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PubMed1997

Light-Dependent Spatial and Temporal Expression of Pigment Regulatory Genes in Developing Maize Seeds.

Both light and developmental stimuli are directly involved in the regulation of plant gene expression. In maize, activation of the anthocyanin pathway represents an excellent model system for studying the interactions between an external factor, such as light, and internal factors that regulate plant and seed development. By analyzing in detail the aleurone and pericarp seed layers, different developmental windows for light have been found in the two tissues[mdash]the former in the advanced stages of development and the latter in the early stages of seed development. Transcriptional control of the structural genes involved in anthocyanin deposition within the pericarp is known to be exerted by the Sn and pl genes, whereas the aleurone is controlled by the R and C1 regulatory genes. By using in situ hybridization analysis, we detected tissue-specific expression of Sn and R in the seed layers, revealing a correlation between structural gene activation and anthocyanin accumulation. In addition, RNA gel blot analysis revealed that Sn expression is enhanced by light, whereas the R gene expression is not. However, the light-induced expression of the myb-type genes C1 and pl, detected by reverse transcriptase-polymerase chain reaction, was found to be the limiting factor for conferring the developmental competence of the pericarp and the aleurone layers to light responsiveness.

Journal Article↗
PubMed2005

Odorant-dependent, spatially restricted induction of c-fos in the olfactory epithelium of the mouse.

Volatile odorous chemicals are detected by around a thousand different G protein-coupled odorant receptors in the mouse. We demonstrated that exposure of the behaving mouse to odorant for a few minutes led to induction of the immediate early gene c-fos for several hours in a fraction of the olfactory sensory neurones in the nasal cavity. Associated with this odorant-specific induction event was activation of extracellular-regulated kinase (ERK)1/2 that preceded increased c-fos expression. The distribution of odorant-activated neurones mimicked the scattered and spatially limited distribution of neurones expressing a single odorant receptor gene. A small change in odorant chemical structure caused a zonal shift in the spatial distribution of activated neurones, suggesting that the gene expression change resulted from specific receptor interaction. Repeated exposure to odorant or use of different concentrations did not change the pattern of c-fos induction. These results indicate that odorant-induced c-fos expression can be used to visualize odorant representations in the olfactory epithelium that reflect late cellular events regulated by adequate odorant receptor stimulation.

Animals↗
PubMed1995

Spatially dependent acoustic cues generated by the external ear of the big brown bat, Eptesicus fuscus.

To measure the directionality of the external ear of the echolocating bat, Eptesicus fuscus, the left or right eardrum of a dead bat was replaced by a microphone which recorded signals received from a sound source that was moved around the stationary head. The test signal was a 0.5-ms FM sweep from 100 kHz to 10 kHz (covering all frequencies in the bat's biosonar sounds). Notches and peaks in transfer functions for 7 tested ears varied systematically with changes in elevation. For the most prominent notch, center frequency decreased from about 50 kHz for elevations at or near the horizontal to 30-40 kHz for elevations 30 degrees-40 degrees below the horizontal. A second notch shifted from about 85 kHz to 70 kHz over these same elevations. Above the horizontal, a peak that flanks these notches changed in amplitude by 15 dB with changes in elevation. Removal of the tragus from the external ear disrupted the systematic movement of notch frequencies with elevation but did not disrupt changes in the peak's amplitude. Smaller changes in notch frequency also occurred with changes in azimuth, so monaural notch information alone cannot determine the position of sound sources away from the median plane. However, because bats routinely keep the head pointed at the target's azimuth, median-plane localization occurs with monaural cues delivered to the two ears. Corresponding changes with elevation occurred in the impulse-response, which consists of a series of 3-6 peaks spaced 10-20 microseconds apart. The time separation of two prominent impulse peaks systematically increased from 22-26 microseconds above the horizontal to about 36-40 microseconds below the horizontal, and removal of the tragus disrupted this time shift below the horizontal.

Animals↗
PubMed1995

Improved lesion detection by level-dependent spatial summation.

A novel signal postprocessing method has been developed for application in lesion detection. A signal distribution, directly related to the 2-dimensional envelope distribution comprising a B-mode image, is convolved with a block shaped kernel of which both base area (i.e. window size) and height are modulated by the local signal level. A theoretical analysis shows that the output includes information regarding the local mean brightness in the original image. This information can be displayed as a gray scale image. The predicted behavior agrees with experimental observations. On the basis of twenty simulated lesion images, it is demonstrated that the present algorithm is superior to the conventional L2-mean filter in lesion detection problems, whereby the performance is quantified by the area AROC under the Receiver Operating Characteristic. An improvement in the median value of AROC of the order of 0.1 was observed. Two parameters are used for adjustment. The total number of summations involved in the processing of a frame is comparable to the number required by the arithmetic mean filter, allowing real-time implementation.

Algorithms↗
PubMed1985

Intensity-dependent spatial summation.

Psychophysical evidence indicates that, in the human retina, the size of the spatial-summation area decreases as illuminance increases. Such a relationship would be beneficial for the detection of spatial contrast in the presence of photon noise. We analyze an image-processing mechanism in which the area of a strictly positive point-spread function varies inversely with local illuminance while its volume remains constant. In addition to its expected effect of improving spatial resolution as illuminance increases, this mechanism also yields center-surround antagonism and all other manifestations of bandpass filtering and accounts for Ricco's law and Weber's law--including the failures of both laws as a function of test conditions. The relationship between this mechanism and lateral inhibition is analyzed.

Humans↗
PubMed1997

Steroid Hormone Modulation of Hippocampal Dependent Spatial Memory.

Recent studies show that the adult CNS is capable of considerable re-structuring and re-growth, a property previously thought limited to the developmental period. Hormones play an important role in many of these plastic processes, and the hippocampus, as a target for all the major classes of steroid hormones, undergoes considerable remodeling. Since it is critical for mediating tasks requiring spatial memory, the hippocampus can serve as an important model for understanding not only the mechanisms underlying plasticity of brain circuits but also how these changes impact on a higher order function, spatial memory. In this review, the effects of steroid hormones on hippocampal remodeling are discussed, and the ability of estradiol to enhance spatial memory as well as the ability of both excessive or diminished corticosteroid levels to impair spatial memory are described. The neural mechanisms for these effects, as well as previous and current contributions of McEwen and colleagues to this expanding area of research, are discussed.

Journal Article↗
PubMed2005

[Spatial variance characters of urban synthesis pattern indices at different scales].

Scale holds the key to understand pattern-process interactions, and indeed, becomes one of the corner-stone concepts in landscape ecology. Geographic Information System and remote sensing techniques provide an effective tool to characterize the spatial pattern and spatial heterogeneity at different scales. As an example, these techniques are applied to analyze the urban landscape diversity index, contagion index and fractal dimension on the SPOT remote sensing images at four scales. This paper modeled the semivariogram of these three landscape indices at different scales, and the results indicated that the spatial variance characters of diversity index, contagion index and fractal dimension were similar at different scales, which was spatial dependence. The spatial dependence was showed at each scale, the smaller the scale, the stronger the spatial dependence. With the scale reduced, more details of spatial variance were discovered. The contribution of spatial autocorrelation of these three indices to total spatial variance increased gradually, but when the scale was quite small, spatial variance analysis would destroy the interior structure of landscape system. The semivariogram models of different landscape indices were very different at the same scale, illuminating that these models were incomparable at different scales. According to above analyses and based on the study of urban land use structure, 1 km extent was the more perfect scale for studying the spatial variance of urban landscape pattern in Shanghai. The spatial variance of landscape indices had the character of scale-dependence, and was a function of scale. The results differed at different scales we chose, and thus, the influence of scales on pattern could not be neglected in the research of landscape ecology. The changes of these three landscape indices displayed the regularity of urban spatial structure at different scales, i. e., they were complicated and no regularity at small scale, polycentric at moderate scale, and circle-zoning at big scale.

City Planning↗
PubMed2001

Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

Independent component analysis (ICA) is a technique that attempts to separate data into maximally independent groups. Achieving maximal independence in space or time yields two varieties of ICA meaningful for functional MRI (fMRI) applications: spatial ICA (SICA) and temporal ICA (TICA). SICA has so far dominated the application of ICA to fMRI. The objective of these experiments was to study ICA with two predictable components present and evaluate the importance of the underlying independence assumption in the application of ICA. Four novel visual activation paradigms were designed, each consisting of two spatiotemporal components that were either spatially dependent, temporally dependent, both spatially and temporally dependent, or spatially and temporally uncorrelated, respectively. Simulated data were generated and fMRI data from six subjects were acquired using these paradigms. Data from each paradigm were analyzed with regression analysis in order to determine if the signal was occurring as expected. Spatial and temporal ICA were then applied to these data, with the general result that ICA found components only where expected, e.g., S(T)ICA "failed" (i.e., yielded independent components unrelated to the "self-evident" components) for paradigms that were spatially (temporally) dependent, and "worked" otherwise. Regression analysis proved a useful "check" for these data, however strong hypotheses will not always be available, and a strength of ICA is that it can characterize data without making specific modeling assumptions. We report a careful examination of some of the assumptions behind ICA methodologies, provide examples of when applying ICA would provide difficult-to-interpret results, and offer suggestions for applying ICA to fMRI data especially when more than one task-related component is present in the data.

Algorithms↗
PubMed2003

The impact of spatial structure on the accuracy of contour maps of small data sets.

Spatial analysis of insect counts provides important information about how insect species respond to the heterogeneity of a given sampling space. Contour mapping is widely used to visualize spatial pest distribution patterns in anthropogenic environments, and in this study we outlined recommendations regarding semivariogram analysis of small data sets (N < 50). Second, we examined how contour maps based upon linear kriging were affected by the spatial structure of the given data set, as error estimation of contour maps appears to have received little attention in the entomological domain. We used weekly trap catches of the warehouse beetle, Trogoderma variabile, and the accuracy assessment was based upon data sets that had either a random spatial structure or were characterized by asymptotic spatial dependence. Asymptotic spatial dependence (typically described with a semivariogram analysis) means that trap catches at locations close to each other are more similar than trap catches at locations further apart. Trap catches were poorly predicted for data sets with a random spatial structure, while there was a significant correlation between observed and predicted trap catches for the spatially rearranged data sets. Therefore, for data sets with a random spatial structure we recommend visualization of the insect counts as scale-sized dots rather than as contour maps.

Animals↗
PubMed2006

Assessment of spatial variability in some soil properties as related to soil salinity and alkalinity in Bafra plain in northern Turkey.

The objectives of this study were to assess the variability in soil properties affecting salinity and alkalinity, and to analyze spatial distribution patterns of salinity (EC) and alkalinity (ESP) in the plain, which was used irrigation agriculture with low quality waters. Soil samples were collected from 0-30 cm, 30-60 cm, 60-90 cm and 90-120 cm soil depths at 60 sampling sites. Soil pH had the minimum variability, and hydraulic conductivity (Ks) had the maximum variability at all depths. The mean values of pH, EC, ESP and Ks increased while the mean values of CEC decreased with soil depth. Values pH, EC and ESP were generally high in the east and northeastern sides. Soil properties indicated moderate to strong spatial dependence. ESP and pH were moderately spatially dependent for three of the four depths, EC exhibited moderate spatial dependence for one of the four depths, CEC had a moderate spatial dependence at all depths, and Ks exhibited a strong spatial dependence. EC, CEC, and ESP were considerably variable in small distances. The spatial variability in small distances of EC, CEC, pH and ESP generally increased with depth. All geostatistical range values were greater than 1230 m. It was inferred that the strong spatial dependency of soil properties would be resulted in extrinsic factors such as ground water level, drainage, irrigation systems and microtopography.

Agriculture↗
PubMed2005

Characterization of the spatial dispersion of corn root injury by corn rootworms (Coleoptera: Chrysomelidae).

The dispersion of root injury to Zea mays L. by corn rootworm, Diabrotica spp., larvae was characterized using geostatistics to determine the appropriate sampling distance to obtain independent estimates of root injury. We also investigated the effect of the root injury levels on the spatial dependence of root injury at three different spatial scales: large-scale study with 25-m sampling distance in three, 8-ha fields; moderate-scale study with 0.2-m sampling distance in six, 2-ha fields; and small-scale study with exhaustive sampling in eight, 12-m(2) plots within cornfields. In the large-scale study, a nugget model best fit the semivariograms, indicating the dispersion of root injury exhibited a random pattern. In the moderate-scale study, all the semivariograms were best fit with an exponential model, and 68 to 96% of the variability was explained by spatial dependence, suggesting a high degree of spatial aggregation of corn root larval injury. The ranges of semivariograms fell within < 4 m, except one field that had the range of 14.7 m. In the small-scale study, the Gaussian, exponential, or spherical models fit the semivariograms best and 50 to 89% of the variability was explained by spatial dependence, suggesting spatial aggregation of root injury. The ranges of semivariograms were from 0.35 to 1.04 m. In the small-scale study, the degree of spatial dependence increased significantly (P < 0.05) as the average root injury increased within the range of root injury observed in the study. These results suggest that the minimum distance between root samples in small-plot insecticide trials should be > 1 m within a row to obtain unbiased estimates of root injury.

Animals↗
PubMed2001

Binocularity and spatial frequency dependence of calcarine activation in two types of amblyopia.

OBJECTIVE AND BACKGROUND: Strabismus and anisometropia early in life frequently causes monocular amblyopia. Activation of the visual cortex is compared between the two types of amblyopia to elucidate differences in the pathogenetic mechanism of the disease. METHODS: Using an EPI gradient echo sequence in 1.5T MRI, calcarine activation by monocular viewing of checkerboard patterns with reversal was examined in terms of binocularity of the activation and dependence on the spatial frequency of the stimuli. RESULTS: First, the proportion of voxels activated by both normal and amblyopic eye monocular stimulations is lower in the strabismic group than in the anisometropic group. Second, the activation by higher-spatial-frequency stimuli is reduced in the anisometropic group, but not in the strabismic group. CONCLUSIONS: These findings from the human visual cortex are consistent with the view proposed based on animal research that the loss of binocular interaction and the undersampling of high-spatial-frequency components of visual stimuli are each one of the underlying changes in strabismic and anisometropic amblyopia, respectively.

Adolescent↗