Large-Area Synthesis of Ferromagnetic Fe5- x GeTe2 /Graphene van der Waals Heterostructures with Curie Temperature above Room Temperature.

Van der Waals (vdW) heterostructures combining layered ferromagnets and other 2D crystals are promising building blocks for the realization of ultracompact devices with integrated magnetic, electronic, and optical functionalities. Their implementation in various technologies depends strongly on the development of a bottom-up scalable synthesis approach allowing for realizing highly uniform heterostructures with well-defined interfaces between different 2D-layered materials. It is also required that each material component of the heterostructure remains functional, which ideally includes ferromagnetic order above room temperature for 2D ferromagnets. Here, it is demonstrated that the large-area growth of Fe5- x GeTe2 /graphene heterostructures is achieved by vdW epitaxy of Fe5- x GeTe2 on epitaxial graphene. Structural characterization confirms the realization of a continuous vdW heterostructure film with a sharp interface between Fe5- x GeTe2 and graphene. Magnetic and transport studies reveal that the ferromagnetic order persists well above 300 K with a perpendicular magnetic anisotropy. In addition, epitaxial graphene on SiC(0001) continues to exhibit a high electronic quality. These results represent an important advance beyond nonscalable flake exfoliation and stacking methods, thus marking a crucial step toward the implementation of ferromagnetic 2D materials in practical applications.

Macroscopic information-based taste representations in insular cortex are shaped by stimulus concentration.

Taste processing is an essential ability in all animals signaling potential harm or benefit of ingestive behavior. However, current evidence for cortical taste representations remains contradictory. To address this issue, high-resolution functional MRI (fMRI) and multivariate pattern analysis were used to characterize taste-related informational content in human insular cortex, which contains primary gustatory cortex. Human participants judged pleasantness and intensity of low- and high-concentration tastes (salty, sweet, sour, and bitter) in two fMRI experiments on two different days to test for task- and concentration-invariant taste representations. We observed patterns of fMRI activity within insular cortex narrowly tuned to specific tastants consistently across tasks in all participants. Fewer patterns responded to more than one taste category. Importantly, changes in taste concentration altered the spatial layout of putative taste-specific patterns with distinct, almost nonoverlapping patterns for each taste category at different concentration levels. Together, our results point at macroscopic representations in human insular cortex as a complex function of taste category and concentration rather than representations based solely on taste identity.

Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns.

An increasing number of studies have investigated the relationships between inter-individual variability in brain regions' connectivity and behavioral phenotypes, making use of large population neuroimaging datasets. However, the replicability of brain-behavior associations identified by these approaches remains an open question. In this study, we examined the cross-dataset replicability of brain-behavior association patterns for fluid cognition and openness predictions using a previously developed region-wise approach, as well as using a standard whole-brain approach. Overall, we found moderate similarity in patterns for fluid cognition predictions across cohorts, especially in the Human Connectome Project Young Adult, Human Connectome Project Aging, and Enhanced Nathan Kline Institute Rockland Sample cohorts, but low similarity in patterns for openness predictions. In addition, we assessed the generalizability of prediction models in cross-dataset predictions, by training the model in one dataset and testing in another. Making use of the region-wise prediction approach, we showed that first, a moderate extent of generalizability could be achieved with fluid cognition prediction, and that, second, a set of common brain regions related to fluid cognition across cohorts could be identified. Nevertheless, the moderate replicability and generalizability could only be achieved in specific contexts. Thus, we argue that replicability and generalizability in connectivity-based prediction remain limited and deserve greater attention in future studies.

REMoDNaV: robust eye-movement classification for dynamic stimulation.

Tracking of eye movements is an established measurement for many types of experimental paradigms. More complex and more prolonged visual stimuli have made algorithmic approaches to eye-movement event classification the most pragmatic option. A recent analysis revealed that many current algorithms are lackluster when it comes to data from viewing dynamic stimuli such as video sequences. Here we present an event classification algorithm-built on an existing velocity-based approach-that is suitable for both static and dynamic stimulation, and is capable of classifying saccades, post-saccadic oscillations, fixations, and smooth pursuit events. We validated classification performance and robustness on three public datasets: 1) manually annotated, trial-based gaze trajectories for viewing static images, moving dots, and short video sequences, 2) lab-quality gaze recordings for a feature-length movie, and 3) gaze recordings acquired under suboptimal lighting conditions inside the bore of a magnetic resonance imaging (MRI) scanner for the same full-length movie. We found that the proposed algorithm performs on par or better compared to state-of-the-art alternatives for static stimulation. Moreover, it yields eye-movement events with biologically plausible characteristics on prolonged dynamic recordings. Lastly, algorithm performance is robust on data acquired under suboptimal conditions that exhibit a temporally varying noise level. These results indicate that the proposed algorithm is a robust tool with improved classification accuracy across a range of use cases. The algorithm is cross-platform compatible, implemented using the Python programming language, and readily available as free and open-source software from public sources.

Nature abhors a paywall: How open science can realize the potential of naturalistic stimuli.

Naturalistic stimuli show significant potential to inform behavioral, cognitive, and clinical neuroscience. To date, this impact is still limited by the relative inaccessibility of both generated neuroimaging data as well as the supporting naturalistic stimuli. In this perspective, we highlight currently available naturalistic datasets and technical solutions such as DataLad that continue to advance our ability to share this data. We also review scientific and sociological challenges in selecting naturalistic stimuli for reproducible research. Overall, we encourage researchers to share their naturalistic datasets to the full extent possible under local copyright law.

Encoding of Auditory Temporal Gestalt in the Human Brain.

The perception of an acoustic rhythm is invariant to the absolute temporal intervals constituting a sound sequence. It is unknown where in the brain temporal Gestalt, the percept emerging from the relative temporal proximity between acoustic events, is encoded. Two different relative temporal patterns, each induced by three experimental conditions with different absolute temporal patterns as sensory basis, were presented to participants. A linear support vector machine classifier was trained to differentiate activation patterns in functional magnetic resonance imaging data to the two different percepts. Across the sensory constituents the classifier decoded which percept was perceived. A searchlight analysis localized activation patterns specific to the temporal Gestalt bilaterally to the temporoparietal junction, including the planum temporale and supramarginal gyrus, and unilaterally to the right inferior frontal gyrus (pars opercularis). We show that auditory areas not only process absolute temporal intervals, but also integrate them into percepts of Gestalt and that encoding of these percepts persists in high-level associative areas. The findings complement existing knowledge regarding the processing of absolute temporal patterns to the processing of relative temporal patterns relevant to the sequential binding of perceptual elements into Gestalt.

COVID-19 and market expectations: Evidence from option-implied densities.

We compare risk-neutral densities from equity index options across several countries during the early phase of the COVID-19 pandemic. The initial reaction in all analyzed markets was late, abrupt and simultaneous. Only a few weeks later, densities started to differ across markets.

Neural signatures underlying deliberation in human foraging decisions.

Humans have a remarkable capacity to mentally project themselves far ahead in time. This ability, which entails the mental simulation of events, is thought to be fundamental to deliberative decision making, as it allows us to search through and evaluate possible choices. Many decisions that humans make are foraging decisions, in which one must decide whether an available offer is worth taking, when compared to unknown future possibilities (i.e., the background). Using a translational decision-making paradigm designed to reveal decision preferences in rats, we found that humans engaged in deliberation when making foraging decisions. A key feature of this task is that preferences (and thus, value) are revealed as a function of serial choices. Like rats, humans also took longer to respond when faced with difficult decisions near their preference boundary, which was associated with prefrontal and hippocampal activation, exemplifying cross-species parallels in deliberation. Furthermore, we found that voxels within the visual cortices encoded neural representations of the available possibilities specifically following regret-inducing experiences, in which the subject had previously rejected a good offer only to encounter a low-valued offer on the subsequent trial.

Hierarchy and scaling behavior of multi-rank domain patterns in ferroelectric K0.9Na0.1NbO3 strained films.

The formation process of a ferroelectric multi-rank domain pattern in the thickness range of 7-52 nm is investigated for monoclinic K0.9Na0.1NbO3 strained epitaxial films on (110) NdScO3 substrates. Although the elastic strain energy density is degenerated for two pseudocubic orientations, a distinctive hierarchy of domain evolution is observed with exclusive in-plane a1a2 domains for very thin films and the retarded onset of a ferroelectric MC phase at larger film thickness. This is accompanied by a thickness dependent transformation from stripe domains to a herringbone pattern and, eventually, for the thickest film, to a checkerboard-like structure. These transformations in the domain arrangement and width are correlated to energetic aspects as depolarization field and anisotropic strain relaxation in the film. While for the MC domains plastic strain relaxation is throughout observed, the a1a2 domains show a two-step strain relaxation mechanism starting with an in-plane elastic shearing, which is followed by plastic lattice relaxation. Our results highlight a pathway for engineering and patterning of periodic ferroelectric domain structures.

Growth mode evolution during (100)-oriented ß-Ga2O3 homoepitaxy.

This work focuses on homoepitaxial growth of ß-Ga2O3 on (100)-oriented substrates during molecular beam epitaxy. It provides a comprehensive study on the growth mode by combining in situ with ex situ tools. In situ reflection high-energy electron diffraction (RHEED) indicates 2D layer-by-layer mode accompanied by (1 × 1) surface reconstruction. The homoepitaxial layers are grown pseudomorphic with the substrate without in-plane strain as probed by in-plane azimuthal RHEED and out-of-plane synchrotron-based high resolution x-ray diffraction. In contrast to the substrate, stacking faults and twin domains are present in the layer.

Ferroelectric monoclinic phases in strained K0.70Na0.30NbO3 thin films promoting selective surface acoustic wave propagation.

We present a detailed analysis of the ferroelectric domain structure of K0.70Na0.30NbO3 thin films on (110) TbScO3 grown by metal-organic chemical vapor deposition. Upon piezoresponse force microscopy and nanofocus x-ray diffraction measurements we derive a domain model revealing monoclinic MC domains. The complex domain pattern is formed out of four co-existing in-plane orientations of the shearing direction of the monoclinic unit cell resulting in four types of superdomains each being composed of well-ordered stripe domains. Finally, we present surface acoustic wave (SAW) experiments that exhibit extraordinary signal intensities given the low thickness of the tested film. Moreover, the SAW propagation is found to occur selectively along the identified shearing directions.

Strain Driven Shape Evolution of Stacked (In,Ga)N Quantum Disks Embedded in GaN Nanowires.

The fabrication of nanowires with axial multiquantum wells or disks presenting a homogeneous size and shape distribution along the whole stack is still an unresolved challenge, despite being essential for narrowing their light emission bandwidth. In this work we demonstrate that the commonly observed change in the shape of the disks along the stacking direction proceeds in a systematic, predictable way. High- resolution transmission electron microscopy of stacked (In,Ga)N quantum discs embedded in GaN nanowires with diameters of ∼40 nm and lengths of ∼700 nm and finite element method calculations show that, contrary to what is normally assumed, this change is not related to the radial growth of the nanowires, which is shown to be negligible, but to the strain relaxation of the whole active region. A simple model is proposed to account for the experimental observations. The model assumes that each disk reaches an equilibrium shape that minimizes the overall energy of the system, given by the sum of the surface and strain energies of the disk itself and the barrier below. The strain state of the barrier is affected by the presence of the disk buried directly below in a way that depends on its shape. This gives rise to a cumulative process, which makes the aspect ratio of each quantum disk to be smaller compared to the disk grown just before, in qualitative agreement with the experimental observations. The obtained results imply that strain relaxation is an important factor to bear in mind for the design of multiquantum disks with controlled shape along the stacking direction in any lattice mismatched nanowire system.

Distractor-resistant Short-Term Memory Is Supported by Transient Changes in Neural Stimulus Representations.

Goal-directed behavior in a complex world requires the maintenance of goal-relevant information despite multiple sources of distraction. However, the brain mechanisms underlying distractor-resistant working or short-term memory (STM) are not fully understood. Although early single-unit recordings in monkeys and fMRI studies in humans pointed to an involvement of lateral prefrontal cortices, more recent studies highlighted the importance of posterior cortices for the active maintenance of visual information also in the presence of distraction. Here, we used a delayed match-to-sample task and multivariate searchlight analyses of fMRI data to investigate STM maintenance across three extended delay phases. Participants maintained two samples (either faces or houses) across an unfilled pre-distractor delay, a distractor-filled delay, and an unfilled post-distractor delay. STM contents (faces vs. houses) could be decoded above-chance in all three delay phases from occipital, temporal, and posterior parietal areas. Classifiers trained to distinguish face versus house maintenance successfully generalized from pre- to post-distractor delays and vice versa, but not to the distractor delay period. Furthermore, classifier performance in all delay phases was correlated with behavioral performance in house, but not face, trials. Our results demonstrate the involvement of distributed posterior, but not lateral prefrontal, cortices in active maintenance during and after distraction. They also show that the neural code underlying STM maintenance is transiently changed in the presence of distractors and reinstated after distraction. The correlation with behavior suggests that active STM maintenance is particularly relevant in house trials, whereas face trials might rely more strongly on contributions from long-term memory.

The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7T.

A decade after it was shown that the orientation of visual grating stimuli can be decoded from human visual cortex activity by means of multivariate pattern classification of BOLD fMRI data, numerous studies have investigated which aspects of neuronal activity are reflected in BOLD response patterns and are accessible for decoding. However, it remains inconclusive what the effect of acquisition resolution on BOLD fMRI decoding analyses is. The present study is the first to provide empirical ultra high-field fMRI data recorded at four spatial resolutions (0.8mm, 1.4mm, 2mm, and 3mm isotropic voxel size) on this topic - in order to test hypotheses on the strength and spatial scale of orientation discriminating signals. We present detailed analysis, in line with predictions from previous simulation studies, about how the performance of orientation decoding varies with different acquisition resolutions. Moreover, we also examine different spatial filtering procedures and its effects on orientation decoding. Here we show that higher-resolution scans with subsequent down-sampling or low-pass filtering yield no benefit over scans natively recorded in the corresponding lower resolution regarding decoding accuracy. The orientation-related signal in the BOLD fMRI data is spatially broadband in nature, includes both high spatial frequency components, as well as large-scale biases previously proposed in the literature. Moreover, we found above chance-level contribution from large draining veins to orientation decoding. Acquired raw data were publicly released to facilitate further investigation.

Multirate method for co-simulation of electrical-chemical systems in multiscale modeling.

Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration. When time constants of model components are different by several orders of magnitude, individual dynamics and mathematical definitions of each component all together impose stability, accuracy and efficiency challenges for the time integrator. Following our numerical investigations in Brocke et al. (Frontiers in Computational Neuroscience, 10, 97, 2016), we present a new multirate algorithm that allows us to handle each component of a large system with a step size appropriate to its time scale. We take care of error estimates in a recursive manner allowing individual components to follow their discretization time course while keeping numerical error within acceptable bounds. The method is developed with an ultimate goal of minimizing the communication between the components. Thus it is especially suitable for co-simulations. Our preliminary results support our confidence that the multirate approach can be used in the class of problems we are interested in. We show that the dynamics ofa communication signal as well as an appropriate choice of the discretization order between system components may have a significant impact on the accuracy of the coupled simulation. Although, the ideas presented in the paper have only been tested on a single model, it is likely that they can be applied to other problems without loss of generality. We believe that this work may significantly contribute to the establishment of a firm theoretical basis and to the development of an efficient computational framework for multiscale modeling and simulations.

Strain engineering of monoclinic domains in K x Na1-x NbO3 epitaxial layers: a pathway to enhanced piezoelectric properties.

A novel concept to obtain a ferroelectric material with enhanced piezoelectric properties is proposed. This approach is based on the combination of two pathways: (i) the evolution of a ferroelectric monoclinic phase and, (ii) the coexistence of different types of ferroelectric domains leading to polarization discontinuities at the domain walls. Each of these pathways enables polarization rotation in the material which is responsible for giant piezoelectricity. Targeted incorporation of anisotropic epitaxial lattice strain is used to implement this approach. The feasibility of our concept is demonstrated for K0.9Na0.1NbO3 epitaxial layers grown on NdScO3 substrates where the coexistence of (100)pc and (001)pc pseudocubic oriented monoclinic domains is experimentally verified. This coexistence results in a complex periodic domain pattern with alternating emergence of ferroelectric in-plane a 1 a 2 and inclined M C monoclinic phases, which differ in the direction of the electrical polarization vector. Our approach opens the possibility to exploit ferroelectric properties in both vertical and lateral directions and to achieve enhanced piezoelectric properties in lead-free material caused by singularities at the domains walls.

Influence of strain relaxation in axial [Formula: see text] nanowire heterostructures on their electronic properties.

We present a systematic theoretical study of the influence of elastic strain relaxation on the built-in electrostatic potentials and the electronic properties of axial [Formula: see text] nanowire (NW) heterostructures. Our simulations reveal that for a sufficiently large ratio between the thickness of the [Formula: see text] disk and the diameter of the NW, the elastic relaxation leads to a significant reduction of the built-in electrostatic potential in comparison to a planar system of similar layer thickness and In content. In this case, the ground state transition energies approach constant values with increasing thickness of the disk and only depend on the In content, a behavior usually associated to that of a quantum well free of built-in electrostatic potentials. We show that the structures under consideration are by no means field-free, and the built-in potentials continue to play an important role even for ultrathin NWs. In particular, strain and the resulting polarization potentials induce complex confinement features of electrons and holes, which depend on the In content, shape, and dimensions of the heterostructure.

A Model of Representational Spaces in Human Cortex.

Current models of the functional architecture of human cortex emphasize areas that capture coarse-scale features of cortical topography but provide no account for population responses that encode information in fine-scale patterns of activity. Here, we present a linear model of shared representational spaces in human cortex that captures fine-scale distinctions among population responses with response-tuning basis functions that are common across brains and models cortical patterns of neural responses with individual-specific topographic basis functions. We derive a common model space for the whole cortex using a new algorithm, searchlight hyperalignment, and complex, dynamic stimuli that provide a broad sampling of visual, auditory, and social percepts. The model aligns representations across brains in occipital, temporal, parietal, and prefrontal cortices, as shown by between-subject multivariate pattern classification and intersubject correlation of representational geometry, indicating that structural principles for shared neural representations apply across widely divergent domains of information. The model provides a rigorous account for individual variability of well-known coarse-scale topographies, such as retinotopy and category selectivity, and goes further to account for fine-scale patterns that are multiplexed with coarse-scale topographies and carry finer distinctions.

Nanofocus x-ray diffraction and cathodoluminescence investigations into individual core-shell (In,Ga)N/GaN rod light-emitting diodes.

Employing nanofocus x-ray diffraction, we investigate the local strain field induced by a five-fold (In,Ga)N multi-quantum well embedded into a GaN micro-rod in core-shell geometry. Due to an x-ray beam width of only 150 nm in diameter, we are able to distinguish between individual m-facets and to detect a significant in-plane strain gradient along the rod height. This gradient translates to a red-shift in the emitted wavelength revealed by spatially resolved cathodoluminescence measurements. We interpret the result in terms of numerically derived in-plane strain using the finite element method and subsequent kinematic scattering simulations which show that the driving parameter for this effect is an increasing indium content towards the rod tip.

Detecting lateral composition modulation in dilute Ga(As,Bi) epilayers.

The ability to characterize a structure into the finest details in a quantitative manner is a key issue to understanding and controlling nanoscale phase separation in novel nanomaterials. In this work, we consider the detectability of lateral composition modulation (LCM), a type of nanoscale phase separation in GaAs(1-x)Bix epilayers, by x-ray diffraction (XRD). We show that the satellite peaks due to LCM are hardly detectable in reasonable time with a lab x-ray diffractometer for GaAs(1-x)Bix samples with an average x up to 25% and relative modulation up to 50%. This is in contrast to LCM reported in other III-V combinations, where the intensity of the satellite peak is relatively high and can be easily detected. Our theoretical considerations are complemented experimentally using highly brilliant synchrotron radiation. The results are in good agreement with the predictions. This work provides a guideline for the systematic characterization of LCM in zincblende III-V semiconductor epilayers and points to the critical role of quantitative characterization of nanoscale phase separation.