Ibotenate Lesions of Hippocampus and/or Subiculum: Dissociating Components of Allocentric Spatial Learning

This study examined the effects of ibotenic acid-induced lesions of the hippocampus, subiculum and hippocampus +/- subiculum upon the capacity of rats to learn and perform a series of allocentric spatial learning tasks in an open-field water maze. The lesions were made by infusing small volumes of the neurotoxin at a total of 26 (hippocampus) or 20 (subiculum) sites intended to achieve complete target cell loss but minimal extratarget damage. The regional extent and axon-sparing nature of these lesions was evaluated using both cresyl violet and Fink - Heimer stained sections. The behavioural findings indicated that both the hippocampus and subiculum lesions caused impairment to the initial postoperative acquisition of place navigation but did not prevent eventual learning to levels of performance almost as effective as those of controls. However, overtraining of the hippocampus + subiculum lesioned rats did not result in significant place learning. Qualitative observations of the paths taken to find a hidden escape platform indicated that different strategies were deployed by hippocampal and subiculum lesioned groups. Subsequent training on a delayed matching to place task revealed a deficit in all lesioned groups across a range of sample choice intervals, but the subiculum lesioned group was less impaired than the group with the hippocampal lesion. Finally, unoperated control rats given both the initial training and overtraining were later given either a hippocampal lesion or sham surgery. The hippocampal lesioned rats were impaired during a subsequent retention/relearning phase. Together, these findings suggest that total hippocampal cell loss may cause a dual deficit: a slower rate of place learning and a separate navigational impairment. The prospect of unravelling dissociable components of allocentric spatial learning is discussed.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Gambling against neglect: unconscious spatial biases induced by reward reinforcement in healthy people and brain-damaged patients.

Orienting attention in space recruits fronto-parietal networks whose damage results in unilateral spatial neglect. However, attention orienting may also be governed by emotional and motivational factors; but it remains unknown whether these factors act through a modulation of the fronto-parietal attentional systems or distinct neural pathways. Here we asked whether attentional orienting is affected by learning about the reward value of targets in a visual search task, in a spatially specific manner, and whether these effects are preserved in right-brain damaged patients with left spatial neglect. We found that associating rewards with left-sided (but not right-sided) targets during search led to progressive exploration biases towards left space, in both healthy people and neglect patients. Such spatially specific biases occurred even without any conscious awareness of the asymmetric reward contingencies. These results show that reward-induced modulations of space representation are preserved despite a dysfunction of fronto-parietal networks associated with neglect, and therefore suggest that they may arise through spared subcortical networks directly acting on sensory processing and/or oculomotor circuits. These effects could be usefully exploited for potentiating rehabilitation strategies in neglect patients.

Effect of spatial processes on the evolution of ecological niches and dispersal in metacommunity systems

RésuméLa coexistence de nombreuses espèces différentes a de tout temps intrigué les biologistes. La diversité et la composition des communautés sont influencées par les perturbations et l'hétérogénéité des conditions environnementales. Bien que dans la nature la distribution spatiale des conditions environnementales soit généralement autocorrélée, cet aspect est rarement pris en compte dans les modèles étudiant la coexistence des espèces. Dans ce travail, nous avons donc abordé, à l'aide de simulations numériques, la coexistence des espèces ainsi que leurs caractéristiques au sein d'un environnement autocorrélé.Afin de prendre en compte cet élément spatial, nous avons développé un modèle de métacommunauté (un ensemble de communautés reliées par la dispersion des espèces) spatialement explicite. Dans ce modèle, les espèces sont en compétition les unes avec les autres pour s'établir dans un nombre de places limité, dans un environnement hétérogène. Les espèces sont caractérisées par six traits: optimum de niche, largeur de niche, capacité de dispersion, compétitivité, investissement dans la reproduction et taux de survie. Nous nous sommes particulièrement intéressés à l'influence de l'autocorrélation spatiale et des perturbations sur la diversité des espèces et sur les traits favorisés dans la métacommunauté. Nous avons montré que l'autocorrélation spatiale peut avoir des effets antagonistes sur la diversité, en fonction du taux de perturbations considéré. L'influence de l'autocorrélation spatiale sur la capacité de dispersion moyenne dans la métacommunauté dépend également des taux de perturbations et survie. Nos résultats ont aussi révélé que de nombreuses espèces avec différents degrés de spécialisation (i.e. différentes largeurs de niche) peuvent coexister. Toutefois, les espèces spécialistes sont favorisées en absence de perturbations et quand la dispersion est illimitée. A l'opposé, un taux élevé de perturbations sélectionne des espèces plus généralistes, associées avec une faible compétitivité.L'autocorrélation spatiale de l'environnement, en interaction avec l'intensité des perturbations, influence donc de manière considérable la coexistence ainsi que les caractéristiques des espèces. Ces caractéristiques sont à leur tour souvent impliquées dans d'importants processus, comme le fonctionnement des écosystèmes, la capacité des espèces à réagir aux invasions, à la fragmentation de l'habitat ou aux changements climatiques. Ce travail a permis une meilleure compréhension des mécanismes responsables de la coexistence et des caractéristiques des espèces, ce qui est crucial afin de prédire le devenir des communautés naturelles dans un environnement changeant.AbstractUnderstanding how so many different species can coexist in nature is a fundamental and long-standing question in ecology. Community diversity and composition are known to be influenced by heterogeneity in environmental conditions and disturbance. Though in nature the spatial distribution of environmental conditions is frequently autocorrelated, this aspect is seldom considered in models investigating species coexistence. In this work, we thus addressed several questions pertaining to species coexistence and composition in spatially autocorrelated environments, with a numerical simulations approach.To take into account this spatial aspect, we developed a spatially explicit model of metacommunity (a set of communities linked by dispersal of species). In this model, species are trophically equivalent, and compete for space in a heterogeneous environment. Species are characterized by six life-history traits: niche optimum, niche breadth, dispersal, competitiveness, reproductive investment and survival rate. We were particularly interested in the influence of environmental spatial autocorrelation and disturbance on species diversity and on the traits of the species favoured in the metacommunity. We showed that spatial autocorrelation can have antagonistic effects on diversity depending on disturbance rate. Similarly, spatial autocorrelation interacted with disturbance rate and survival rate to shape the mean dispersal ability observed in the metacommunity. Our results also revealed that many species with various degrees of specialization (i.e. different niche breadths) can coexist together. However specialist species were favoured in the absence of disturbance, and when dispersal was unlimited. In contrast, high disturbance rate selected for more generalist species, associated with low competitive ability.The spatial structure of the environment, together with disturbance and species traits, thus strongly impacts species diversity and, more importantly, species composition. Species composition is known to affect several important metacommunity properties such as ecosystem functioning, resistance and reaction to invasion, to habitat fragmentation and to climate changes. This work allowed a better understanding of the mechanisms responsible for species composition, which is of crucial importance to predict the fate of natural metacommunities in changing environments

Spatial predictions of land-use transitions and associated threats to biodiversity: the case of forest regrowth in mountain grasslands

Question Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location Western Swiss Alps (4003210m a.s.l.). Methods We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for the management and conservation of biodiversity at intermediate elevations. Conclusions Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

Glucagon-like peptide-1 increases beta-cell glucose competence and proliferation by translational induction of insulin-like growth factor-1 receptor expression.

Glucagon-like peptide-1 (GLP-1) protects beta-cells against apoptosis, increases their glucose competence, and induces their proliferation. We previously demonstrated that the anti-apoptotic effect was mediated by an increase in insulin-like growth factor-1 receptor (IGF-1R) expression and signaling, which was dependent on autocrine secretion of insulin-like growth factor 2 (IGF-2). Here, we further investigated how GLP-1 induces IGF-1R expression and whether the IGF-2/IGF-1R autocrine loop is also involved in mediating GLP-1-increase in glucose competence and proliferation. We show that GLP-1 up-regulated IGF-1R expression by a protein kinase A-dependent translational control mechanism, whereas isobutylmethylxanthine, which led to higher intracellular accumulation of cAMP than GLP-1, increased both IGF-1R transcription and translation. We then demonstrated, using MIN6 cells and primary islets, that the glucose competence of these cells was dependent on the level of IGF-1R expression and on IGF-2 secretion. We showed that GLP-1-induced primary beta-cell proliferation was suppressed by Igf-1r gene inactivation and by IGF-2 immunoneutralization or knockdown. Together our data show that regulation of beta-cell number and function by GLP-1 depends on the cAMP/protein kinase A mediated-induction of IGF-1R expression and the increased activity of an IGF-2/IGF-1R autocrine loop.

Auditory-somatosensory multisensory interactions in humans: dissociating detection and spatial discrimination.

Simple reaction times (RTs) to auditory-somatosensory (AS) multisensory stimuli are facilitated over their unisensory counterparts both when stimuli are delivered to the same location and when separated. In two experiments we addressed the possibility that top-down and/or task-related influences can dynamically impact the spatial representations mediating these effects and the extent to which multisensory facilitation will be observed. Participants performed a simple detection task in response to auditory, somatosensory, or simultaneous AS stimuli that in turn were either spatially aligned or misaligned by lateralizing the stimuli. Additionally, we also informed the participants that they would be retrogradely queried (one-third of trials) regarding the side where a given stimulus in a given sensory modality was presented. In this way, we sought to have participants attending to all possible spatial locations and sensory modalities, while nonetheless having them perform a simple detection task. Experiment 1 provided no cues prior to stimulus delivery. Experiment 2 included spatially uninformative cues (50% of trials). In both experiments, multisensory conditions significantly facilitated detection RTs with no evidence for differences according to spatial alignment (though general benefits of cuing were observed in Experiment 2). Facilitated detection occurs even when attending to spatial information. Performance with probes, quantified using sensitivity (d'), was impaired following multisensory trials in general and significantly more so following misaligned multisensory trials. This indicates that spatial information is not available, despite being task-relevant. The collective results support a model wherein early AS interactions may result in a loss of spatial acuity for unisensory information.

Hepatic glucose sensing is required to preserve β cell glucose competence.

Liver glucose metabolism plays a central role in glucose homeostasis and may also regulate feeding and energy expenditure. Here we assessed the impact of glucose transporter 2 (Glut2) gene inactivation in adult mouse liver (LG2KO mice). Loss of Glut2 suppressed hepatic glucose uptake but not glucose output. In the fasted state, expression of carbohydrate-responsive element-binding protein (ChREBP) and its glycolytic and lipogenic target genes was abnormally elevated. Feeding, energy expenditure, and insulin sensitivity were identical in LG2KO and control mice. Glucose tolerance was initially normal after Glut2 inactivation, but LG2KO mice exhibited progressive impairment of glucose-stimulated insulin secretion even though β cell mass and insulin content remained normal. Liver transcript profiling revealed a coordinated downregulation of cholesterol biosynthesis genes in LG2KO mice that was associated with reduced hepatic cholesterol in fasted mice and reduced bile acids (BAs) in feces, with a similar trend in plasma. We showed that chronic BAs or farnesoid X receptor (FXR) agonist treatment of primary islets increases glucose-stimulated insulin secretion, an effect not seen in islets from Fxr-/- mice. Collectively, our data show that glucose sensing by the liver controls β cell glucose competence and suggest BAs as a potential mechanistic link.

Spatial distribution of motor units recruited during electrical stimulation of the quadriceps muscle versus the femoral nerve.

INTRODUCTION: In this study we investigated differences in the spatial recruitment of motor units (MUs) in the quadriceps when electrical stimulation is applied over the quadriceps belly versus the femoral nerve. METHODS: M-waves and mechanical twitches were evoked using over-the-quadriceps and femoral nerve stimulation of gradually increasing intensity from 22 young, healthy subjects. Spatial recruitment was investigated using recruitment curves of M-waves recorded from the vastus medialis (VM) and vastus lateralis (VL) and of twitches recorded from the quadriceps. RESULTS: At maximal stimulation intensity (Imax), no differences were found between nerve and over-the-quadriceps stimulation. At submaximal intensities, VL M-wave amplitude was higher for over-the-quadriceps stimulation at 40% Imax, and peak twitch force was greater for nerve stimulation at 60% and 80% Imax. CONCLUSIONS: For the VM, MU spatial recruitment during nerve and over-the-quadriceps stimulation of increasing intensity occurred in a similar manner, whereas significant differences were observed for the VL. Muscle Nerve, 2013.