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.

Textural controls on induced polarization and permeability in granular media

The spatial resolution visualized with hydrological models and the conceptualized images of subsurface hydrological processes often exceed resolution of the data collected with classical instrumentation at the field scale. In recent years it was possible to increasingly diminish the inherent gap to information from point like field data through the application of hydrogeophysical methods at field-scale. With regards to all common geophysical exploration techniques, electric and electromagnetic methods have arguably to greatest sensitivity to hydrologically relevant parameters. Of particular interest in this context are induced polarisation (IP) measurements, which essentially constrain the capacity of a probed subsurface region to store an electrical charge. In the absence of metallic conductors the IP- response is largely driven by current conduction along the grain surfaces. This offers the perspective to link such measurements to the characteristics of the solid-fluid-interface and thus, at least in unconsolidated sediments, should allow for first-order estimates of the permeability structure.¦While the IP-effect is well explored through laboratory experiments and in part verified through field data for clay-rich environments, the applicability of IP-based characterizations to clay-poor aquifers is not clear. For example, polarization mechanisms like membrane polarization are not applicable in the rather wide pore-systems of clay free sands, and the direct transposition of Schwarz' theory relating polarization of spheres to the relaxation mechanism of polarized cells to complex natural sediments yields ambiguous results.¦In order to improve our understanding of the structural origins of IP-signals in such environments as well as their correlation with pertinent hydrological parameters, various laboratory measurements have been conducted. We consider saturated quartz samples with a grain size spectrum varying from fine sand to fine gravel, that is grain diameters between 0,09 and 5,6 mm, as well as corresponding pertinent mixtures which can be regarded as proxies for widespread alluvial deposits. The pore space characteristics are altered by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples, while keeping any electrochemical variability during the measurements as small as possible. The results do not follow simple assumptions on relationships to single parameters such as grain size. It was found that the complexity of natural occurring media is not yet sufficiently represented when modelling IP. At the same time simple correlation to permeability was found to be strong and consistent. Hence, adaptations with the aim of better representing the geo-structure of natural porous media were applied to the simplified model space used in Schwarz' IP-effect-theory. The resulting semi- empiric relationship was found to more accurately predict the IP-effect and its relation to the parameters grain size and permeability. If combined with recent findings about the effect of pore fluid electrochemistry together with advanced complex resistivity tomography, these results will allow us to picture diverse aspects of the subsurface with relative certainty. Within the framework of single measurement campaigns, hydrologiste can than collect data with information about the geo-structure and geo-chemistry of the subsurface. However, additional research efforts will be necessary to further improve the understanding of the physical origins of IP-effect and minimize the potential for false interpretations.¦-¦Dans l'étude des processus et caractéristiques hydrologiques des subsurfaces, la résolution spatiale donnée par les modèles hydrologiques dépasse souvent la résolution des données du terrain récoltées avec des méthodes classiques d'hydrologie. Récemment il est possible de réduire de plus en plus cet divergence spatiale entre modèles numériques et données du terrain par l'utilisation de méthodes géophysiques, notamment celles géoélectriques. Parmi les méthodes électriques, la polarisation provoquée (PP) permet de représenter la capacité des roches poreuses et des sols à stocker une charge électrique. En l'absence des métaux dans le sous-sol, cet effet est largement influencé par des caractéristiques de surface des matériaux. En conséquence les mesures PP offrent une information des interfaces entre solides et fluides dans les matériaux poreux que nous pouvons lier à la perméabilité également dirigée par ces mêmes paramètres. L'effet de la polarisation provoquée à été étudié dans différentes études de laboratoire, ainsi que sur le terrain. A cause d'une faible capacité de polarisation des matériaux sableux, comparé aux argiles, leur caractérisation par l'effet-PP reste difficile a interpréter d'une manière cohérente pour les environnements hétérogènes.¦Pour améliorer les connaissances sur l'importance de la structure du sous-sol sableux envers l'effet PP et des paramètres hydrologiques, nous avons fait des mesures de laboratoire variées. En détail, nous avons considéré des échantillons sableux de quartz avec des distributions de taille de grain entre sables fins et graviers fins, en diamètre cela fait entre 0,09 et 5,6 mm. Les caractéristiques de l'espace poreux sont changées en modifiant (i) la distribution de taille des grains, (ii) le degré de compaction, et (iii) le niveau d'hétérogénéité dans la distribution de taille de grains. En suite nous étudions comment ces changements influencent l'effet-PP, la perméabilité et la surface spécifique des échantillons. Les paramètres électrochimiques sont gardés à un minimum pendant les mesures. Les résultats ne montrent pas de relation simple entre les paramètres pétro-physiques comme par exemples la taille des grains. La complexité des media naturels n'est pas encore suffisamment représenté par les modèles des processus PP. Néanmoins, la simple corrélation entre effet PP et perméabilité est fort et consistant. En conséquence la théorie de Schwarz sur l'effet-PP a été adapté de manière semi-empirique pour mieux pouvoir estimer la relation entre les résultats de l'effet-PP et les paramètres taille de graines et perméabilité. Nos résultats concernant l'influence de la texture des matériaux et celles de l'effet de l'électrochimie des fluides dans les pores, permettront de visualiser des divers aspects du sous-sol. Avec des telles mesures géo-électriques, les hydrologues peuvent collectionner des données contenant des informations sur la structure et la chimie des fluides des sous-sols. Néanmoins, plus de recherches sur les origines physiques de l'effet-PP sont nécessaires afin de minimiser le risque potentiel d'une mauvaise interprétation des données.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

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.

Multilocus phylogeography of the common lizard Zootoca vivipara at the Ibero-Pyrenean suture zone reveals lowland barriers and high-elevation introgression.

BACKGROUND: The geographic distribution of evolutionary lineages and the patterns of gene flow upon secondary contact provide insight into the process of divergence and speciation. We explore the evolutionary history of the common lizard Zootoca vivipara (= Lacerta vivipara) in the Iberian Peninsula and test the role of the Pyrenees and the Cantabrian Mountains in restricting gene flow and driving lineage isolation and divergence. We also assess patterns of introgression among lineages upon secondary contact, and test for the role of high-elevation trans-mountain colonisations in explaining spatial patterns of genetic diversity. We use mtDNA sequence data and genome-wide AFLP loci to reconstruct phylogenetic relationships among lineages, and measure genetic structure RESULTS: The main genetic split in mtDNA corresponds generally to the French and Spanish sides of the Pyrenees as previously reported, in contrast to genome-wide AFLP data, which show a major division between NW Spain and the rest. Both types of markers support the existence of four distinct and geographically congruent genetic groups, which are consistent with major topographic barriers. Both datasets reveal the presence of three independent contact zones between lineages in the Pyrenean region, one in the Basque lowlands, one in the low-elevation mountains of the western Pyrenees, and one in the French side of the central Pyrenees. The latter shows genetic evidence of a recent, high-altitude trans-Pyrenean incursion from Spain into France. CONCLUSIONS: The distribution and age of major lineages is consistent with a Pleistocene origin and a role for both the Pyrenees and the Cantabrian Mountains in driving isolation and differentiation of Z. vivipara lineages at large geographic scales. However, mountain ranges are not always effective barriers to dispersal, and have not prevented a recent high-elevation trans-Pyrenean incursion that has led to asymmetrical introgression among divergent lineages. Cytonuclear discordance in patterns of genetic structure and introgression at contact zones suggests selection may be involved at various scales. Suture zones are important areas for the study of lineage formation and speciation, and our results show that biogeographic barriers can yield markedly different phylogeographic patterns in different vertebrate and invertebrate taxa.

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

Evaluation of spatial distribution of flatfish by laser scannig

Peer reviewed

Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.

High-SNR analytical performance of spatial multiplexing MIMO systems with CSI

In this paper, we investigate the average andoutage performance of spatial multiplexing multiple-input multiple-output (MIMO) systems with channel state information at both sides of the link. Such systems result, for example, from exploiting the channel eigenmodes in multiantenna systems. Dueto the complexity of obtaining the exact expression for the average bit error rate (BER) and the outage probability, we deriveapproximations in the high signal-to-noise ratio (SNR) regime assuming an uncorrelated Rayleigh flat-fading channel. Moreexactly, capitalizing on previous work by Wang and Giannakis, the average BER and outage probability versus SNR curves ofspatial multiplexing MIMO systems are characterized in terms of two key parameters: the array gain and the diversity gain. Finally, these results are applied to analyze the performance of a variety of linear MIMO transceiver designs available in the literature.

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique forthe reception of pilot-aided multirate multicode direct-sequencecode division multiple access (DS/CDMA) systems such as widebandCDMA (WCDMA). These systems introduce a code-multiplexedpilot sequence that can be used for the estimation of thefilter weights, but the presence of the traffic signal (transmittedat the same time as the pilot sequence) corrupts that estimationand degrades the performance of the filter significantly. This iscaused by the fact that although the traffic and pilot signals areusually designed to be orthogonal, the frequency selectivity of thechannel degrades this orthogonality at hte receiving end. Here,we propose a semi-blind technique that eliminates the self-noisecaused by the code-multiplexing of the pilot. We derive analyticallythe asymptotic performance of both the training-only andthe semi-blind techniques and compare them with the actual simulatedperformance. It is shown, both analytically and via simulation,that high gains can be achieved with respect to training-onlybasedtechniques.

Spatial processing for frequency diversity schemes

A novel technique to obtain optimum blind spatialprocessing for frequency diversity spread spectrum (FDSS) communicationsystems is introduced. The sufficient statistics for alinear combiner, which prove ineffective due to the interferers frequencycharacteristics, are modified to yield improved detectionunder partial jamming in the spectral domain. Robustness to partialtime jamming is achieved by extending the notion of replicasover the frequency axis to a repetition over the time variable. Analysisand simulations are provided, showing the advantages of usingFDSS with spatial diversity to combat the interference when it isconfined to a narrow frequency band or short time interval relativeto the desired signal extent in either domain.

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.