Auditory spatial deficits following hemispheric lesions : dissociation of explicit and implicit processing

Les déficits auditifs spatiaux se produisent fréquemment après une lésion hémisphérique ; un précédent case report suggérait que la capacité explicite à reconnaître des positions sonores, comme dans la localisation des sons, peut être atteinte alors que l'utilisation implicite d'indices sonores pour la reconnaissance d'objets sonores dans un environnement bruyant reste préservée. En testant systématiquement des patients avec lésion hémisphérique inaugurale, nous avons montré que (1) l'utilisation explicite et/ou implicite des indices sonores peut être perturbée ; (2) la dissociation entre l'atteinte de l'utilisation explicite des indices sonores versus une préservation de l'utilisation implicite de ces indices est assez fréquente ; et (3) différents types de déficits dans la localisation des sons peuvent être associés avec une utilisation implicite préservée de ces indices sonores. Conceptuellement, la dissociation entre l'utilisation explicite et implicite de ces indices sonores peut illustrer la dichotomie des deux voies du système auditif. Nos résultats parlent en faveur d'une évaluation systématique des fonctions auditives spatiales dans un contexte clinique, surtout quand l'adaptation à un environnement sonore est en jeu. De plus, des études systématiques sont nécessaires afin de mettre en lien les troubles de l'utilisation explicite versus implicite de ces indices sonores avec les difficultés à effectuer les activités de la vie quotidienne, afin d'élaborer des stratégies de réhabilitation appropriées et afin de s'assurer jusqu'à quel point l'utilisation explicite et implicite des indices spatiaux peut être rééduquée à la suite d'un dommage cérébral.

Temporal and spatial appearance of the membrane cytoskeleton and perineuronal nets in the rat neocortex.

Parvalbumin-immunoreactive interneurons are surrounded by perineuronal nets, containing molecules of the extracellular matrix (e.g. tenascin-R). Furthermore, they seem to have a special cytoskeleton composed of, among others, ankyrinR and beta Rspectrin. In the present developmental study we showed that the intracellular markers parvalbumin, ankyrinR and beta Rspectrin as well as Vicia Villosa agglutinin, an extracellular marker for perineuronal nets, appeared in the second postnatal week. In the third postnatal week, ankyrinR and beta R spectrin were present in the parvalbumin-positive interneurons. Tenascin-R appeared in a similar topographic distribution as the intracellular markers. The adult pattern was established upon the end of the fourth postnatal week. Our results indicate that cytoskeletal maturity maybe a prerequisite for the organization of perineuronal nets of extracellular matrix.

Spatial modelling of biodiversity at the community level

1. Statistical modelling is often used to relate sparse biological survey data to remotely derived environmental predictors, thereby providing a basis for predictively mapping biodiversity across an entire region of interest. The most popular strategy for such modelling has been to model distributions of individual species one at a time. Spatial modelling of biodiversity at the community level may, however, confer significant benefits for applications involving very large numbers of species, particularly if many of these species are recorded infrequently. 2. Community-level modelling combines data from multiple species and produces information on spatial pattern in the distribution of biodiversity at a collective community level instead of, or in addition to, the level of individual species. Spatial outputs from community-level modelling include predictive mapping of community types (groups of locations with similar species composition), species groups (groups of species with similar distributions), axes or gradients of compositional variation, levels of compositional dissimilarity between pairs of locations, and various macro-ecological properties (e.g. species richness). 3. Three broad modelling strategies can be used to generate these outputs: (i) 'assemble first, predict later', in which biological survey data are first classified, ordinated or aggregated to produce community-level entities or attributes that are then modelled in relation to environmental predictors; (ii) 'predict first, assemble later', in which individual species are modelled one at a time as a function of environmental variables, to produce a stack of species distribution maps that is then subjected to classification, ordination or aggregation; and (iii) 'assemble and predict together', in which all species are modelled simultaneously, within a single integrated modelling process. These strategies each have particular strengths and weaknesses, depending on the intended purpose of modelling and the type, quality and quantity of data involved. 4. Synthesis and applications. The potential benefits of modelling large multispecies data sets using community-level, as opposed to species-level, approaches include faster processing, increased power to detect shared patterns of environmental response across rarely recorded species, and enhanced capacity to synthesize complex data into a form more readily interpretable by scientists and decision-makers. Community-level modelling therefore deserves to be considered more often, and more widely, as a potential alternative or supplement to modelling individual species.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Impaired early visual response modulations to spatial information in chronic schizophrenia.

Early visual processing stages have been demonstrated to be impaired in schizophrenia patients and their first-degree relatives. The amplitude and topography of the P1 component of the visual evoked potential (VEP) are both affected; the latter of which indicates alterations in active brain networks between populations. At least two issues remain unresolved. First, the specificity of this deficit (and suitability as an endophenotype) has yet to be established, with evidence for impaired P1 responses in other clinical populations. Second, it remains unknown whether schizophrenia patients exhibit intact functional modulation of the P1 VEP component; an aspect that may assist in distinguishing effects specific to schizophrenia. We applied electrical neuroimaging analyses to VEPs from chronic schizophrenia patients and healthy controls in response to variation in the parafoveal spatial extent of stimuli. Healthy controls demonstrated robust modulation of the VEP strength and topography as a function of the spatial extent of stimuli during the P1 component. By contrast, no such modulations were evident at early latencies in the responses from patients with schizophrenia. Source estimations localized these deficits to the left precuneus and medial inferior parietal cortex. These findings provide insights on potential underlying low-level impairments in schizophrenia.

The multipoint Morisita index for the analysis of spatial patterns

In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.

Spatial predictions of phylogenetic diversity in conservation decision making.

Considering genetic relatedness among species has long been argued as an important step toward measuring biological diversity more accurately, rather than relying solely on species richness. Some researchers have correlated measures of phylogenetic diversity and species richness across a series of sites and suggest that values of phylogenetic diversity do not differ enough from those of species richness to justify their inclusion in conservation planning. We compared predictions of species richness and 10 measures of phylogenetic diversity by creating distribution models for 168 individual species of a species-rich plant family, the Cape Proteaceae. When we used average amounts of land set aside for conservation to compare areas selected on the basis of species richness with areas selected on the basis of phylogenetic diversity, correlations between species richness and different measures of phylogenetic diversity varied considerably. Correlations between species richness and measures that were based on the length of phylogenetic tree branches and tree shape were weaker than those that were based on tree shape alone. Elevation explained up to 31% of the segregation of species rich versus phylogenetically rich areas. Given these results, the increased availability of molecular data, and the known ecological effect of phylogenetically rich communities, consideration of phylogenetic diversity in conservation decision making may be feasible and informative.

As the world turns: short-term human spatial memory in egocentric and allocentric coordinates

We aimed to determine whether human subjects' reliance on different sources of spatial information encoded in different frames of reference (i.e., egocentric versus allocentric) affects their performance, decision time and memory capacity in a short-term spatial memory task performed in the real world. Subjects were asked to play the Memory game (a.k.a. the Concentration game) without an opponent, in four different conditions that controlled for the subjects' reliance on egocentric and/or allocentric frames of reference for the elaboration of a spatial representation of the image locations enabling maximal efficiency. We report experimental data from young adult men and women, and describe a mathematical model to estimate human short-term spatial memory capacity. We found that short-term spatial memory capacity was greatest when an egocentric spatial frame of reference enabled subjects to encode and remember the image locations. However, when egocentric information was not reliable, short-term spatial memory capacity was greater and decision time shorter when an allocentric representation of the image locations with respect to distant objects in the surrounding environment was available, as compared to when only a spatial representation encoding the relationships between the individual images, independent of the surrounding environment, was available. Our findings thus further demonstrate that changes in viewpoint produced by the movement of images placed in front of a stationary subject is not equivalent to the movement of the subject around stationary images. We discuss possible limitations of classical neuropsychological and virtual reality experiments of spatial memory, which typically restrict the sensory information normally available to human subjects in the real world.

A homing procedure for studying spatial memory in immature and adult rodents

In this procedure, subjects learn the spatial position of one hole out of many, that allows them to escape from a large open-field into their home cage. The arena is circular and can be rotated between trials so that no proximal landmark is permanently associated with the target hole. This task is thus similar to the Morris water maze procedure, since subjects must remember the position of the escape hole relative to extra-arena cues only. In addition it allows studying the importance of olfactory cues such as scent marks in or around a hole. Since the motivation is to reach home and the motor requirement is low, this task provides a useful alternative to the Morris place navigation task for studying spatial orientation in weanling or senescent rats. Examples are given showing that various behavioural parameters provide a good estimation as how subjects learn this task.