Efficient LSTM Training with Eligibility Traces

Training recurrent neural networks is predominantly achieved via backpropagation through time (BPTT). However, this algorithm is not an optimal solution from both a biological and computational perspective. A more efficient and biologically plausible alternative for BPTT is e-prop. We investigate the applicability of e-prop to long short-term memorys (LSTMs), for both supervised and reinforcement learning (RL) tasks. We show that e-prop is a suitable optimization algorithm for LSTMs by comparing it to BPTT on two benchmarks for supervised learning. This proves that e-prop can achieve learning even for problems with long sequences of several hundred timesteps. We introduce extensions that improve the performance of e-prop, which can partially be applied to other network architectures. With the help of these extensions we show that, under certain conditions, e-prop can outperform BPTT for one of the two benchmarks for supervised learning. Finally, we deliver a proof of concept for the integration of e-prop to RL in the domain of deep recurrent Q-learning

Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System

Various gait parameters can be used to assess the risk of falling in older adults. However, the state-of-the-art systems used to quantify gait parameters often come with high costs as well as training and space requirements. Gait analysis systems, which use mobile and commercially available cameras, can be an easily available, marker-free alternative. In a study with 44 participants (age ≥ 65 years), gait patterns were analyzed with three different systems: a pressure sensitive walkway system (GAITRite-System, GS) as gold standard, Motognosis Labs Software using a Microsoft Kinect Sensor (MKS), and a smartphone camera-based application (SCA). Intertrial repeatability showed moderate to excellent results for MKS (ICC(1,1) 0.574 to 0.962) for almost all measured gait parameters and moderate reliability in SCA measures for gait speed (ICC(1,1) 0.526 to 0.535). All gait parameters of MKS showed a high level of agreement with GS (ICC(2,k) 0.811 to 0.981). Gait parameters extracted with SCA showed poor reliability. The tested gait analysis systems based on different camera systems are currently only partially able to capture valid gait parameters. If the underlying algorithms are adapted and camera technology is advancing, it is conceivable that these comparatively simple methods could be used for gait analysis

A microfluidic perspective on conventional in vitro transcranial direct current stimulation methods

Transcranial direct current stimulation (tDCS) is a promising non-invasive brain stimulation method to treat neurological and psychiatric diseases. However, its underlying neural mechanisms warrant further investigation. Indeed, dose–response interrelations are poorly understood. Placing explanted brain tissue, mostly from mice or rats, into a uniform direct current electric field (dcEF) is a well-established in vitro system to elucidate the neural mechanism of tDCS. Nevertheless, we will show that generating a defined, uniform, and constant dcEF throughout a brain slice is challenging. This article critically reviews the methods used to generate and calibrate a uniform dcEF. We use finite element analysis (FEA) to evaluate the widely used parallel electrode configuration and show that it may not reliably generate uniform dcEF within a brain slice inside an open interface or submerged chamber. Moreover, equivalent circuit analysis and measurements inside a testing chamber suggest that calibrating the dcEF intensity with two recording electrodes can inaccurately capture the true EF magnitude in the targeted tissue when specific criteria are not met. Finally, we outline why microfluidic chambers are an effective and calibration-free approach of generating spatiotemporally uniform dcEF for DCS in vitro studies, facilitating accurate and fine-scale dcEF adjustments. We are convinced that improving the precision and addressing the limitations of current experimental platforms will substantially improve the reproducibility of in vitro experimental results. A better mechanistic understanding of dose–response relations will ultimately facilitate more effective non-invasive stimulation therapies in patients

Hardware-in-the-Loop Co-Simulation Based Validation of Power System Control Applications

Renewables are key enablers for the realization of a sustainable energy supply but grid operators and energy utilities have to mange their intermittent behavior and limited storage capabilities by ensuring the security of supply and power quality. Advanced control approaches, automation concepts, and communication technologies have the potential to address these challenges by providing new intelligent solutions and products. However, the validation of certain aspects of such smart grid systems, especially advanced control and automation concepts is still a challenge. The main aim of this work therefore is to introduce a hardware-in-the-loop co-simulation-based validation framework which allows the simulation of large-scale power networks and control solutions together with real-world components. The application of this concept to a selected voltage control example shows its applicability.Comment: 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE

EU-Gipfel: Kann eine Fiskalunion den Euro retten?

Ende Januar einigten sich 25 EU-Staaten in einem Fiskalpakt auf Schuldenbremsen, die sie auf eine Politik des ausgeglichenen Haushalts festlegen. Für den Fall von Abweichungen soll ein automatischer Korrekturmechanismus in die Regelungen integriert werden. Die Einfügung von Schuldenbremsen in die nationalen Gesetzgebungen soll durch den Europäischen Gerichtshof überprüft werden. Ist der Euro so zu retten?

Contactless recording of sleep apnea and periodic leg movements by nocturnal 3-D-video and subsequent visual perceptive computing

Contactless measurements during the night by a 3-D-camera are less time-consuming in comparison to polysomnography because they do not require sophisticated wiring. However, it is not clear what might be the diagnostic benefit and accuracy of this technology. We investigated 59 persons simultaneously by polysomnography and 3-D-camera and visual perceptive computing (19 patients with restless legs syndrome (RLS), 21 patients with obstructive sleep apnea (OSA), and 19 healthy volunteers). There was a significant correlation between the apnea hypopnea index (AHI) measured by polysomnography and respiratory events measured with the 3-D-camera in OSA patients (r = 0.823; p < 0.001). The receiver operating characteristic curve yielded a sensitivity of 90% for OSA with a specificity of 71.4%. In RLS patients 72.8% of leg movements confirmed by polysomnography could be detected by 3-D-video and a significant moderate correlation was found between PLM measured by polysomnography and by the 3-D-camera (RLS: r = 0.654; p = 0.004). In total, 95.4% of the sleep epochs were correctly classified by the machine learning approach, but only 32.5% of awake epochs. Further studies should investigate, if this technique might be an alternative to home sleep testing in persons with an increased pre-test probability for OSA