Single Subject Finger Somatotopy Mapping at 7T.

Introduction: The primary somatosensory cortex (SI) contains Brodmann areas (BA) 1, 2, 3a, and 3b. Research in non-human primates showed that BAs 3b, 1, and 2 each contain one full representation of the hand with separate representations for each finger. This research also showed that the finger representation in BA3b has larger and clearer finger somatotopy than BA1 and 2. Although several efforts to map finger somatotopy in SI by fMRI have been made at 1.5 and 3T these studies have yielded variable results and were not able to detect single subject finger somatotopy, probably due to the limited spatial extent of the cortical areas representing a digit (close to the resolution in most fMRI experiments), complications due to acquisition of consistent maps for individual subjects (Schweizer et al 2008), or inter-individual variability in sulcal anatomy impeding group studies. Here, we used 7T fMRI to investigate finger somatotopy in SI, some of its functional characteristics, and its reproducibility. Methods: Eight right-handed male subjects were scanned on a 7T scanner (Siemens Medical, Germany) with an 8-channel Tx/Rx rf-coil (Rapid Biomedical, Germany). 1.3x1.3x1.3mm3 resolution fMRI data were acquired using a sinusoidal readout EPI sequence (Speck et al, 2008) and FOV=210mm, TE/TR=27ms/2.5s, GRAPPA=2. Each volume contained 28 transverse slices covering SI. A single EPI volume with 64 slices was acquired to aid coregistration. 1x1x1mm3 anatomical data were acquire using the MP2RAGE sequence (Marques et al, 2009; TE/TR/TI1,2/TRmprage=2.63ms/7.2ms/0.9,3.2s/5s). Subjects were positioned supine in the scanner with their right arm comfortably against the magnet bore. An experimenter was positioned at the entrance of the bore where he could easily reach and stroke successively the two distal phalanxes of each digit. The order of stroked digit was D1 (thumb)-D3-D5-D2-D4, with 20s ON, 10s OFF alternated. This sequence was repeated four times per run and two functional runs were acquired per subject. Realignment, smoothing (FWHM 2 mm), coregistration of the anatomical to the fMRI data and calculation of t-statistics were done using SPM8. An SI mask was obtained via an F-contrast (p<0.001) over all digits. Within the mask, voxels were labeled with the number of the digit demonstrating the highest t-value for that particular voxel. Results: For all subjects, areas corresponding to the five digits were identified in contralateral SI. BA3b showed the most consistent somatotopic finger representation (see an example in Fig.1). The five digits were localized in a consecutive order in the cortex, with D1 most anterior, inferior and distal and D5, most posterior, superior and medial (mean distance between centres of mass of digit representations ±stderr: 4.2±0.7mm; see Fig. 2). The analysis of average beta values within each finger representation region revealed the specificity of the somatotopic region to the tactile input for each tested finger (except digit 4 and 5). Five of these subjects also presented an orderly and consecutive representation of the five digits in BA1 and 2. Conclusions: Our data reveal that the increased BOLD sensitivity at 7T and the high spatial resolution used in this study allow consistent somatotopic mapping using human touch as a stimulus and that human SI contains at least three separate regions that contain five separate representations of all single contralateral fingers. Moreover, adjacent fingers were represented at adjacent cortical regions across the three SI regions. The spatial organization of SI as reflected in individual subject topography corresponds well with previous electrophysiological data in non-human primates. The small distance between digit representations highlights the need for the high spatial resolution available at 7T.

Social Cognition is not Reducible to Theory of Mind. When Children use Deontic Rules to Predict Others' Behaviors

The objective of this paper is to discuss whether children have a capacity for deonticreasoning that is irreducible to mentalizing. The results of two experiments point tothe existence of such non-mentalistic understanding and prediction of the behaviourof others. In Study 1, young children (3- and 4-year-olds) were told different versionsof classic false-belief tasks, some of which were modified by the introduction of a ruleor a regularity. When the task (a standard change of location task) included a rule, theperformance of 3-year-olds, who fail traditional false-belief tasks, significantly improved.In Study 2, 3-year-olds proved to be able to infer a rule from a social situation and touse it in order to predict the behaviour of a character involved in a modified versionof the false-belief task. These studies suggest that rules play a central role in the socialcognition of young children and that deontic reasoning might not necessarily involvemind reading.

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Some reflections on Geobotany and Vegetation mapping

uivalent Spanish and Catalan terms.

Mapping cell-matrix stresses during stretch reveals inelastic reorganization of the cytoskeleton.

The mechanical properties of the living cell are intimately related to cell signaling biology through cytoskeletal tension. The tension borne by the cytoskeleton (CSK) is in part generated internally by the actomyosin machinery and externally by stretch. Here we studied how cytoskeletal tension is modified during stretch and the tensional changes undergone by the sites of cell-matrix interaction. To this end we developed a novel technique to map cell-matrix stresses during application of stretch. We found that cell-matrix stresses increased with imposition of stretch but dropped below baseline levels on stretch release. Inhibition of the actomyosin machinery resulted in a larger relative increase in CSK tension with stretch and in a smaller drop in tension after stretch release. Cell-matrix stress maps showed that the loci of cell adhesion initially bearing greater stress also exhibited larger drops in traction forces after stretch removal. Our results suggest that stretch partially disrupts the actin-myosin apparatus and the cytoskeletal structures that support the largest CSK tension. These findings indicate that cells use the mechanical energy injected by stretch to rapidly reorganize their structure and redistribute tension.

Interactome mapping of the phosphatidylinositol 3-kinase-mammalian target of rapamycin pathway identifies deformed epidermal autoregulatory factor-1 as a new glycogen synthase kinase-3 interactor.

The phosphatidylinositol 3-kinase-mammalian target of rapamycin (PI3K-mTOR) pathway plays pivotal roles in cell survival, growth, and proliferation downstream of growth factors. Its perturbations are associated with cancer progression, type 2 diabetes, and neurological disorders. To better understand the mechanisms of action and regulation of this pathway, we initiated a large scale yeast two-hybrid screen for 33 components of the PI3K-mTOR pathway. Identification of 67 new interactions was followed by validation by co-affinity purification and exhaustive literature curation of existing information. We provide a nearly complete, functionally annotated interactome of 802 interactions for the PI3K-mTOR pathway. Our screen revealed a predominant place for glycogen synthase kinase-3 (GSK3) A and B and the AMP-activated protein kinase. In particular, we identified the deformed epidermal autoregulatory factor-1 (DEAF1) transcription factor as an interactor and in vitro substrate of GSK3A and GSK3B. Moreover, GSK3 inhibitors increased DEAF1 transcriptional activity on the 5-HT1A serotonin receptor promoter. We propose that DEAF1 may represent a therapeutic target of lithium and other GSK3 inhibitors used in bipolar disease and depression.

Mapping, organic matter mass and water volume of a peatland in Serra do Espinhaço Meridional

Peatlands form in areas where net primary of organic matter production exceeds losses due to the decomposition, leaching or disturbance. Due to their chemical and physical characteristics, bogs can influence water dynamics because they can store large volumes of water in the rainy season and gradually release this water during the other months of the year. In Diamantina, Minas Gerais, Brazil, a peatland in the environmental protection area of Pau-de-Fruta ensures the water supply of 40,000 inhabitants. The hypothesis of this study is that the peat bogs in Pau-de-Fruta act as an environment for carbon storage and a regulator of water flow in the Córrego das Pedras basin. The objective of this study was to estimate the water volume and organic matter mass in this peatland and to study the influence of this environment on the water flow in the Córrego das Pedras basin. The peatland was mapped using 57 transects, at intervals of 100 m. Along all transects, the depth of the peat bog, the Universal Transverse Mercator (UTM) coordinates and altitude were recorded every 20 m and used to calculate the area and volume of the peatland. The water volume was estimated, using a method developed in this study, and the mass of organic matter based on samples from 106 profiles. The peatland covered 81.7 hectares (ha), and stored 497,767 m³ of water, representing 83.7 % of the total volume of the peat bog. The total amount of organic matter (OM) was 45,148 t, corresponding to 552 t ha-1 of OM. The peat bog occupies 11.9 % of the area covered by the Córrego das Pedras basin and stores 77.6 % of the annual water surplus, thus controlling the water flow in the basin and consequently regulating the water course.

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

Automatic Mapping and Classification of Spatial Environmental Data

The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.