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Simultaneous deep brain stimulation (DBS) and functional magnetic resonance imaging (fMRI) constitutes a powerful tool for elucidating brain functional connectivity, and exploring neuromodulatory mechanisms of DBS therapies. Previous DBS-fMRI studies could not provide full activation pattern maps due to poor MRI compatibility of the DBS electrodes, which caused obstruction of large brain areas on MRI scans. Here, we fabricate graphene fiber (GF) electrodes with high charge-injection-capacity and little-to-no MRI artifact at 9.4T. DBS-fMRI with GF electrodes at the subthalamic nucleus (STN) in Parkinsonian rats reveal robust blood-oxygenation-level-dependent responses along the basal ganglia-thalamocortical network in a frequency-dependent manner, with responses from some regions not previously detectable. This full map indicates that STN-DBS modulates both motor and non-motor pathways, possibly through orthodromic and antidromic signal propagation. With the capability for full, unbiased activation pattern mapping, DBS-fMRI using GF electrodes can provide important insights into DBS therapeutic mechanisms in various neurological disorders. Combination of fMRI and deep brain stimulation (DBS) allows for large-scale mapping of brain responses to DBS. Here the authors develop highly MRI compatible graphene fiber electrodes for full brain activation pattern mapping under DBS in Parkinsonian rats.

Object detection in high-speed and dynamic environments remains a core challenge in computer vision. Conventional frame-based cameras often suffer from motion blur and high latency, while event cameras capture brightness changes asynchronously with microsecond resolution, high dynamic range, and ultra-low latency, offering a promising alternative. Despite these advantages, existing event-based detection methods still suffer from high computational cost, limited temporal modeling, and unsatisfactory real-time performance. We present PMRVT (Parallel Attention Multilayer Perceptron Recurrent Vision Transformer), a unified framework that systematically balances early-stage efficiency, enriched spatial expressiveness, and long-horizon temporal consistency. This balance is achieved through a hybrid hierarchical backbone, a Parallel Attention Feature Fusion (PAFF) mechanism with coordinated dual-path design, and a temporal integration strategy, jointly ensuring strong accuracy and real-time performance. Extensive experiments on Gen1 and 1 Mpx datasets show that PMRVT achieves 48.7% and 48.6% mAP with inference latencies of 7.72 ms and 19.94 ms, respectively. Compared with state-of-the-art methods, PMRVT improves accuracy by 1.5 percentage points (pp) and reduces latency by 8%, striking a favorable balance between accuracy and speed and offering a reliable solution for real-time event-based vision applications.

The available treatments for depression have substantial limitations, including low response rates and substantial lag time before a response is achieved. We applied deep brain stimulation (DBS) to the lateral habenula (LHb) of two rat models of depression (Wistar Kyoto rats and lipopolysaccharide-treated rats) and observed an immediate (within seconds to minutes) alleviation of depressive-like symptoms with a high-response rate. Simultaneous functional MRI (fMRI) conducted on the same sets of depressive rats used in behavioral tests revealed DBS-induced activation of multiple regions in afferent and efferent circuitry of the LHb. The activation levels of brain regions connected to the medial LHb (M-LHb) were correlated with the extent of behavioral improvements. Rats with more medial stimulation sites in the LHb exhibited greater antidepressant effects than those with more lateral stimulation sites. These results indicated that the antidromic activation of the limbic system and orthodromic activation of the monoaminergic systems connected to the M-LHb played a critical role in the rapid antidepressant effects of LHb-DBS. This study indicates that M-LHb-DBS might act as a valuable, rapid-acting antidepressant therapeutic strategy for treatment-resistant depression and demonstrates the potential of using fMRI activation of specific brain regions as biomarkers to predict and evaluate antidepressant efficacy.

This review describes work presented in the 2014 inaugural Tsinghua University Press-Springer Nano Research Award lecture, as well as current and future opportunities for nanoscience research at the interface with brain science. First, we briefly summarize some of the considerations and the research journey that has led to our focus on bottom-up nanoscale science and technology. Second, we recapitulate the motivation for and our seminal contributions to nanowire- based nanoscience and technology, including the rational design and synthesis of increasingly complex nanowire structures, and the corresponding broad range of ＂applications＂ enabled by the capability to control structure, com- position and size from the atomic level upwards. Third, we describe in more detail nanowire-based electronic devices as revolutionary tools for brain science, including （i） motivation for nanoelectronics in brain science, （ii） demonstration of nanowire nanoelectronic arrays for high-spatial/high-temporal resolution extracellular recording, （iii） the development of fundamentally-new intracellular nanoelectronic devices that approach the sizes of single ion channels, （iv） the introduction and demonstration of a new paradigm for innervating cell networks with addressable nanoelectronic arrays in three-dimensions. Last, we conclude with a brief discussion of the exciting and potentially transformative advances expected to come from work at the nanoelectronics-brain interface.

Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces. The invasiveness of extensive craniotomy hinders large-scale cortex mapping. Here, the authors developed a flexible, shape-changing electrode array which enables minimally invasive implantation and achieves high spatiotemporal resolution brain mapping.

Nanoelectronic devices offer substantial potential for interrogating biological systems, although nearly all work has focused on planar device designs. We have overcome this limitation through synthetic integration of a nanoscale field-effect transistor (nanoFET) device at the tip of an acute-angle kinked silicon nanowire, where nanoscale connections are made by the arms of the kinked nanostructure, and remote multilayer interconnects allow three-dimensional (3D) probe presentation. The acute-angle probe geometry was designed and synthesized by controlling eis versus trans crystal conformations between adjacent kinks, and the nanoFET was localized through modulation doping. 3D nanoFET probes exhibited conductance and sensitivity in aqueous solution, independent of large mechanical deflections, and demonstrated high pH sensitivity. Additionally, 3D nanoprobes modified with phospholipid bilayers can enter single cells to allow robust recording of intracellular potentials.

Visual electrophysiology measurements are important for ophthalmic diagnostic testing. Electrodes with combined optical transparency and softness are highly desirable, and sometimes indispensable for many ocular electrophysiology measurements. Here we report the fabrication of soft graphene contact lens electrodes (GRACEs) with broad-spectrum optical transparency, and their application in conformal, full-cornea recording of electroretinography (ERG) from cynomolgus monkeys. The GRACEs give higher signal amplitude than conventional ERG electrodes in recordings of various full-field ERG responses. High-quality topographic mapping of multifocal ERG under simultaneous fundus monitoring is realized. A conformal and tight interface between the GRACEs and cornea is revealed. Neither corneal irritation nor abnormal behavior of the animals is observed after ERG measurements with GRACEs. Furthermore, spatially resolved ERG recordings on rabbits with graphene multi-electrode array reveal a stronger signal at the central cornea than the periphery. These results demonstrate the unique capabilities of the graphene-based electrodes for in vivo visual electrophysiology studies. The electrical response of the eye to optical stimulus is important in disease diagnosis but current electrodes used have limitations. Here, the authors report on the development of soft transparent graphene-based contact lens electrodes for electroretinogram recording and test the device in vivo.

The ability to make electrical measurements inside cells has led to many important advances in electrophysiology 1 , 2 , 3 , 4 , 5 , 6 . The patch clamp technique, in which a glass micropipette filled with electrolyte is inserted into a cell, offers both high signal-to-noise ratio and temporal resolution 1 , 2 . Ideally, the micropipette should be as small as possible to increase the spatial resolution and reduce the invasiveness of the measurement, but the overall performance of the technique depends on the impedance of the interface between the micropipette and the cell interior 1 , 2 , which limits how small the micropipette can be. Techniques that involve inserting metal or carbon microelectrodes into cells are subject to similar constraints 4 , 7 , 8 , 9 . Field-effect transistors (FETs) can also record electric potentials inside cells 10 , and because their performance does not depend on impedance 11 , 12 , they can be made much smaller than micropipettes and microelectrodes. Moreover, FET arrays are better suited for multiplexed measurements. Previously, we have demonstrated FET-based intracellular recording with kinked nanowire structures 10 , but the kink configuration and device design places limits on the probe size and the potential for multiplexing. Here, we report a new approach in which a SiO 2 nanotube is synthetically integrated on top of a nanoscale FET. This nanotube penetrates the cell membrane, bringing the cell cytosol into contact with the FET, which is then able to record the intracellular transmembrane potential. Simulations show that the bandwidth of this branched intracellular nanotube FET (BIT-FET) is high enough for it to record fast action potentials even when the nanotube diameter is decreased to 3 nm, a length scale well below that accessible with other methods 1 , 2 , 4 . Studies of cardiomyocyte cells demonstrate that when phospholipid-modified BIT-FETs are brought close to cells, the nanotubes can spontaneously penetrate the cell membrane to allow the full-amplitude intracellular action potential to be recorded, thus showing that a stable and tight seal forms between the nanotube and cell membrane. We also show that multiple BIT-FETs can record multiplexed intracellular signals from both single cells and networks of cells. A silicon nanowire field-effect transistor coupled to the interior of a cell by means of a hollow silicon dioxide nanotube can detect changes in the electric potential of the intracellular fluid.

Librarians need feedback from users to improve library services. On the other hand, users need assistance from librarians in order to gain a better understanding of library services. This paper focuses on how Chinese students use U.S. academic libraries’ virtual reference services (VRS), and how academic librarians use VRS. By collecting data from Chinese students and librarians, this paper hopes to create a better understanding of these two factors in order to improve VRS.

Electrical impedance tomography (EIT) has been applied in the field of human-computer interaction due to its advantages including the fact that it is non-invasive and has both low power consumption and a low cost. Previous work has focused on static gesture recognition based on EIT. Compared with static gestures, dynamic gestures are more informative and can achieve more functions in human-machine collaboration. In order to verify the feasibility of dynamic gesture recognition based on EIT, a traditional excitation drive pattern is optimized in this paper. The drive pattern of the fixed excitation electrode is tested for the first time to simplify the measurement process of the dynamic gesture. To improve the recognition accuracy of the dynamic gestures, a dual-channel feature extraction network combining a convolutional neural network (CNN) and gated recurrent unit (GRU), namely CG-SVM, is proposed. The new center distance loss is designed in order to simultaneously supervise the intra-class distance and inter-class distance. As a result, the discriminability of the confusing data is improved. With the new excitation drive pattern and classification network, the recognition accuracy of different interference data has increased by 2.7~14.2%. The new method has stronger robustness, and realizes the dynamic gesture recognition based on EIT for the first time.