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At least 307 records · Page 17Linked to original sources
PubMed2000

Spatial spectral analysis of human electrocorticograms including the alpha and gamma bands.

Spatial spectral analysis is essential for deriving spatial patterns from simultaneous recordings of electrocorticograms (ECoG), in order to determine the optimal interval between electrodes in arrays, and to design spatial filters, particularly for extraction of information about the dynamics of human gamma activity. ECoG were recorded from up to 64 electrodes 0.5 mm apart in a linear array 3.2 cm long, which was placed on the exposed superior temporal gyrus or motor cortex of volunteers undergoing diagnostic surgery. Visual displays of multiple traces revealed broad spectrum oscillations in episodic bursts having a common aperiodic wave form with recurring patterns of spatial amplitude modulation (AM patterns) on selected portions of the array. The one-dimensional spatial spectrum of the human ECoG was calculated at successive time samples and averaged over periods of up to 20 s. Log power decreased monotonically with increasing log spatial frequency in cycles/mm (c/mm) to the noise level approximately 2 log units below maximal power at minimal frequency (0.039+/-0.002 c/mm). The inflection point at 0.40+/-0.05 c/mm specified an optimal value for a low pass spatial filter to remove noise, and an optimal interelectrode spacing of 1.25 mm to avoid undersampling and aliasing. An 8 x 8 array with that spacing would be 10 x 10 mm.

Adolescent↗
PubMed1996

Analysis of spatial and temporal clustering of horses with Salmonella krefeld in an intensive care unit of a veterinary hospital.

OBJECTIVE: To determine whether clustering existed in the spatial or temporal distribution of horses that shed Salmonella krefeld in their feces during hospitalization. DESIGN: Retrospective analysis of medical records. ANIMALS: 219 horses housed in the intensive care unit of a veterinary medical teaching hospital from October 1991 through May 1992. PROCEDURE: Bacteriologic culturing of fecal samples was used to identify horses shedding S krefeld. For affected horses, the scan statistic was used to analyze temporal clustering, and Knox's method was used to analyze temporal-spatial clustering. RESULTS: 20 horses were identified as shedding S krefeld in their feces. Significant temporal clustering of affected horses was observed for periods of 5, 6, 7, and 8 days. Temporal-spatial analysis did not detect a significant distribution for any combination of time and distance among affected horses. CLINICAL IMPLICATIONS: Detection of temporal clustering and concurrent random temporal-spatial distribution of affected horses suggested that affected horses were grouped in time, but means of transmission was not related to proximity between horses.

Animals↗
PubMed2004

Spatial-temporal analysis of Ross River virus disease patterns in Queensland, Australia.

Ross River virus is the most common vector-borne disease in Australia, with the majority of notifications being in Queensland. This study describes a retrospective spatial analysis of Queensland Ross River virus disease notifications spanning a 10-year period. Notifications were mapped to the local government area (LGA) of the residence of the patient. Ross River virus disease outbreaks within each LGA were detected by applying a Poisson model. Estimates of the seasonal incidence rates indicated wide variation between seasons and LGAs. Positive spatial autocorrelation between LGAs experiencing outbreaks indicated that LGAs within the same region often experience outbreaks at the same time. A hierarchical cluster analysis of the outbreak data was used to group LGAs with similar temporal outbreak patterns. This analysis highlights the variability in Ross River virus disease notification rates across Queensland, and provides a robust method for identifying disease outbreaks.

Adolescent↗
PubMed2006

[Maternal and child health indicators in Belo Horizonte, Minas Gerais State, Brazil, 2001: an analysis of intra-urban differences].

Spatial analysis of health indicators is as an important methodology for detection of intra-urban differences. This study aimed to examine the spatial distribution of all live births in Belo Horizonte, analyzing the presence of spatial clusters of health indicators for newborns and their mothers, using data from the Information System on Live Births. For each area covered by a Primary Health Care Unit, we calculated the indicators using empirical Bayesian methods. For spatial analysis, the indicators obtained from the global Moran (I) index and Local Indicators of Spatial Association (LISA) were used. Analysis using LISA showed the presence of relevant spatial clusters for adolescent mothers and those with low schooling, stillbirths in previous pregnancies, cesarean sections, and low attendance at prenatal care, especially in areas with low socio-demographic characteristics. The methodology adopted was configured as a key instrument for detecting risk areas where clustering occurs. The method can easily be incorporated into health surveillance systems as a mechanism for controlling events related to births in a given area.

Adolescent↗
PubMed1996

Neuronal pattern correlates with the severity of human immunodeficiency virus-associated dementia complex. Usefulness of spatial pattern analysis in clinicopathological studies.

The spatial distributional pattern of neurons, in the superior frontal gyrus of 32 subjects who died of acquired immune deficiency syndrome, was examined. The patients were classified as nondemented, mildly demented, and severely demented, and some were treated with the anti-retroviral drug zidovudine. Spatial statistical techniques were employed to investigate the degree of clustering in the individual cases and various groups. We found that the cluster pattern of large and small neurons differed significantly with increasing severity of dementia but was not influenced by the duration of zidovudine treatment. We conclude that this is a sensitive technique for clinicopathological correlations and that the differences may result from loss of specific neuronal populations, which could determine the degree of dementia.

AIDS Dementia Complex↗
PubMed1996

Nearest-neighbor analysis of spatial point patterns: application to biomedical image interpretation.

Analysis of the spatial distributions of objects is fundamental to biomedical image interpretation. Nearest-neighbor (NN) methods are generally used to assess whether objects are arranged at random or in a deterministic manner. Simple standard NN techniques, however, may fail to identify complex spatial organizations. To overcome this problem the present study proposes a NN iterative algorithm that enables deterministic spatial patterns to be detected by identifying the distances between objects for which there is the greatest deviation from randomness and hence the amplitude of the areas of maximum reciprocal influence between objects. The performance of the algorithm is evaluated by applying it to both manufactured and experimental data. The manufactured date example showed that the proposed procedure produced neither false positives or negatives. The method proved to be extremely sensitive, detecting even small deviations from randomness. The experimental analysis was applied to the study of the spatial distribution of apopototic structures in malignant neoplastic tissue. It showed that the apopototic cells and bodies are characterized by a complex spatial pattern, and aggregate closely.

Algorithms↗
PubMed2002

[Spatial autocorrelation analysis on schistosomiasis cases and Oncomelania snails in three provinces of the lower reach of Yangtze River].

OBJECTIVE: To explore the spatial distribution of schistosomiasis cases and Oncomelania snails in the provinces of Jiangsu, Anhui and Jiangxi with the assistance of geographic information systems (GIS). METHODS: Epidemiological data of schistosomiasis in recent 20 years were collected, and the relevant GIS databases were established. The spatial autocorrelation analysis was carried out with ArcView 3. x, S-Plus, and Spatial Statistics software. RESULTS: Except for schistosomiasis cases in Jiangsu, the spatial distribution of schistosomiasis cases and Oncomelania snails in the three provinces were fitted to the spatial autocorrelation at a certain degree. Generally the autocorrelation coefficients (Moran's I) in Oncomelania snails were higher than that in schistosomiasis cases. CONCLUSION: Spatial autocorrelation analysis can be used to estimate the value of one variable in different spatial position, and it is a good way to find out the spatial cluster distribution in different stages.

Animals↗
PubMed2005

Current practices in cancer spatial data analysis: a call for guidance.

There has long been a recognition that place matters in health, from recognition of clusters of yellow fever and cholera in the 1800s to modern day analyses of regional and neighborhood effects on cancer patterns. Here we provide a summary of discussions about current practices in the spatial analysis of georeferenced cancer data by a panel of experts recently convened at the National Cancer Institute.

Journal Article↗
PubMed1989

Spatial autocorrelation analysis of migration and selection.

We test various assumptions necessary for the interpretation of spatial autocorrelation analysis of gene frequency surfaces, using simulations of Wright's isolation-by-distance model with migration or selection superimposed. Increasing neighborhood size enhances spatial autocorrelation, which is reduced again for the largest neighborhood sizes. Spatial correlograms are independent of the mean gene frequency of the surface. Migration affects surfaces and correlograms when immigrant gene frequency differentials are substantial. Multiple directions of migration are reflected in the correlograms. Selection gradients yield clinal correlograms; other selection patterns are less clearly reflected in their correlograms. Sequential migration from different directions and at different gene frequencies can be disaggregated into component migration vectors by means of principal components analysis. This encourages analysis by such methods of gene frequency surfaces in nature. The empirical results of these findings lend support to the inference structure developed earlier for spatial autocorrelation analysis.

Computer Simulation↗
PubMed1993

EEG/EP: new techniques.

The topographic analysis of electrical brain activity consists of the extraction of quantitative features which adequately describe the scalp recorded electrical fields of the brain. In the beginning of brain electrical activity mapping most methods centered mainly around the graphical display of multichannel EEG and evoked potential data. Meanwhile quantitative analysis strategies have been developed, and such methods are applied to topographic EEG and evoked potential data enabling the statistical evaluation of the effects of different experimental conditions as well as the comparison of various clinical populations. Major new analysis techniques comprise the computation of global field power and global dissimilarity for determination of components of evoked potential fields, the segmentation of map series by topographical features, time range analysis, FFT approximation for the spatial analysis of EEG frequency bands as well as correlation analysis and spatial principal components analysis (Spatial PCA). Data from experiments dealing with evoked brain activity will illustrate the application of these quantitative methods that also can be used for the analysis of the spontaneous EEG.

Brain↗
PubMed1993

Fluorescence photobleaching with spatial Fourier analysis: measurement of diffusion in light-scattering media.

A new method for the measurement of diffusion in thick samples is introduced, based upon the spatial Fourier analysis of Tsay and Jacobson (Biophys. J. 60: 360-368, 1991) for the video image analysis of fluorescence recovery after photobleaching (FRAP). In this approach, the diffusion coefficient is calculated from the decay of Fourier transform coefficients in successive fluorescence images. Previously, the application of FRAP in thick samples has been confounded by the optical effects of out-of-focus light and scattering and absorption by the sample. The theory of image formation is invoked to show that the decay rate is the same for both the observed fluorescence intensity and the true concentration distribution in the tissue. The method was tested in a series of macromolecular diffusion measurements in aqueous solution, in agarose gel, and in simulated tissue consisting of tumor cells (45% v/v) and blood cells (5% v/v) in an agarose gel. For a range of fluorescently labeled proteins (MW = 14 to 600 kD) and dextrans (MW = 4.4 to 147.8 kD), the diffusion coefficients in aqueous solution were comparable to previously published values. A comparison of the spatial Fourier analysis with a conventional direct photometric method revealed that even for the weakly scattering agarose sample, the conventional method gives a result that is inaccurate and dependent on sample thickness whereas the diffusion coefficient calculated by the spatial Fourier method agreed with published values and was independent of sample thickness. The diffusion coefficient of albumin in the simulated tissue samples, as determined by the spatial Fourier analysis, varied slightly with sample thickness. In contrast, when the same video images were analyzed by direct photometric analysis, the calculated diffusion coefficients were grossly inaccurate and highly dependent on sample thickness. No simple correction could be devised to ensure the accuracy of the direct photometric method of analysis.These in vitro experiments demonstrate the advantage of our new analysis for obtaining an accurate measure of the local diffusion coefficient in microscopic samples that are thick (thickness greater than the microscope depth of focus) and scatter light.

Biopolymers↗
PubMedDate not supplied

Geography of surnames in the Azores: specificity and spatial distribution analysis.

In order to obtain a better understanding of the genetic structure of the Azorean population, a specificity and spatial distribution analysis was performed, based on 2,454 different surnames present in the Azorean telephone directory (2002). We considered as specific surnames those with an absolute frequency ratio equal to or higher than 50%. The results revealed 51 specific surnames in the whole archipelago. The smallest island presents the only surname with 100% specificity (Pedras). In addition, São Miguel island, which contains 54% of the Azorean population, has the highest number of specific surnames (25 specific surnames). The spatial distribution analysis was used to detect genetic similarity between municipalities through the calculation of spatial autocorrelation (Moran's I coefficient). Of 240 surnames included in the analysis, 113 showed statistically significant patterns. Five different patterns were obtained, of which the most relevant was isolation by distance and depression (41.6%). However, 43.4% had no defined pattern. The overall correlogram shows a majority of positive values for distances lower than 49 km and between 269-309 km, indicating high similarity between closer municipalities and between distant municipalities whose populations show historic and sociocultural affinities. In conclusion, our data are in agreement with the historical background of the Azorean population.

Azores↗
PubMed2001

Spatial distribution analysis on climatic variables in northeast China.

Information ecology is a new research area of modern ecology. Here describes the spatial distribution analysis methods of four sorts of climatic variables, i.e. temperature, precipitation, relative humidity and sunshine fraction in Northeast China. First, digital terrain models was built with large-scale maps and vector data. Then trend surface analysis and interpolation method were used to analyze the spatial distribution of these four kinds of climatic variables at three temporal scale: (1) monthly data; (2) mean monthly data of thirty years, and (3) mean annual data of thirty years. Ecological information system were used for graphics analysis on the spatial distribution of these climatic variables.

Algorithms↗
PubMed2004

A spatially disaggregate analysis of road casualties in England.

Spatially disaggregate ward level data for England is used in an analysis of various area-wide factors on road casualties. Data on 8414 wards was input into a geographic information system that contained data on land use types, road characteristics and road casualties. Demographic data on area-wide deprivation (the index of multiple deprivation) for each ward was also included. Negative binomial count data models were used to analyze the associations between these factors with traffic fatalities, serious injuries and slight injuries. Results suggest that urbanized areas are associated with fewer casualties (especially fatalities) while areas of higher employment density are associated with more casualties. More deprived areas tend to have higher levels of casualties, though not of motorized casualties (except slight injuries). The effect of road characteristics are less significant but there are some positive associations with the density of "A" and "B" level roads.

Accidents, Traffic↗
PubMed2003

Space, place and movement as aspects of health care in three women's prisons.

This paper focuses on prison as a place in which the prisoner seeks health and health services. Drawing on the work of Henri LeFebvre, Edward Casey, Jeffrey Malpas, and Michel Foucault, a spatial analysis examines the constitutive roles of movement, social structure, and power in determining the prisoner's access to health care. The research methodology utilizes quantitative and qualitative analysis of women prisoners' attempts to get treatment for their health problems. The narratives of these often-failed attempts construct prison as a place where health care access is continually thwarted by rules, custodial priorities, poor health care management, incompetence, and indifference. Analysis of spatial practices, representations of space, and spaces of representation demonstrate the imposition of structural ordering, its naturalization, and the role of narrative in questioning the order, thereby creating possibilities for imaginary and real places where the prisoners' health needs can be met. Simultaneously, this analysis illuminates basic ethical questions about the limitations of human connection and medical caring in prison settings, regardless of the personal motivation of the caregiver.

Adult↗
PubMed1995

Disease models implicit in statistical tests of disease clustering.

State and local health departments investigate an increasing number of cluster allegations, for which the selection of appropriate statistical methods is an important problem. Many of the methods for the spatial analysis of health data assume, either implicitly or explicitly, some model of disease occurrence, and comparisons of methods can be difficult when their underlying disease models differ. We review some of the issues involved in the statistical analysis of spatial disease patterns and describe several methods recently proposed to detect areas of increased disease rates. The disease models upon which the methods are based are explicitly described, and they provide a useful basis for comparing alternative clustering methods.

Cluster Analysis↗