studies indicate that high-anxious musicians may suffer from hyperventilation symptoms before and/or during performance. Reported symptoms include amongst others shortness of breath, fast or deep breathing, dizziness and thumping heart. However, no study has yet tested if these self-reported symptoms reflect actual cardio respiratory changes. Disturbances in breathing patterns and hyperventilation may contribute to the often observed poorer performance of anxious musicians under stressful performance situations. The main goal of this study is to determine if music performance anxiety is manifest physiologically in specific correlates of cardio respiratory activity. We studied 74 professional music students divided into two groups (i.e. high-anxious and lowanxious) based on their self-reported performance anxiety in three distinct situations: baseline, private performance (without audience), public performance (with audience). We measured a) breathing patterns, end-tidal carbon dioxide (EtCO2, a good non-invasive estimator for hyperventilation), ECG and b) self-perceived emotions and self-perceived physiological activation. The poster will concentrate on the preliminary results of this study. The focus will be a) on differences between high-anxious and low-anxious musicians regarding breaths per minute and heart rate and b) on the response coherence between self-perceived palpitations and actual heart rate.

Influence of learning on range expansion and adaptation to novel habitats.

Learning has been postulated to 'drive' evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual-based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically-based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Intrahippocampal cholinergic grafts in aged rats compensate impairments in a radial maze and in a place learning task

Age-related cognitive impairments were studied in rats kept in semi-enriched conditions during their whole life, and tested during ontogeny and adult life in various classical spatial tasks. In addition, the effect of intrahippocampal grafts of fetal septal-diagonal band tissue, rich in cholinergic neurons, was studied in some of these subjects. The rats received bilateral cell suspensions when aged 23-24 months. Starting 4 weeks after grafting, they were trained during 5 weeks in an 8-arm maze made of connected plexiglass tunnels. No age-related impairment was detected during the first eight trials, when the maze shape was that of a classical radial maze in which the rats had already been trained when young. The older rats were impaired when the task was made more difficult by rendering two arms parallel to each other. They developed an important neglect of one of the parallel tunnels resulting in a high amount of errors before completion of the task. In addition, the old rats developed a systematic response pattern of visits to adjacent arms in a sequence, which was not observed in the younger subjects. None of these behaviours were observed in the old rats with a septal transplant. Sixteen weeks after grafting, another experiment was conducted in a homing hole board task. Rats were allowed to escape from a large circular arena through one hole out of many, and to reach home via a flexible tube under the table. The escape hole was at a fixed position according to distant room cues, and olfactory cues were made irrelevant by rotating the table between the trials. An additional cue was placed on the escape position. No age-related difference in escape was observed during training. During a probe trial with no hole connected and no proximal cue present, the old untreated rats were less clearly focussed on the training sector than were either the younger or the grafted old subjects. Taken together, these experiments indicate that enriched housing conditions and spatial training during adult life do not protect against all age-related deterioration in spatial ability. However, it might be that the considerable improvement observed in the grafted subjects results from an interaction between the graft treatment and the housing conditions.

Effects of inbreeding on aversive learning in Drosophila.

Inbreeding adversely affects life history traits as well as various other fitness-related traits, but its effect on cognitive traits remains largely unexplored, despite their importance to fitness of many animals under natural conditions. We studied the effects of inbreeding on aversive learning (avoidance of an odour previously associated with mechanical shock) in multiple inbred lines of Drosophila melanogaster derived from a natural population through up to 12 generations of sib mating. Whereas the strongly inbred lines after 12 generations of inbreeding (0.75<F<0.93) consistently showed reduced egg-to-adult viability (on average by 28%), the reduction in learning performance varied among assays (average=18% reduction), being most pronounced for intermediate conditioning intensity. Furthermore, moderately inbred lines (F=0.38) showed no detectable decline in learning performance, but still had reduced egg-to-adult viability, which indicates that overall inbreeding effects on learning are mild. Learning performance varied among strongly inbred lines, indicating the presence of segregating variance for learning in the base population. However, the learning performance of some inbred lines matched that of outbred flies, supporting the dominance rather than the overdominance model of inbreeding depression for this trait. Across the inbred lines, learning performance was positively correlated with the egg-to-adult viability. This positive genetic correlation contradicts a trade-off observed in previous selection experiments and suggests that much of the genetic variation for learning is owing to pleiotropic effects of genes affecting functions related to survival. These results suggest that genetic variation that affects learning specifically (rather than pleiotropically through general physiological condition) is either low or mostly due to alleles with additive (semi-dominant) effects.

Absence of snapshot memory of the target view interferes with place navigation learning by rats in the water maze

Contribution of visual and nonvisual mechanisms to spatial behavior of rats in the Morris water maze was studied with a computerized infrared tracking system, which switched off the room lights when the subject entered the inner circular area of the pool with an escape platform. Naive rats trained under light-dark conditions (L-D) found the escape platform more slowly than rats trained in permanent light (L). After group members were swapped, the L-pretrained rats found under L-D conditions the same target faster and eventually approached latencies attained during L navigation. Performance of L-D-trained rats deteriorated in permanent darkness (D) but improved with continued D training. Thus L-D navigation improves gradually by procedural learning (extrapolation of the start-target azimuth into the zero-visibility zone) but remains impaired by lack of immediate visual feedback rather than by absence of the snapshot memory of the target view.

Psychophysiological activation during preparation, performance, and recovery in high- and low-anxious music students

The present study provides a comprehensive view of (a) the time dynamics of the psychophysiological responding in performing music students (n = 66) before, during, and after a private and a public performance and (b) the moderating effect of music performance anxiety (MPA). Heart rate (HR), minute ventilation (VE), and all affective and somatic self-report variables increased in the public session compared to the private session. Furthermore, the activation of all variables was stronger during the performances than before or after. Differences between phases were larger in the public than in the private session for HR, VE, total breath duration, anxiety, and trembling. Furthermore, while higher MPA scores were associated with higher scores and with larger changes between sessions and phases for self-reports, this association was less coherent for physiological variables. Finally, self-reported intra-individual performance improvements or deteriorations were not associated with MPA. This study makes a novel contribution by showing how the presence of an audience influences low- and high-anxious musicians' psychophysiological responding before, during and after performing. Overall, the findings are more consistent with models of anxiety that emphasize the importance of cognitive rather than physiological factors in MPA.