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In this paper, we report on a systematic study of a soft X-ray Gas Electron Multiplier (GEM) detector built with aluminium-clad kapton GEM foils. The primary objective of this research is to comprehend the performance of this type of detector when irradiated with soft energy photons. The results are analysed and discussed with a particular focus on the long-term detector stability, as well as its gas gain and energy resolution uniformity across the detector area. Presented results lead us to the conclusion that the aluminium based GEM detector is a promising device to suppress the X-ray Fluorescence (XRF) background, simultaneously providing very good stability during long-term measurement campaigns.
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In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat's brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.
Asunto(s)
Encéfalo , Neuronas , Animales , Estimulación Eléctrica , Electrónica , Microelectrodos , RatasRESUMEN
The goal of the work was to investigate the possible application of factor analysis methods for processing X-ray Fluorescence (XRF) data acquired with a full-field XRF spectrometer employing a position-sensitive and energy-dispersive Gas Electron Multiplier (GEM) detector, which provides only limited energy resolution at a level of 18% Full Width at Half Maximum (FWHM) at 5.9 keV. In this article, we present the design and performance of the full-field imaging spectrometer and the results of case studies performed using the developed instrument. The XRF imaging data collected for two historical paintings are presented along with the procedures applied to data calibration and analysis. The maps of elemental distributions were built using three different analysis methods: Region of Interest (ROI), Non-Negative Matrix Factorisation (NMF), and Principal Component Analysis (PCA). The results obtained for these paintings show that the factor analysis methods NMF and PCA provide significant enhancement of selectivity of the elemental analysis in case of limited energy resolution of the spectrometer.
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In this paper, we report on the systematic study of different variants of X-ray detectors based on GEM technology using modified GEM foils with greatly reduced amount of copper. The main goal of this study was understanding the performance of such detectors applied in X-Ray Fluorescence (XRF) elemental analysis. Reduction of the amount of copper in the detector structure is crucial for suppression of XRF background from copper, but one has to ensure that key detector parameters are not affected by such modification. The tested detector variants include detectors with different types of copper-less GEM foils, which have been manufactured starting from standard copper-clad foils and removing partially the copper layer in additional post-processing steps. The results are analyzed and discussed with a particular focus on the energy resolution, uniformity of gas gain and energy resolution across the detector area, and on the long-term stability of the gas gain. Long-term stability tests performed for selected detectors do not indicate for any accelerated aging of the copper-less detectors compared to standard detectors using copper-clad GEM foils. The presented results lead us to conclude that the copper-less GEM detectors are promising devices to suppress the XRF background.
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Local Field Potential (LFP), despite its name, often reflects remote activity. Depending on the orientation and synchrony of their sources, both oscillations and more complex waves may passively spread in brain tissue over long distances and be falsely interpreted as local activity at such distant recording sites. Here we show that the whisker-evoked potentials in the thalamic nuclei are of local origin up to around 6 ms post stimulus, but the later (7-15 ms) wave is overshadowed by a negative component reaching from cortex. This component can be analytically removed and local thalamic LFP can be recovered reliably using Current Source Density analysis. We used model-based kernel CSD (kCSD) method which allowed us to study the contribution of local and distant currents to LFP from rat thalamic nuclei and barrel cortex recorded with multiple, non-linear and non-regular multichannel probes. Importantly, we verified that concurrent recordings from the cortex are not essential for reliable thalamic CSD estimation. The proposed framework can be used to analyze LFP from other brain areas and has consequences for general LFP interpretation and analysis.