Detection of common EEG phenomena using individual electrodes placed outside the hair.

Many studies over the past decades have provided exciting evidence that electrical signals recorded from the scalp (electroencephalogram, EEG) hold meaningful information about the brain's function or dysfunction. This information is used routinely in research laboratories to test specific hypotheses and in clinical settings to aid in diagnoses (such as during polysomnography evaluations). Unfortunately, with very few exceptions, such meaningful information about brain function has not yet led to valuable solutions that can address the needs of many people outside such research laboratories or clinics. One of the major hurdles to practical application of EEG-based neurotechnologies is the current predominant requirement to use electrodes that are placed in the hair, which greatly reduces practicality and cosmesis. While several studies reported results using one specific combination of signal/reference electrode outside the hair in one specific context (such as a brain-computer interface experiment), it has been unclear what information about brain function can be acquired using different signal/referencing locations placed outside the hair. To address this issue, in this study, we set out to determine to what extent EEG phenomena related to auditory, visual, cognitive, motor, and sleep function can be detected from different combinations of individual signal/referencing electrodes that are placed outside the hair. The results of our study from 15 subjects suggest that only a few EEG electrodes placed in locations on the forehead or around the ear can provide substantial task-related information in 6 of 7 tasks. Thus, the results of our study provide encouraging evidence and guidance that should invigorate and facilitate the translation of laboratory experiments into practical, useful, and valuable EEG-based neurotechnology solutions.

Slow-wave modulation analysis during states of unconsciousness using the novel tau-modulation method.

Objective. Slow-wave modulation occurs during states of unconsciousness and is a large-scale indicator of underlying brain states. Conventional methods typically characterize these large-scale dynamics by assuming that slow-wave activity is sinusoidal with a stationary frequency. However, slow-wave activity typically has an irregular waveform shape with a non-stationary frequency, causing these methods to be highly unpredictable and inaccurate. To address these limitations, we developed a novel method using tau-modulation, which is more robust than conventional methods in estimating the modulation of slow-wave activity and does not require assumptions on the shape or stationarity of the underlying waveform.Approach. We propose a novel method to estimate modulatory effects on slow-wave activity. Tau-modulation curves are constructed from cross-correlation between slow-wave and high-frequency activity. The resultant curves capture several aspects of modulation, including attenuation or enhancement of slow-wave activity, the temporal synchrony between slow-wave and high-frequency activity, and the rate at which the overall brain activity oscillates between states.Main results. The method's performance was tested on an open electrocorticographic dataset from two monkeys that were recorded during propofol-induced anesthesia, with electrodes implanted over the left hemispheres. We found a robust propagation of slow-wave modulation along the anterior-posterior axis of the lateral aspect of the cortex. This propagation preferentially originated from the anterior superior temporal cortex and anterior cingulate gyrus. We also found the modulation frequency and polarity to track the stages of anesthesia. The algorithm performed well, even with non-sinusoidal activity and in the presence of real-world noise.Significance. The novel method provides new insight into several aspects of slow-wave modulation that have been previously difficult to evaluate across several brain states. This ability to better characterize slow-wave modulation, without spurious correlations induced by non-sinusoidal signals, may lead to robust and physiologically-plausible diagnostic tools for monitoring brain functions during states of unconsciousness.

Spatio-temporal evolution of human neural activity during visually cued hand movements.

Making hand movements in response to visual cues is common in daily life. It has been well known that this process activates multiple areas in the brain, but how these neural activations progress across space and time remains largely unknown. Taking advantage of intracranial electroencephalographic (iEEG) recordings using depth and subdural electrodes from 36 human subjects using the same task, we applied single-trial and cross-trial analyses to high-frequency iEEG activity. The results show that the neural activation was widely distributed across the human brain both within and on the surface of the brain, and focused specifically on certain areas in the parietal, frontal, and occipital lobes, where parietal lobes present significant left lateralization on the activation. We also demonstrate temporal differences across these brain regions. Finally, we evaluated the degree to which the timing of activity within these regions was related to sensory or motor function. The findings of this study promote the understanding of task-related neural processing of the human brain, and may provide important insights for translational applications.

Strain-Induced Performance Enhancement of a Monolayer Photodetector via Patterned Substrate Engineering.

Two-dimensional (2D) materials exhibit tremendous potential for applications in next-generation photodetectors. Currently, approaches aiming at enhancing the device's performance are limited, mainly relying on complex hybrid systems such as heterostructures and sensitization. Here, we propose a new strategy by constructing patterned nanostructures compatible with the conventional silicon substrate. Using CVD-grown monolayer MoS2 on the periodical nanocone arrays, we demonstrate a high-performance MoS2 photodetector via manipulating strain distribution engineered by the substrate at the nanoscale. Compared to the pristine MoS2 counterpart, the strained MoS2 photodetector exhibits a much enhanced performance, including a high signal-to-noise ratio over 105 and large responsivity of 3.2 × 104 A W-1. The physical mechanism responsible for the enhancement is discussed by combining Kelvin probe force microscopy with theoretical simulation. The enhanced performances can be attributed to the improved light absorption, the fast separation of photo-excited carriers, and the suppression of dark currents induced by the designed periodical nanocone arrays. This work depicts an alternative method to achieve high-performance optoelectronic devices based on 2D materials integrated with semiconductor circuits.

Neural excitatory rebound induced by valproic acid may predict its inadequate control of seizures.

BACKGROUND: Valproic acid (VPA) represents one of the most efficient antiseizure medications (ASMs) for both general and focal seizures, but some patients may have inadequate control by VPA monotherapy. In this study, we aimed to verify the hypothesis that excitatory dynamic rebound induced by inhibitory power may contribute to the ineffectiveness of VPA therapy and become a predictor of post-operative inadequate control of seizures. METHODS: Awake craniotomy surgeries were performed in 16 patients with intro-operative high-density electrocorticogram (ECoG) recording. The relationship between seizure control and the excitatory rebound was further determined by diagnostic test and univariate analysis. Thereafter, kanic acid (KA)-induced epileptic mouse model was used to confirm that its behavior and neural activity would be controlled by VPA. Finally, a computational simulation model was established to verify the hypothesis. FINDINGS: Inadequate control of seizures by VPA monotherapy and post-operative status epilepticus are closely related to a significant excitatory rebound after VPA injection (rebound electrodes≧5/64, p = 0.008), together with increased synchronization of the local field potential (LFP). In addition, the neural activity in the model mice showed a significant rebound on spike firing (53/77 units, 68.83%). The LFP increased the power spectral density in multiple wavebands after VPA injection in animal experiments (p < 0.001). Computational simulation experiments revealed that inhibitory power-induced excitatory rebound is an intrinsic feature in the neural network. INTERPRETATION: Despite the limitations, we provide evidence that inadequate control of seizures by VPA monotherapy could be associated with neural excitatory rebounds, which were predicted by intraoperative ECoG analysis. Combined with the evidence from computational models and animal experiments, our findings suggested that ineffective ASMs may be because of the excitatory rebound, which is mediated by increased inhibitory power. FUNDING: This work was supported by National Natural Science Foundation of China (62127810, 81970418), Shanghai Municipal Science and Technology Major Project (2018SHZDZX03) and ZJLab; Science and Technology Commission of Shanghai Municipality (18JC1410403, 19411969000, 19ZR1477700, 20Z11900100); MOE Frontiers Center for Brain Science; Shanghai Key Laboratory of Health Identification and Assessment (21DZ2271000); Shanghai Shenkang (SHDC2020CR3073B).

Automated intraoperative central sulcus localization and somatotopic mapping using median nerve stimulation.

Objective. Accurate identification of functional cortical regions is essential in neurological resection. The central sulcus (CS) is an important landmark that delineates functional cortical regions. Median nerve stimulation (MNS) is a standard procedure to identify the position of the CS intraoperatively. In this paper, we introduce an automated procedure that uses MNS to rapidly localize the CS and create functional somatotopic maps.Approach. We recorded electrocorticographic signals from 13 patients who underwent MNS in the course of an awake craniotomy. We analyzed these signals to develop an automated procedure that determines the location of the CS and that also produces functional somatotopic maps.Main results. The comparison between our automated method and visual inspection performed by the neurosurgeon shows that our procedure has a high sensitivity (89%) in identifying the CS. Further, we found substantial concordance between the functional somatotopic maps generated by our method and passive functional mapping (92% sensitivity).Significance. Our automated MNS-based method can rapidly localize the CS and create functional somatotopic maps without imposing additional burden on the clinical procedure. With additional development and validation, our method may lead to a diagnostic tool that guides neurosurgeons and reduces postoperative morbidity in patients undergoing resective brain surgery.

Controllable Heterogenous Seeding-Induced Crystallization for High-Efficiency FAPbI3 -Based Perovskite Solar Cells Over 24.

The addition of small seeding particles into a supersaturated solution is one among the most effective approaches to obtain high-quality semiconductor materials via increased crystallization rates. However, limited study is conducted on this approach for the fabrication of perovskite solar cells. Here, a new strategy-"heterogenous seeding-induced crystallization (hetero-SiC)" to assist the growth of FAPbI3 -based perovskite is proposed. In this work, di-tert-butyl(methyl)phosphonium tetrafluoroborate is directly introduced into the precursor, which forms a low-solubility complex with PbI2 . The low-solubility complex can serve as the seed to induce crystallization of the perovskite during the solvent-evaporation process. Various in situ measurement tools are used to visualize the hetero-SiC process, which is shown to be an effective way of manipulating the nucleation and crystal growth of perovskites. The hetero-SiC process greatly improves the film quality, reduces film defects, and suppresses nonradiative recombination. A hetero-SIC proof-of-concept device exhibits outstanding performance with 24.0% power conversion efficiency (PCE), well over the control device with 22.2% PCE. Additionally, hetero-SiC perovskite solar cell (PSC) stability under light illumination is enhanced and the PSC retains 84% of its initial performance after 1400 h of light illumination.

Spontaneous State Detection Using Time-Frequency and Time-Domain Features Extracted From Stereo-Electroencephalography Traces.

As a minimally invasive recording technique, stereo-electroencephalography (SEEG) measures intracranial signals directly by inserting depth electrodes shafts into the human brain, and thus can capture neural activities in both cortical layers and subcortical structures. Despite gradually increasing SEEG-based brain-computer interface (BCI) studies, the features utilized were usually confined to the amplitude of the event-related potential (ERP) or band power, and the decoding capabilities of other time-frequency and time-domain features have not been demonstrated for SEEG recordings yet. In this study, we aimed to verify the validity of time-domain and time-frequency features of SEEG, where classification performances served as evaluating indicators. To do this, using SEEG signals under intermittent auditory stimuli, we extracted features including the average amplitude, root mean square, slope of linear regression, and line-length from the ERP trace and three traces of band power activities (high-gamma, beta, and alpha). These features were used to detect the active state (including activations to two types of names) against the idle state. Results suggested that valid time-domain and time-frequency features distributed across multiple regions, including the temporal lobe, parietal lobe, and deeper structures such as the insula. Among all feature types, the average amplitude, root mean square, and line-length extracted from high-gamma (60-140 Hz) power and the line-length extracted from ERP were the most informative. Using a hidden Markov model (HMM), we could precisely detect the onset and the end of the active state with a sensitivity of 95.7 ± 1.3% and a precision of 91.7 ± 1.6%. The valid features derived from high-gamma power and ERP in this work provided new insights into the feature selection procedure for further SEEG-based BCI applications.

Decoding continuous kinetic information of grasp from stereo-electroencephalographic (SEEG) recordings.

Objective.Brain-computer interfaces (BCIs) have the potential to bypass damaged neural pathways and restore functionality lost due to injury or disease. Approaches to decoding kinematic information are well documented; however, the decoding of kinetic information has received less attention. Additionally, the possibility of using stereo-electroencephalography (SEEG) for kinetic decoding during hand grasping tasks is still largely unknown. Thus, the objective of this paper is to demonstrate kinetic parameter decoding using SEEG in patients performing a grasping task with two different force levels under two different ascending rates.Approach.Temporal-spectral representations were studied to investigate frequency modulation under different force tasks. Then, force amplitude was decoded from SEEG recordings using multiple decoders, including a linear model, a partial least squares model, an unscented Kalman filter, and three deep learning models (shallow convolutional neural network, deep convolutional neural network and the proposed CNN+RNN neural network).Main results.The current study showed that: (a) for some channel, both low-frequency modulation (event-related desynchronization (ERD)) and high-frequency modulation (event-related synchronization) were sustained during prolonged force holding periods; (b) continuously changing grasp force can be decoded from the SEEG signals; (c) the novel CNN+RNN deep learning model achieved the best decoding performance, with the predicted force magnitude closely aligned to the ground truth under different force amplitudes and changing rates.Significance.This work verified the possibility of decoding continuously changing grasp force using SEEG recordings. The result presented in this study demonstrated the potential of SEEG recordings for future BCI application.

Manipulating Crystallization Kinetics in High-Performance Blade-Coated Perovskite Solar Cells via Cosolvent-Assisted Phase Transition.

Manipulating the perovskite solidification process, including nucleation and crystal growth, plays a critical role in controlling film morphology and thus affects the resultant device performance. In this work, a facile and effective ethyl alcohol (EtOH) cosolvent strategy is demonstrated with the incorporation of EtOH into perovskite ink for high-performance room-temperature blade-coated perovskite solar cells (PSCs) and modules. Systematic real-time perovskite crystallization studies uncover the delicate perovskite structural evolutions and phase-transition pathway. Time-resolved X-ray diffraction and density functional theory calculations both demonstrate that EtOH in the mixed-solvent system significantly promotes the formation of an FA-based precursor solvate (FA2 PbBr4 ·DMSO) during the trace-solvent-assisted transition process, which finely regulates the balance between nucleation and crystal growth to guarantee high-quality perovskite films. This strategy efficiently suppresses nonradiative recombination and improves efficiencies in both 1.54 (23.19%) and 1.60 eV (22.51%) perovskite systems, which represents one of the highest records for blade-coated PSCs in both small-area devices and minimodules. An excellent VOC deficit as low as 335 mV in the 1.54 eV perovskite system, coincident with the measured nonradiative recombination loss of only 77 mV, is achieved. More importantly, significantly enhanced device stability is another signature of this approach.

Assessing differential representation of hand movements in multiple domains using stereo-electroencephalographic recordings.

Invasive brain-computer interfaces (BCI) have made great progress in the reconstruction of fine hand movement parameters for paralyzed patients, where superficial measurement modalities including electrocorticography (ECoG) and micro-array recordings are mostly used. However, these recording techniques typically focus on the signals from the sensorimotor cortex, leaving subcortical regions and other cortical regions related to the movements largely unexplored. As an intracranial recording technique for the presurgical assessments of brain surgery, stereo-encephalography (SEEG) inserts depth electrodes containing multiple contacts into the brain and thus provides the unique opportunity for investigating movement-related neural representation throughout the brain. Although SEEG samples neural signals with high spatial-temporal resolutions, its potential of being used to build BCIs has just been realized recently, and the decoding of SEEG activity related to hand movements has not been comprehensively investigated yet. Here, we systematically evaluated the factors influencing the performance of movement decoding using SEEG signals recorded from 32 human subjects performing a visually-cued hand movement task. Our results suggest that multiple regions in both lateral and depth directions present significant neural selectivity to the task, whereas the sensorimotor area, including both precentral and postcentral cortex, carries the richest discriminative neural information for the decoding. The posterior parietal and prefrontal cortex contribute gradually less, but still rich sources for extracting movement parameters. The insula, temporal and occipital cortex also contains useful task-related information for decoding. Under the cortex layer, white matter presents decodable neural patterns but yields a lower accuracy (42.0 ± 0.8%) than the cortex on average (44.2 ± 0.8%, p<0.01). Notably, collectively using neural signals from multiple task-related areas can significantly enhance the movement decoding performance by 6.9% (p<0.01) on average compared to using a single region. Among the different spectral components of SEEG activity, the high gamma and delta bands offer the most informative features for hand movements reconstruction. Additionally, the phase-amplitude coupling strength between these two frequency ranges correlates positively with the performance of movement decoding. In the temporal domain, maximum decoding accuracy is first reached around 2 s after the onset of movement commands. In sum, this study provides valuable insights for the future motor BCIs design employing both SEEG recordings and other recording modalities.

Changes in lifestyle, mood, and disease management among community-dwelling older adults during the COVID-19 pandemic in China.

Background: Lives of older adults have been greatly affected by the COVID-19 pandemic. Methods: A telephone survey was conducted among the older adults aged 60 and above who lived in downtown Shanghai. We compared the lifestyle, mood, and disease management of older adults before and during the COVID-19 pandemic. Results: One hundred and fifty-six older adults in Shanghai completed the survey. The proportions of older adults with adequate consumption of meat (49.4% vs. 53.1%, P = 0.0339) and eggs (73.7% vs. 77.6%, P = 0.0143) were significantly higher than before. Participants spent significantly more time on housework (median: 2.0, IQR:1.0-3.0 vs. median: 2.0, IQR:1.0-2.0 h/day; P = 0.0361) and leisure activities (median: 7.0, IQR: 5.0-8.6 vs. median: 6.0, IQR: 4.0-8.5 h/day; P<0.0001) during the pandemic than before. More participants developed new hobbies (27.6% vs. 36.5%, P = 0.0470) and learned new skills (5.1% vs. 19.9%, P<0.0001). However, the number of participants routinely self-testing blood glucose and/or blood pressure decreased from 77.6% before to 64.1% during the pandemic (P = 0.0002). Conclusions: The COVID-19 pandemic affected the lifestyle, mood, and chronic diseases management among community-dwelling older adults. Supportive measures and interventions need to be tailored to older adults living in the community.

Detection of human white matter activation and evaluation of its function in movement decoding using stereo-electroencephalography (SEEG).

Objective. White matter tissue takes up approximately 50% of the human brain volume and it is widely known as a messenger conducting information between areas of the central nervous system. However, the characteristics of white matter neural activity and whether white matter neural recordings can contribute to movement decoding are often ignored and still remain largely unknown. In this work, we make quantitative analyses to investigate these two important questions using invasive neural recordings.Approach. We recorded stereo-electroencephalography (SEEG) data from 32 human subjects during a visually-cued motor task, where SEEG recordings can tap into gray and white matter electrical activity simultaneously. Using the proximal tissue density method, we identified the location (i.e. gray or white matter) of each SEEG contact. Focusing on alpha oscillatory and high gamma activities, we compared the activation patterns between gray matter and white matter. Then, we evaluated the performance of such white matter activation in movement decoding.Main results. The results show that white matter also presents activation under the task, in a similar way with the gray matter but at a significantly lower amplitude. Additionally, this work also demonstrates that combing white matter neural activities together with that of gray matter significantly promotes the movement decoding accuracy than using gray matter signals only.Significance. Taking advantage of SEEG recordings from a large number of subjects, we reveal the response characteristics of white matter neural signals under the task and demonstrate its enhancing function in movement decoding. This study highlights the importance of taking white matter activities into consideration in further scientific research and translational applications.

Multifunctional Crosslinking-Enabled Strain-Regulating Crystallization for Stable, Efficient α-FAPbI3 -Based Perovskite Solar Cells.

α-Formamidinium lead triiodide (α-FAPbI3 ) represents the state-of-the-art for perovskite solar cells (PSCs) but experiences intrinsic thermally induced tensile strain due to a higher phase-converting temperature, which is a critical instability factor. An in situ crosslinking-enabled strain-regulating crystallization (CSRC) method with trimethylolpropane triacrylate (TMTA) is introduced to precisely regulate the top section of perovskite film where the largest lattice distortion occurs. In CSRC, crosslinking provides in situ perovskite thermal-expansion confinement and strain regulation during the annealing crystallization process, which is proven to be much more effective than the conventional strain-compensation (post-treatment) method. Moreover, CSRC with TMTA successfully achieves multifunctionality simultaneously: the regulation of tensile strain, perovskite defects passivation with an enhanced open-circuit voltage (VOC  = 50 mV), and enlarged perovskite grain size. The CSRC approach gives significantly enhanced power conversion efficiency (PCE) of 22.39% in α-FAPbI3 -based PSC versus 20.29% in the control case. More importantly, the control PSCs' instability factor-residual tensile strain-is regulated into compression strain in the CSRC perovskite film through TMTA crosslinking, resulting in not only the best PCE but also outstanding device stability in both long-term storage (over 4000 h with 95% of initial PCE) and light soaking (1248 h with 80% of initial PCE) conditions.

Effective Piezo-Phototronic Enhancement of Flexible Photodetectors Based on 2D Hybrid Perovskite Ferroelectric Single-Crystalline Thin-Films.

2D hybrid perovskites are very attractive for optoelectronic applications because of their numerous exceptional properties. The emerging 2D perovskite ferroelectrics, in which are the coupling of spontaneous polarization and piezoelectric effects, as well as photoexcitation and semiconductor behaviors, have great appeal in the field of piezo-phototronics that enable to effectively improve the performance of optoelectronic devices via modulating the electro-optical processes. However, current studies on 2D perovskite ferroelectrics focus on bulk ceramics that cannot endure irregular mechanical deformation and limit their application in flexible optoelectronics and piezo-phototronics. Herein, we synthesize ferroelectric EA4 Pb3 Br10 single-crystalline thin-films (SCFs) for integration into flexible photodetectors. The in-plane multiaxial ferroelectricity is evident within the EA4 Pb3 Br10 SCFs through systematic characterizations. Flexible photodetectors based on EA4 Pb3 Br10 SCFs are achieved with an impressive photodetection performance. More importantly, optoelectronic EA4 Pb3 Br10 SCFs incorporated with in-plane ferroelectric polarization and effective piezoelectric coefficient show great promise for the observation of piezo-phototronic effect, which is capable of greatly enhancing the photodetector performance. Under external strains, the responsivity of the flexible photodetectors can be modulated by piezo-phototronic effect with a remarkable enhancement up to 284%. Our findings shed light on the piezo-phototronic devices and offer a promising avenue to broaden functionalities of hybrid perovskite ferroelectrics.

Large-scale growth of few-layer two-dimensional black phosphorus.

Two-dimensional materials provide opportunities for developing semiconductor applications at atomistic thickness to break the limits of silicon technology. Black phosphorus (BP), as a layered semiconductor with controllable bandgap and high carrier mobility, is one of the most promising candidates for transistor devices at atomistic thickness1-4. However, the lack of large-scale growth greatly hinders its development in devices. Here, we report the growth of ultrathin BP on the centimetre scale through pulsed laser deposition. The unique plasma-activated region induced by laser ablation provides highly desirable conditions for BP cluster formation and transportation5,6, facilitating growth. Furthermore, we fabricated large-scale field-effect transistor arrays on BP films, yielding appealing hole mobility of up to 213 and 617 cm2 V-1 s-1 at 295 and 250 K, respectively. Our results pave the way for further developing BP-based wafer-scale devices with potential applications in the information industry.

Printing High-Efficiency Perovskite Solar Cells in High-Humidity Ambient Environment-An In Situ Guided Investigation.

Extensive studies are conducted on perovskite solar cells (PSCs) with significant performance advances (mainly spin coating techniques), which have encouraged recent efforts on scalable coating techniques for the manufacture of PSCs. However, devices fabricated by blade coating techniques are inferior to state-of-the-art spin-coated devices because the power conversion efficiency (PCE) is highly dependent on the morphology and crystallization kinetics in the controlled environment and the delicate solvent system engineering. In this study, based on the widely studied perovskite solution system dimethylformamide-dimethyl sulfoxide, air-knife-assisted ambient fabrication of PSCs at a high relative humidity of 55 ± 5% is reported. In-depth time-resolved UV-vis spectrometry is carried out to investigate the impact of solvent removal and crystallization rate, which are critical factors influencing the crystallization kinetics and morphology because of adventitious moisture. UV-vis spectrometry enables accurate determination of the thickness of the wet precursor film. Anti-solvent-free, high-humidity ambient coatings of hysteresis-free PSCs with PCEs of 21.1% and 18.0% are demonstrated for 0.06 and 1 cm2 devices, respectively. These PSCs exhibit comparable stability to those fabricated in a glovebox, thus demonstrating their high potential.

Effects of Gaze Fixation on the Performance of a Motor Imagery-Based Brain-Computer Interface.

Motor imagery-based brain-computer interfaces (BCIs) have been studied without controlling subjects' gaze fixation position previously. The effect of gaze fixation and covert attention on the behavioral performance of BCI is still unknown. This study designed a gaze fixation controlled experiment. Subjects were required to conduct a secondary task of gaze fixation when performing the primary task of motor imagination. Subjects' performance was analyzed according to the relationship between motor imagery target and the gaze fixation position, resulting in three BCI control conditions, i.e., congruent, incongruent, and center cross trials. A group of fourteen subjects was recruited. The average group performances of three different conditions did not show statistically significant differences in terms of BCI control accuracy, feedback duration, and trajectory length. Further analysis of gaze shift response time revealed a significantly shorter response time for congruent trials compared to incongruent trials. Meanwhile, the parietal occipital cortex also showed active neural activities for congruent and incongruent trials, and this was revealed by a contrast analysis of R-square values and lateralization index. However, the lateralization index computed from the parietal and occipital areas was not correlated with the BCI behavioral performance. Subjects' BCI behavioral performance was not affected by the position of gaze fixation and covert attention. This indicated that motor imagery-based BCI could be used freely in robotic arm control without sacrificing performance.

Efficient Flexible Perovskite Solar Cells Using Low-Cost Cu Top and Bottom Electrodes.

Perovskite solar cells (PSCs) are promising technology for flexible photovoltaic applications because of the low cost and good flexibility of the halide perovskite materials. Nevertheless, the use of transparent conductive oxides (TCOs) and noble metals (e.g., Au and Ag) as PSC electrodes is very costly, and TCOs are too brittle for flexible applications. How to fabricate flexible PSCs (FPSCs) with cost-effective and soft electrode materials remains to be a big challenge. Herein, we report the first study of FPSCs using low-cost Cu electrodes. Both the transparent bottom electrode and the opaque top electrode are fabricated with Cu. FPSCs made with such Cu electrodes acquire a champion efficiency of 13.58% (Jsc of 17.79 mA cm-2, Voc of 1.031 V, and FF of 74.07%), which retains over 90% after 1000 cycles of bending at a small radius of curvature of 5 mm. The device shows negligible changes in Voc and FF after storage for 10 weeks without encapsulation.

A General Wet Transferring Approach for Diffusion-Facilitated Space-Confined Grown Perovskite Single-Crystalline Optoelectronic Thin Films.

Hybrid perovskite single-crystalline thin films are promising for making high-performance perovskite optoelectronic devices due to their superior physical properties. However, it is still challenging to incorporate them into multilayer devices because of their on-substrate growth. Here, a wet transfer method is used in transferring perovskite single-crystalline films perfectly onto various target substrates. More importantly, large millimeter-scaled single-crystalline films can be obtained via a diffusion-facilitated space-confined growth method as thin as a few hundred nanometers, which are capable of sustaining excellent crystalline quality and morphology after the transferring process. The availability of these crystalline films offers us a convenient route to further investigate their intrinsic properties of hybrid perovskites. We also demonstrate that the wet transfer method can be used for scalable fabrication of perovskite single-crystalline film-based photodetectors exhibiting a remarkable photoresponsivity. It is expected that this transferring strategy would promise broad applications of perovskite single-crystalline films for more complex perovskite devices.