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Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.
To handle heterogeneity within students, to foster needed generic
competencies, to motivate them, and to increase their employability, a didactical method to teach and learn programming in non-major degree programs shall be found. Therefore, this paper covers strategies and the theoretical underpinning concerning these four challenges and gives solutions how to cope with them. Finally, Pair Programming is presented as a method that addresses the issues introduced here.
High angular resolution, large collecting area and reduced weight per unit area are required for astronomical X-ray telescopes of the next generation observatories. New technologies for processing X-ray mirrors are under development to fulfill these needs. One option is to realize a Wolter I type telescope constituted of several hundred nested thin and light-weight X-ray mirror segments. The individual mirror segments need to be coated with an about 100 nm thick film of a high-reflective material to enhance the reflectivity for X-rays. Thereby an accurate shape metrology of the segments is necessary to predict the angular resolution of the astronomical telescope as well as to control the development process of X-ray mirrors. We present the challenges in shape measurements of thin glasses used to control the coating process and first experimental results about the repeatability of the measurements.