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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.
- ItemA Leak in the Academic Pipeline : Identity and Health Among Postdoctoral Women(Lausanne : Frontiers Research Foundation, 2019) Ysseldyk, Renate; Greenaway, Katharine H.; Hassinger, Elena; Zutrauen, Sarah; Lintz, Jana; Bhatia, Maya P.; Frye, Margaret; Starkenburg, Else; Tai, VeraSeveral challenges (e.g., sexism, parental leave, the glass ceiling, etc.) disproportionately affect women in academia (and beyond), and thus perpetuate the leaky pipeline metaphor for women who opt-out of an academic career. Although this pattern can be seen at all levels of the academic hierarchy, a critical time for women facing such challenges is during the postdoctoral stage, when personal life transitions and professional ambitions collide. Using a social identity approach, we explore factors affecting the mental health of postdoctoral women, including identity development (e.g., as a mother, a scientist) and lack of control (uncertainty about one’s future personal and professional prospects), which likely contribute to the leak from academia. In this mixed-method research, Study 1 comprised interviews with postdoctoral women in North America (n = 13) and Europe (n = 8) across a range disciplines (e.g., psychology, physics, political science). Common themes included the negative impact of career uncertainty, gender-based challenges (especially sexism and maternity leave), and work-life balance on mental and physical health. However, interviewees also described attempts to overcome gender inequality and institutional barriers by drawing on support networks. Study 2 comprised an online survey of postdoctoral women (N = 146) from a range of countries and academic disciplines to assess the relationships between social identification (e.g., disciplinary, gender, social group), perceived control (i.e., over work and life), and mental health (i.e., depression, anxiety, stress, and life satisfaction). Postdoctoral women showed mild levels of stress and depression, and were only slightly satisfied with life. They also showed only moderate levels of perceived control over one’s life and work. However, hierarchical regression analyses revealed that strongly identifying with one’s discipline was most consistently positively associated with both perceived control and mental health. Collectively, these findings implicate the postdoctoral stage as being stressful and tenuous for women regardless of academic background or nationality. They also highlight the importance of disciplinary identity as a potentially protective factor for mental health that, in turn, may diminish the rate at which postdoctoral women leak from the academic pipeline.
- 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.
- ItemSynaptic Plasticity in Memristive Artificial Synapses and Their Robustness Against Noisy Inputs(Lausanne : Frontiers Research Foundation, 2021) Du, Nan; Zhao, Xianyue; Chen, Ziang; Choubey, Bhaskar; Di Ventra, Massimiliano; Skorupa, Ilona; Bürger, Danilo; Schmidt, HeidemarieEmerging brain-inspired neuromorphic computing paradigms require devices that can emulate the complete functionality of biological synapses upon different neuronal activities in order to process big data flows in an efficient and cognitive manner while being robust against any noisy input. The memristive device has been proposed as a promising candidate for emulating artificial synapses due to their complex multilevel and dynamical plastic behaviors. In this work, we exploit ultrastable analog BiFeO3 (BFO)-based memristive devices for experimentally demonstrating that BFO artificial synapses support various long-term plastic functions, i.e., spike timing-dependent plasticity (STDP), cycle number-dependent plasticity (CNDP), and spiking rate-dependent plasticity (SRDP). The study on the impact of electrical stimuli in terms of pulse width and amplitude on STDP behaviors shows that their learning windows possess a wide range of timescale configurability, which can be a function of applied waveform. Moreover, beyond SRDP, the systematical and comparative study on generalized frequency-dependent plasticity (FDP) is carried out, which reveals for the first time that the ratio modulation between pulse width and pulse interval time within one spike cycle can result in both synaptic potentiation and depression effect within the same firing frequency. The impact of intrinsic neuronal noise on the STDP function of a single BFO artificial synapse can be neglected because thermal noise is two orders of magnitude smaller than the writing voltage and because the cycle-to-cycle variation of the current–voltage characteristics of a single BFO artificial synapses is small. However, extrinsic voltage fluctuations, e.g., in neural networks, cause a noisy input into the artificial synapses of the neural network. Here, the impact of extrinsic neuronal noise on the STDP function of a single BFO artificial synapse is analyzed in order to understand the robustness of plastic behavior in memristive artificial synapses against extrinsic noisy input.
- ItemIncreasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface(Lausanne : Frontiers Research Foundation, 2018) Maksimenko, Vladimir A.; Hramov, Alexander E.; Frolov, Nikita S.; Lüttjohann, Annika; Nedaivozov, Vladimir O.; Grubov, Vadim V.; Runnova, Anastasia E.; Makarov, Vladimir V.; Kurths, Jürgen; Pisarchik, Alexander N.Brain-computer interfaces (BCIs) attract a lot of attention because of their ability to improve the brain's efficiency in performing complex tasks using a computer. Furthermore, BCIs can increase human's performance not only due to human-machine interactions, but also thanks to an optimal distribution of cognitive load among all members of a group working on a common task, i.e., due to human-human interaction. The latter is of particular importance when sustained attention and alertness are required. In every day practice, this is a common occurrence, for example, among office workers, pilots of a military or a civil aircraft, power plant operators, etc. Their routinely work includes continuous monitoring of instrument readings and implies a heavy cognitive load due to processing large amounts of visual information. In this paper, we propose a brain-to-brain interface (BBI) which estimates brain states of every participant and distributes a cognitive load among all members of the group accomplishing together a common task. The BBI allows sharing the whole workload between all participants depending on their current cognitive performance estimated from their electrical brain activity. We show that the team efficiency can be increased due to redistribution of the work between participants so that the most difficult workload falls on the operator who exhibits maximum performance. Finally, we demonstrate that the human-to-human interaction is more efficient in the presence of a certain delay determined by brain rhythms. The obtained results are promising for the development of a new generation of communication systems based on neurophysiological brain activity of interacting people. Such BBIs will distribute a common task between all group members according to their individual physical conditions.
- ItemBasins of attraction of chimera states on networks(Lausanne : Frontiers Research Foundation, 2022) Li, Qiang; Larosz, Kelly C.; Han, Dingding; Ji, Peng; Kurths, JürgenNetworks of identical coupled oscillators display a remarkable spatiotemporal pattern, the chimera state, where coherent oscillations coexist with incoherent ones. In this paper we show quantitatively in terms of basin stability that stable and breathing chimera states in the original two coupled networks typically have very small basins of attraction. In fact, the original system is dominated by periodic and quasi-periodic chimera states, in strong contrast to the model after reduction, which can not be uncovered by the Ott-Antonsen ansatz. Moreover, we demonstrate that the curve of the basin stability behaves bimodally after the system being subjected to even large perturbations. Finally, we investigate the emergence of chimera states in brain network, through inducing perturbations by stimulating brain regions. The emerged chimera states are quantified by Kuramoto order parameter and chimera index, and results show a weak and negative correlation between these two metrics.
- 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.