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- ItemWell-being in amyotrophic lateral sclerosis: A pilot experience sampling study(Lausanne : Frontiers Research Foundation, 2014) Real, R.G.; Dickhaus, T.; Ludolph, A.; Hautzinger, M.; Kübler, A.Objective: The aim of this longitudinal study was to identify predictors of instantaneous well-being in patients with amyotrophic lateral sclerosis (ALS). Based on flow theory well-being was expected to be highest when perceived demands and perceived control were in balance, and that thinking about the past would be a risk factor for rumination which would in turn reduce well-being. Methods: Using the experience sampling method, data on current activities, associated aspects of perceived demands, control, and well-being were collected from 10 patients with ALS three times a day for two weeks. Results: Results show that perceived control was uniformly and positively associated with well-being, but that demands were only positively associated with well-being when they were perceived as controllable. Mediation analysis confirmed thinking about the past, but not thinking about the future, to be a risk factor for rumination and reduced well-being. Discussion: Findings extend our knowledge of factors contributing to well-being in ALS as not only perceived control but also perceived demands can contribute to well-being. They further show that a focus on present experiences might contribute to increased well-being.
- ItemSingle pairing spike-timing dependent plasticity in BiFeO3 memristors with a time window of 25 ms to 125 μs(Lausanne : Frontiers Research Foundation, 2015) Du, Nan; Kiani, Mahdi; Mayr, Christian G.; You, Tiangui; Bürger, Danilo; Skorupa, Ilona; Schmidt, Oliver G.; Schmidt, HeidemarieMemristive devices are popular among neuromorphic engineers for their ability to emulate forms of spike-driven synaptic plasticity by applying specific voltage and current waveforms at their two terminals. In this paper, we investigate spike-timing dependent plasticity (STDP) with a single pairing of one presynaptic voltage spike and one post-synaptic voltage spike in a BiFeO3 memristive device. In most memristive materials the learning window is primarily a function of the material characteristics and not of the applied waveform. In contrast, we show that the analog resistive switching of the developed artificial synapses allows to adjust the learning time constant of the STDP function from 25 ms to 125 μs via the duration of applied voltage spikes. Also, as the induced weight change may degrade, we investigate the remanence of the resistance change for several hours after analog resistive switching, thus emulating the processes expected in biological synapses. As the power consumption is a major constraint in neuromorphic circuits, we show methods to reduce the consumed energy per setting pulse to only 4.5 pJ in the developed artificial synapses.
- ItemA monolithically integrated silicon modulator with a 10 Gb/s 5 V pp or 5.6 V pp driver in 0.25 μm SiGe:C BiCMOS(Lausanne : Frontiers Research Foundation, 2014) Goll, B.; Thomson, D.J.; Zimmermann, L.; Porte, H.; Gardes, F.Y.; Hu, Y.; Knoll, D.; Lischke, S.; Tillack, B.; Reed, G.T.; Zimmermann, H.This paper presents as a novelty a fully monolithically integrated 10 Gb/s silicon modulator consisting of an electrical driver plus optical phase modulator in 0.25 μm SiGe:C BiCMOS technology on one chip, where instead of a SOI CMOS process (only MOS transistors) a SiGe BiCMOS process (MOS transistors and fast SiGe bipolar transistors) is implemented. The fastest bipolar transistors in the BiCMOS product line used have a transit frequency of f t ≈ 120 GHz and a collector-emitter breakdown voltage of BV CE0 = 2.2 V (IHP SG25H3). The main focus of this paper will be given to the electronic drivers, where two driver variants are implemented in the test chips. Circuit descriptions and simulations, which treat the influences of noise and bond wires, are presented. Measurements at separate test chips for the drivers show that the integrated driver variant one has a low power consumption in the range of 0.66 to 0.68 W but a high gain of S 21 = 37 dB. From the large signal point of view this driver delivers an inverted as well as a non-inverted output data signal between 0 and 2.5 V (5 V pp differential). Driver variant one is supplied with 2.5 V and with 3.5 V. Bit-error-ratio (BER) measurements resulted in a BER better than 10 −12 for voltage differences of the input data stream down to 50 mV pp . Driver variant two, which is an adapted version of driver variant one, is supplied with 2.5 and 4.2 V, consumes 0.83 to 0.87 W, delivers a differential data signal with 5.6 V pp at the output and has a gain of S 21 = 40 dB. The chip of the fully integrated modulator occupies an area of 12.3 mm 2 due to the photonic components. Measurements with a 240 mV pp electrical input data stream, 1.25 V input common-mode voltage and for an optical input wavelength of 1540 nm resulted in an extinction ratio of 3.3 dB for 1 mm long RF phase shifters in each modulator arm driven by driver variant one and a DC tuning voltage of 1.2 V. The extinction ratio was 8.4 dB at a DC tuning voltage of 7 V for a device with 2 mm long RF phase shifters in each arm and driver variant two.
- ItemHigh-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing(Lausanne : Frontiers Research Foundation, 2015) Mohammadi, Siawoosh; Tabelow, Karsten; Ruthotto, Lars; Feiweier, Thorsten; Polzehl, Jörg; Weiskopf, NikolausDiffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g., intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2–3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1 mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view (rFoV) imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e., produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.
- ItemHow to test the “quantumness” of a quantum computer?(Lausanne : Frontiers Research Foundation, 2014) Zagoskin, A.M.; Il’ichev, E.; Grajcar, M.; Betouras, J.J.; Nori, F.Recent devices, using hundreds of superconducting quantum bits, claim to perform quantum computing. However, it is not an easy task to determine and quantify the degree of quantum coherence and control used by these devices. Namely, it is a difficult task to know with certainty whether or not a given device (e.g., the D-Wave One or D-Wave Two) is a quantum computer. Such a verification of quantum computing would be more accessible if we already had some kind of working quantum computer, to be able to compare the outputs of these various computing devices. Moreover, the verification process itself could strongly depend on whether the tested device is a standard (gate-based) or, e.g., an adiabatic quantum computer. Here we do not propose a technical solution to this quantum-computing “verification problem,” but rather outline the problem in a way which would help both specialists and non-experts to see the scale of this difficult task, and indicate some possible paths toward its solution.
- ItemOrder patterns networks (orpan) - A method to estimate time-evolving functional connectivity from multivariate time series(Lausanne : Frontiers Research Foundation, 2012) Schinkel, S.; Zamora-López, G.; Dimigen, O.; Sommer, W.; Kurths, J.Complex networks provide an excellent framework for studying the function of the human brain activity. Yet estimating functional networks from measured signals is not trivial, especially if the data is non-stationary and noisy as it is often the case with physiological recordings. In this article we propose a method that uses the local rank structure of the data to define functional links in terms of identical rank structures. The method yields temporal sequences of networks which permits to trace the evolution of the functional connectivity during the time course of the observation. We demonstrate the potentials of this approach with model data as well as with experimental data from an electrophysiological study on language processing.
- ItemCortical hot spots and labyrinths: Why cortical neuromodulation for episodic migraine with aura should be personalized(Lausanne : Frontiers Research Foundation, 2015) Dahlem, M.A.; Schmidt, B.; Bojak, I.; Boie, S.; Kneer, F.; Hadjikhani, N.; Kurths, J.