Combined analysis of grey matter voxel-based morphometry and white matter tract-based spatial statistics in late-life bipolar disorder.

Background: Previous magnetic resonance imaging (MRI) studies in young patients with bipolar disorder indicated the presence of grey matter concentration changes as well as microstructural alterations in white matter in various neocortical areas and the corpus callosum. Whether these structural changes are also present in elderly patients with bipolar disorder with long-lasting clinical evolution remains unclear. Methods: We performed a prospective MRI study of consecutive elderly, euthymic patients with bipolar disorder and healthy, elderly controls. We conducted a voxel-based morphometry (VBM) analysis and a tract-based spatial statistics (TBSS) analysis to assess fractional anisotropy and longitudinal, radial and mean diffusivity derived by diffusion tensor imaging (DTI). Results: We included 19 patients with bipolar disorder and 47 controls in our study. Fractional anisotropy was the most sensitive DTI marker and decreased significantly in the ventral part of the corpus callosum in patients with bipolar disorder. Longitudinal, radial and mean diffusivity showed no significant between-group differences. Grey matter concentration was reduced in patients with bipolar disorder in the right anterior insula, head of the caudate nucleus, nucleus accumbens, ventral putamen and frontal orbital cortex. Conversely, there was no grey matter concentration or fractional anisotropy increase in any brain region in patients with bipolar disorder compared with controls. Limitations: The major limitation of our study is the small number of patients with bipolar disorder. Conclusion: Our data document the concomitant presence of grey matter concentration decreases in the anterior limbic areas and the reduced fibre tract coherence in the corpus callosum of elderly patients with long-lasting bipolar disorder.

Multifractal portrayal of the distribution of the Swiss population

The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).

Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

Spatio-temporal analysis of an invasive plant pathogen (Phytophthora ramorum) in England and Wales

Phytophthora ramorum is a damaging invasive plant pathogen and was first discovered in the UK in 2002. Spatial point analyses were applied to the occurrence of this disease in England and Wales during the period of 2003-2006 in order to assess its spatio-temporal spread. Out of the 4301 garden centres and nurseries (GCN) surveyed, there were 164, 105, 123 and 41 sites with P. ramorum in 2003, 2004, 2005 and 2006, respectively. Spatial analysis of the observed point patterns of GCN outbreaks suggested that these sites were significantly clumped within a radius of ca 60 km in 2003, but not in later years. Further analyses were conducted to determine the relationship of GCN outbreak sites over two consecutive years and thus to infer possible disease spread over time. This analysis suggested that disease spread among GCN sites was most likely to have occurred within a distance of 60 km for 2003-2004, but not for the later years. There were 35, 63, 81 and 58 sites with P. ramorum in the semi-natural environment (SNE). Analyses were carried out to assess whether infected GCN sites could act as an inoculum source of infected SNE plants or vice versa. In all years, there was a significant spatial closeness among GCN and SNE outbreak sites within a distance of 1 km. But a significant relationship over a longer distance (within 60 km) was only observed between cases in 2003 and 2004. These analyses suggest that statutory actions taken so far appear to have reduced the extent of long-distance spread of P. ramorum among garden centres and nurseries, but not the disease spread at a shorter distance between GCN and SNE sites.

Geostatistical analysis of the spatial distribution of Rotylenchulus reniformis on cotton cultivated under crop rotation

The spatial distribution of Rotylenchulus reniformis on cotton cultivated in crop rotation with sorghum-peanut-velvetbean was studied using geostatistics. The experimental field, which had been continuously cropped with cotton for 20 years, comprised two 32 x 48 m-grids, each divided in sixty-four 4 x 6 in sampling plots. For all crops, 300 cm(3) soil samples were taken at the center of each plot at crop germination (Pi) and again at harvest (Pf), from which the numbers of nematodes were determined. The results revealed that the spatial distribution of R. reniformis was highly aggregated and with the aid of geostatistical techniques the nematode intensities were mapped and the risk areas accurately identified. Consequently, geostatistics is here considered a useful tool for planning nematode control strategies, particularly in precision agriculture.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variabilidade espacial de atributos do solo e da produtividade de milho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Congruent spatial and temporal foraging by a dominant ant (Hym., Formicidae) and its replacement in an assemblage in a large urban structure in southeastern Brazil

At fixed bail stations in a large institutional setting in Brazil, the temporal and spatial pattern of usage of the dominant species of ant was studied. The ant Crematogaster cf. magnifica, was found in 91% of sampling points. These studies were conducted using the same points as a previous study of tile then dominant ant. Monomorium pharaonis, which was found to have declined from 93% to 3% spatial point occupation. The frequency of point usage during this study was significantly different from the Poisson distribution for both species, indicating non-random use of space. Crematogaster cf. magnifica was significantly more spatially exclusive than had been documented for M. pharaonis, and the probability of points originally occupied by M. pharaonis later becoming occupied by C. cf. magnifica was in excess of 90%. Temporal bait exploitation patterns of the two species did not differ. These data demonstrate that structural ant communities can change over time without human intervention, although short- term stability is characteristic of the urban dominant ants in subtropical Brazil.

Spatial-Temporal Variation in Orchid Bee Communities (Hymenoptera: Apidae) in Remnants of Arboreal Caatinga in the Chapada Diamantina Region, State of Bahia, Brazil

The spatial and temporal distribution of organisms is a fundamental aspect of biological communities. The present study focused on three remnants of arboreal Caatinga in northeastern Brazil between May, 2009 and April, 2010. A total of 627 euglossine males were captured in traps baited with artificial aromatic compounds. The specimens belonged to 14 species and four genera: Euglossa Latreille, Eulaema Lepeletier, Eufriesea Cockerell, and Exaerete Hoffmannsegg. Eulaema nigrita Lepeletier (41.6), Euglossa carolina Nem,sio (15.3%), Eulaema marcii Nem,sio (13.6%), and Euglossa melanotricha Moure (12.8%) were the most common species sampled. The distribution of collected specimens per fragment was as follows: BraA(0)na (280 ha)-259 individuals belonging to 14 species; Cambui (179 ha)-161 individuals from eight species; and Pindoba (100 ha)-207 individuals represented by seven species. BraA(0)na had the highest diversity (H'aEuro parts per thousand= 1.91) and estimated species richness. The largest fragment was the main source of the observed variation in species richness and abundance, indicating a non-random pattern of spatial distribution. The analysis of environmental factors indicated that seasonal variation in these factors was the principal determinant of species occurrence and abundance.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

The spatiotemporal pattern of auditory cortical responses during verbal hallucinations

Functional magnetic resonance imaging (fMRI) studies can provide insight into the neural correlates of hallucinations. Commonly, such studies require self-reports about the timing of the hallucination events. While many studies have found activity in higher-order sensory cortical areas, only a few have demonstrated activity of the primary auditory cortex during auditory verbal hallucinations. In this case, using self-reports as a model of brain activity may not be sensitive enough to capture all neurophysiological signals related to hallucinations. We used spatial independent component analysis (sICA) to extract the activity patterns associated with auditory verbal hallucinations in six schizophrenia patients. SICA decomposes the functional data set into a set of spatial maps without the use of any input function. The resulting activity patterns from auditory and sensorimotor components were further analyzed in a single-subject fashion using a visualization tool that allows for easy inspection of the variability of regional brain responses. We found bilateral auditory cortex activity, including Heschl's gyrus, during hallucinations of one patient, and unilateral auditory cortex activity in two more patients. The associated time courses showed a large variability in the shape, amplitude, and time of onset relative to the self-reports. However, the average of the time courses during hallucinations showed a clear association with this clinical phenomenon. We suggest that detection of this activity may be facilitated by examining hallucination epochs of sufficient length, in combination with a data-driven approach.

Hebbian analysis of the transformation of medial entorhinal grid-cell inputs to hippocampal place fields.

The discovery of grid cells in the medial entorhinal cortex (MEC) permits the characterization of hippocampal computation in much greater detail than previously possible. The present study addresses how an integrate-and-fire unit driven by grid-cell spike trains may transform the multipeaked, spatial firing pattern of grid cells into the single-peaked activity that is typical of hippocampal place cells. Previous studies have shown that in the absence of network interactions, this transformation can succeed only if the place cell receives inputs from grids with overlapping vertices at the location of the place cell's firing field. In our simulations, the selection of these inputs was accomplished by fast Hebbian plasticity alone. The resulting nonlinear process was acutely sensitive to small input variations. Simulations differing only in the exact spike timing of grid cells produced different field locations for the same place cells. Place fields became concentrated in areas that correlated with the initial trajectory of the animal; the introduction of feedback inhibitory cells reduced this bias. These results suggest distinct roles for plasticity of the perforant path synapses and for competition via feedback inhibition in the formation of place fields in a novel environment. Furthermore, they imply that variability in MEC spiking patterns or in the rat's trajectory is sufficient for generating a distinct population code in a novel environment and suggest that recalling this code in a familiar environment involves additional inputs and/or a different mode of operation of the network.

Performance tiers: Implementing comparative effectiveness analysis in the health care setting through operations research and spatial methods

This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^

Spatial and temporal precipitation patterns of the Ebro River Basin, Spain

The Ebro River Basin, with around 85 000 km2 and located in NE Spain, is characterized by the high spatial heterogeneity of its geology, topography, climatology and land use. Rainfall is one of the most important climatic variables studied owing to its non-homogenous behaviour in event and intensity, which creates drought, water runoff and soil erosion with negative environmental and social consequences. In this work we characterized the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (? index) and the maximum probable singularity in the rainfall distribution ( s). A spatial and temporal analysis of the UM parameters is applied to study the possible changes. With this porpoise, 60 daily rainfall series were selected from 132 synthetic series generated by Luna and Balairón (AEMet). These daily rainfall series present a length of 60 years, from 1950 to 2009. Each one of them was subdivided (1950?1970 and 1980?2009) to analyse the difference between the two periods. The range of variation of precipitation amounts and the frequency of dry events between both periods are discussed, as well as the evolution of the UM parameters through the years.

Knowledge-based spatiotemporal linear abstraction

We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways.