Temporal lobe white matter asymmetry and language laterality in epilepsy patients.

Recent studies using diffusion tensor imaging (DTI) have advanced our knowledge of the organization of white matter subserving language function. It remains unclear, however, how DTI may be used to predict accurately a key feature of language organization: its asymmetric representation in one cerebral hemisphere. In this study of epilepsy patients with unambiguous lateralization on Wada testing (19 left and 4 right lateralized subjects; no bilateral subjects), the predictive value of DTI for classifying the dominant hemisphere for language was assessed relative to the existing standard-the intra-carotid Amytal (Wada) procedure. Our specific hypothesis is that language laterality in both unilateral left- and right-hemisphere language dominant subjects may be predicted by hemispheric asymmetry in the relative density of three white matter pathways terminating in the temporal lobe implicated in different aspects of language function: the arcuate (AF), uncinate (UF), and inferior longitudinal fasciculi (ILF). Laterality indices computed from asymmetry of high anisotropy AF pathways, but not the other pathways, classified the majority (19 of 23) of patients using the Wada results as the standard. A logistic regression model incorporating information from DTI of the AF, fMRI activity in Broca's area, and handedness was able to classify 22 of 23 (95.6%) patients correctly according to their Wada score. We conclude that evaluation of highly anisotropic components of the AF alone has significant predictive power for determining language laterality, and that this markedly asymmetric distribution in the dominant hemisphere may reflect enhanced connectivity between frontal and temporal sites to support fluent language processes. Given the small sample reported in this preliminary study, future research should assess this method on a larger group of patients, including subjects with bi-hemispheric dominance.

Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

Incidental findings on cone beam computed tomography scans in cleft lip and palate patients.

OBJECTIVES Cone beam computed tomography (CBCT) is frequently used in treatment planning for alveolar bone grafting (ABG) and orthognathic surgery in patients with cleft lip and palate (CLP). CBCT images may depict coincident findings. The aim of this study was to assess the prevalence of incidental findings on CBCT scans in CLP patients. SUBJECTS AND METHODS Initial CBCTs taken from consecutive patients (n = 187; mean age 11.7 years, range 6.9-45) with a non-syndromic orofacial cleft from January 2006 until June 2012 were systematically evaluated. Twenty-eight patients (mean age 19.3 years, range 13.2-30.9) had been subjected to ABG before their first CBCT was taken; 61 patients had a CBCT before and after ABG. Sinuses, nasopharynx, oropharynx, throat, skull, vertebrae, temporomandibular joint (TMJ), maxilla and mandible were checked for incidental findings. RESULTS On 95.1 % of the CBCTs, incidental findings were found. The most prevalent were airway/sinus findings (56.1 %), followed by dental problems, e.g. missing teeth (52 %), nasal septum deviation (34 %), middle ear and mastoid opacification, suggestive for otitis media (10 %) and (chronic) mastoiditis (9 %), abnormal TMJ anatomy (4.9 %) and abnormal vertebral anatomy (1.6 %). In the 28 patients whose first CBCT was taken at least 2 years after ABG, bone was still present in the reconstructed cleft area except in 2 out of 12 patients with a bilateral CLP. The ABG donor site (all bone grafts were taken from the chin area) was still recognizable in over 50 % of the patients. Based on the CBCT findings, 10 % of the patients were referred for further diagnosis and 9 % for further treatment related to dental problems. CONCLUSION Incidental findings are common on CBCTs. Compared with the literature, CLP patients have more dental, nasal and ear problems. Thus, whenever a CBCT is available, this scan should be reviewed by all specialists in the CLP team focusing on their specific background knowledge concerning symptoms and treatment of these patients. CLINICAL RELEVANCE The high number of findings indicates that CBCT imaging is a helpful tool in the treatment of CLP patients not only related to alveolar bone grafting and orthognathic surgery but it also provides diagnostic information for almost all specialties involved in CLP treatment.

First valence, then arousal: the temporal dynamics of brain electric activity evoked by emotional stimuli

The temporal dynamics of the neural activity that implements the dimensions valence and arousal during processing of emotional stimuli were studied in two multi-channel ERP experiments that used visually presented emotional words (experiment 1) and emotional pictures (experiment 2) as stimulus material. Thirty-two healthy subjects participated (mean age 26.8 +/- 6.4 years, 24 women). The stimuli in both experiments were selected on the basis of verbal reports in such a way that we were able to map the temporal dynamics of one dimension while controlling for the other one. Words (pictures) were centrally presented for 450 (600) ms with interstimulus intervals of 1,550 (1,400) ms. ERP microstate analysis of the entire epochs of stimulus presentations parsed the data into sequential steps of information processing. The results revealed that in several microstates of both experiments, processing of pleasant and unpleasant valence (experiment 1, microstate #3: 118-162 ms, #6: 218-238 ms, #7: 238-266 ms, #8: 266-294 ms; experiment 2, microstate #5: 142-178 ms, #6: 178-226 ms, #7: 226-246 ms, #9: 262-302 ms, #10: 302-330 ms) as well as of low and high arousal (experiment 1, microstate #8: 266-294 ms, #9: 294-346 ms; experiment 2, microstate #10: 302-330 ms, #15: 562-600 ms) involved different neural assemblies. The results revealed also that in both experiments, information about valence was extracted before information about arousal. The last microstate of valence extraction was identical with the first microstate of arousal extraction.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices

SUMMARY There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

Monitoring the temporal development of natural hazard risks as a basis indicator for climate change adaptation.

The potential effects of climatic changes on natural risks are widely discussed. But the formulation of strategies for adapting risk management practice to climate changes requires knowledge of the related risks for people and economic values. The main goals of this work were (1) the development of a method for analysing and comparing risks induced by different natural hazard types, (2) highlighting the most relevant natural hazard processes and related damages, (3) the development of an information system for the monitoring of the temporal development of natural hazard risk and (4) the visualisation of the resulting information for the wider public. A comparative exposure analysis provides the basis for pointing out the hot spots of natural hazard risks in the province of Carinthia, Austria. An analysis of flood risks in all municipalities provides the basis for setting the priorities in the planning of flood protection measures. The methods form the basis for a monitoring system that periodically observes the temporal development of natural hazard risks. This makes it possible firstly to identify situations in which natural hazard risks are rising and secondly to differentiate between the most relevant factors responsible for the increasing risks. The factors that most influence the natural risks could be made evident.

Soil and land information: How to support decision-making?

Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.

Spatial and temporal aspects of synaptic plasticity

The notion that changes in synaptic efficacy underlie learning and memory processes is now widely accepted even if definitive proof of the synaptic plasticity and memory hypothesis is still lacking. When learning occurs, patterns of neural activity representing the occurrence of events cause changes in the strength of synaptic connections within the brain. Reactivation of these altered connections constitutes the experience of memory for these events and for other events with which they may be associated. These statements summarize a long-standing theory of memory formation that we refer to as the synaptic plasticity and memory hypothesis. Since activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation, and is both necessary and sufficient for the information storage, we can speculate that a methodological study of the synapse will help us understand the mechanism of learning. Random events underlie a wide range of biological processes as diverse as genetic drift and molecular diffusion, regulation of gene expression and neural network function. Additionally spatial variability may be important especially in systems with nonlinear behavior. Since synapse is a complex biological system we expect that stochasticity as well as spatial gradients of different enzymes may be significant for induction of plasticity. ^ In that study we address the question "how important spatial and temporal aspects of synaptic plasticity may be". We developed methods to justify our basic assumptions and examined the main sources of variability of calcium dynamics. Among them, a physiological method to estimate the number of postsynaptic receptors as well as a hybrid algorithm for simulating postsynaptic calcium dynamics. Additionally we studied how synaptic geometry may enhance any possible spatial gradient of calcium dynamics and how that spatial variability affect plasticity curves. Finally, we explored the potential of structural synaptic plasticity to provide a metaplasticity mechanism specific for the synapse. ^

Analysis of temporal microbial properties from experimental plots of the Jena experiment (2003-2014)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the temporal stability were taken every year in May/June from 2003 to 2014, except in 2005. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

Modelización del cálculo de Indicadores Ambientales, a partir de sensores ópticos de alta resolución temporal a bordo de satélite

La presente tesis doctoral tiene por objeto el estudio y análisis de técnicas y modelos de obtención de parámetros biofísicos e indicadores ambientales, de manera automatizada a partir de imágenes procedentes de satélite de alta resolución temporal. En primer lugar se revisan los diferentes programas espaciales de observación del territorio, con especial atención a los que proporcionan dicha resolución. También se han revisado las metodologías y procesos que permiten la obtención de diferentes parámetros cuantitativos y documentos cualitativos, relacionados con diversos aspectos de las cubiertas terrestres, atendiendo a su adaptabilidad a las particularidades de los datos. En segundo lugar se propone un modelo de obtención de parámetros ambientales, que integra información proveniente de sensores espaciales y de otras fuentes auxiliares utilizando, en cierta medida, las metodologías presentadas en apartados anteriores y optimizando algunas de las referidas o proponiendo otras nuevas, de manera que se permita dicha obtención de manera eficiente, a partir de los datos disponibles y de forma sistemática. Tras esta revisión de metodologías y propuesta del modelo, se ha procedido a la realización de experimentos, con la finalidad de comprobar su comportamiento en diferentes casos prácticos, depurar los flujos de datos y procesos, así como establecer las situaciones que pueden afectar a los resultados. De todo ello se deducirá la evaluación del referido modelo. Los sensores considerados en este trabajo han sido MODIS, de alta resolución temporal y Thematic Mapper (TM), de media resolución espacial, por tratarse de instrumentos de referencia en la realización de estudios ambientales. También por la duración de sus correspondientes misiones de registro de datos, lo que permite realizar estudios de evolución temporal de ciertos parámetros biofísicos, durante amplios periodos de tiempo. Así mismo. es de destacar que la continuidad de los correspondientes programas parece estar asegurada. Entre los experimentos realizados, se ha ensayado una metodología para la integración de datos procedentes de ambos sensores. También se ha analizado un método de interpolación temporal que permite obtener imágenes sintéticas con la resolución espacial de TM (30 m) y la temporal de MODIS (1 día), ampliando el rango de aplicación de este último sensor. Asimismo, se han analizado algunos de los factores que afectan a los datos registrados, tal como la geometría de la toma de los mismos y los episodios de precipitación, los cuales alteran los resultados obtenidos. Por otro lado, se ha comprobado la validez del modelo propuesto en el estudio de fenómenos ambientales dinámicos, en concreto la contaminación orgánica de aguas embalsadas. Finalmente, se ha demostrado un buen comportamiento del modelo en todos los casos ensayados, así como su flexibilidad, lo que le permite adaptarse a nuevos orígenes de datos, o nuevas metodologías de cálculo. Abstract This thesis aims to the study and analysis of techniques and models, in order to obtain biophysical parameters and environmental indicators in an automated way, using high temporal resolution satellite data. Firstly we have reviewed the main Earth Observation Programs, paying attention to those that provide high temporal resolution. Also have reviewed the methodologies and process flow diagrams in order to obtain quantitative parameters and qualitative documents, relating to various aspects of land cover, according to their adaptability to the peculiarities of the data. In the next stage, a model which allows obtaining environmental parameters, has been proposed. This structure integrates information from space sensors and ancillary data sources, using the methodologies presented in previous sections that permits the parameters calculation in an efficient and automated way. After this review of methodologies and the proposal of the model, we proceeded to carry out experiments, in order to check the behavior of the structure in real situations. From this, we derive the accuracy of the model. The sensors used in this work have been MODIS, which is a high temporal resolution sensor, and Thematic Mapper (TM), which is a medium spatial resolution instrument. This choice was motivated because they are reference sensors in environmental studies, as well as for the duration of their corresponding missions of data logging, and whose continuity seems assured. Among the experiments, we tested a methodology that allows the integration of data from cited sensors, we discussed a proposal for a temporal interpolation method for obtaining synthetic images with spatial resolution of TM (30 m) and temporal of MODIS (1 day), extending the application range of this one. Furthermore, we have analyzed some of the factors that affect the recorded data, such as the relative position of the satellite with the ground point, and the rainfall events, which alter the obtained results. On the other hand, we have proven the validity of the proposed model in the study of the organic contamination in inland water bodies. Finally, we have demonstrated a good performance of the proposed model in all cases tested, as well as its flexibility and adaptability.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

An Interactive Bibliography on Temporal GIS.

This report introduces TimeBliography, a dynamic and online bibliography on temporal GIS. We provide a brief description of the bibliography as well as the components and functionalities of the web application that supports it. The bibliography is fully accessible on the Web at http://spaceandtime.wsiabato.info.

Adaptive spatio-temporal filter for low-cost camera depth maps

In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise.

Efficient spatio-temporal hole filling strategy for Kinect depth maps

In this paper we present an efficient hole filling strategy that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach is based on a joint-bilateral filtering framework that includes spatial and temporal information. The missing depth values are obtained applying iteratively a joint-bilateral filter to their neighbor pixels. The filter weights are selected considering three different factors: visual data, depth information and a temporal-consistency map. Video and depth data are combined to improve depth map quality in presence of edges and homogeneous regions. Finally, the temporal-consistency map is generated in order to track the reliability of the depth measurements near the hole regions. The obtained depth values are included iteratively in the filtering process of the successive frames and the accuracy of the hole regions depth values increases while new samples are acquired and filtered