945 resultados para temporal and spatial renderings
Resumo:
Cortical dynamics can be imaged at high spatiotemporal resolution with voltage-sensitive dyes (VSDs) and calcium-sensitive dyes (CaSDs). We combined these two imaging techniques using epifluorescence optics together with whole cell recordings to measure the spatiotemporal dynamics of activity in the mouse somatosensory barrel cortex in vitro and in the supragranular layers in vivo. The two optical signals reported distinct aspects of cortical function. VSD fluorescence varied linearly with membrane potential and was dominated by subthreshold postsynaptic potentials, whereas the CaSD signal predominantly reflected local action potential firing. Combining VSDs and CaSDs allowed us to monitor the synaptic drive and the spiking activity of a given area at the same time in the same preparation. The spatial extent of the two dye signals was different, with VSD signals spreading further than CaSD signals, reflecting broad subthreshold and narrow suprathreshold receptive fields. Importantly, the signals from the dyes were differentially affected by pharmacological manipulations, stimulation strength, and depth of isoflurane anesthesia. Combined VSD and CaSD measurements can therefore be used to specify the temporal and spatial relationships between subthreshold and suprathreshold activity of the neocortex.
Resumo:
Magmatic volatiles play a crucial role in volcanism, from magma production at depth to generation of seismic phenomena to control of eruption style. Accordingly, many models of volcano dynamics rely heavily on behavior of such volatiles. Yet measurements of emission rates of volcanic gases have historically been limited, which has restricted model verification to processes on the order of days or longer. UV cameras are a recent advancement in the field of remote sensing of volcanic SO2 emissions. They offer enhanced temporal and spatial resolution over previous measurement techniques, but need development before they can be widely adopted and achieve the promise of integration with other geophysical datasets. Large datasets require a means by which to quickly and efficiently use imagery to calculate emission rates. We present a suite of programs designed to semi-automatically determine emission rates of SO2 from series of UV images. Extraction of high temporal resolution SO2 emission rates via this software facilitates comparison of gas data to geophysical data for the purposes of evaluating models of volcanic activity and has already proven useful at several volcanoes. Integrated UV camera and seismic measurements recorded in January 2009 at Fuego volcano, Guatemala, provide new insight into the system’s shallow conduit processes. High temporal resolution SO2 data reveal patterns of SO2 emission rate relative to explosions and seismic tremor that indicate tremor and degassing share a common source process. Progressive decreases in emission rate appear to represent inhibition of gas loss from magma as a result of rheological stiffening in the upper conduit. Measurements of emission rate from two closely-spaced vents, made possible by the high spatial resolution of the camera, help constrain this model. UV camera measurements at Kilauea volcano, Hawaii, in May of 2010 captured two occurrences of lava filling and draining within the summit vent. Accompanying high lava stands were diminished SO2 emission rates, decreased seismic and infrasonic tremor, minor deflation, and slowed lava lake surface velocity. Incorporation of UV camera data into the multi-parameter dataset gives credence to the likelihood of shallow gas accumulation as the cause of such events.
Resumo:
Vegetation phenology is an important indicator of climate change and climate variability and it is strongly connected to biospheric–atmospheric gas exchange. We aimed to evaluate the applicability of phenological information derived from digital imagery for the interpretation of CO2 exchange measurements. For the years 2005–2007 we analyzed seasonal phenological development of 2 temperate mixed forests using tower-based imagery from standard RGB cameras. Phenological information was jointly analyzed with gross primary productivity (GPP) derived from net ecosystem exchange data. Automated image analysis provided reliable information on vegetation developmental stages of beech and ash trees covering all seasons. A phenological index derived from image color values was strongly correlated with GPP, with a significant mean time lag of several days for ash trees and several weeks for beech trees in early summer (May to mid-July). Leaf emergence dates for the dominant tree species partly explained temporal behaviour of spring GPP but were also masked by local meteorological conditions. We conclude that digital cameras at flux measurement sites not only provide an objective measure of the physiological state of a forest canopy at high temporal and spatial resolutions, but also complement CO2 and water exchange measurements, improving our knowledge of ecosystem processes.
Impact of Orthorectification and Spatial Sampling on Maximum NDVI Composite Data in Mountain Regions
Resumo:
Objectives: Although behavioral studies have demonstrated that normative affective traits modulate the processing of facial and emotionally charged stimuli, direct electrophysiological evidence for this modulation is still lacking. Methods: Event-related potential (ERP) data associated with personal, traitlike approach- or withdrawal-related attitude (assessed post-recording and 14 months later) were investigated in 18 subjects during task-free (i.e. unrequested, spontaneous) emotional evaluation of faces. Temporal and spatial aspects of 27 channel ERP were analyzed with microstate analysis and low resolution electromagnetic tomography (LORETA), a new method to compute 3 dimensional cortical current density implemented in the Talairach brain atlas. Results: Microstate analysis showed group differences 132-196 and 196-272 ms poststimulus, with right-shifted electric gravity centers for subjects with negative affective attitude. During these (over subjects reliably identifiable) personality-modulated, face-elicited microstates, LORETA revealed activation of bilateral occipito-temporal regions, reportedly associated with facial configuration extraction processes. Negative compared to positive affective attitude showed higher activity right temporal; positive compared to negative attitude showed higher activity left temporo-parieto-occipital. Conclusions: These temporal and spatial aspects suggest that the subject groups differed in brain activity at early, automatic, stimulus-related face processing steps when structural face encoding (configuration extraction) occurs. In sum, the brain functional microstates associated with affect-related personality features modulate brain mechanisms during face processing already at early information processing stages.
Resumo:
The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.
Resumo:
Although we have amassed extensive catalogues of signalling network components, our understanding of the spatiotemporal control of emergent network structures has lagged behind. Dynamic behaviour is starting to be explored throughout the genome, but analysis of spatial behaviours is still confined to individual proteins. The challenge is to reveal how cells integrate temporal and spatial information to determine specific biological functions. Key findings are the discovery of molecular signalling machines such as Ras nanoclusters, spatial activity gradients and flexible network circuitries that involve transcriptional feedback. They reveal design principles of spatiotemporal organization that are crucial for network function and cell fate decisions.