Objective. Loss of balance control can have serious consequences on interaction between humans and machines as well as the general well-being of humans. Perceived balance perturbations are always accompanied by a specific cortical activation, the so-called perturbation-evoked potential (PEP). In this study, we investigate the possibility to classify PEPs from ongoing EEG. Approach. Fifteen healthy

Objective . Functional magnetic resonance imaging (fMRI) is commonly used to measure brain activity through the blood oxygen level dependent (BOLD) signal mechanism, but this only provides an indirect proxy signal to neuronal activity. Magnetoencephalography (MEG) provides a more direct measurement of the magnetic fields created by neuronal currents in the brain, but requires very specialized hardware

Objective. Translational studies on animals play a vital role in the advancement of transcranial magnetic stimulation (TMS) as clinical technique. Nonetheless the relevance of these procedures is frequently limited by the lack of TMS systems specifically designed for small animals capable of producing comparable stimulation conditions to those found in human TMS. In this work, we propose to take advantage

Objective. Estimating the ongoing phase of oscillations in electroencephalography (EEG) recordings is an important aspect of understanding brain function, as well as for the development of phase-dependent closed-loop real-time systems that deliver stimuli. Such stimuli may take the form of direct brain stimulation (for example transcranial magnetic stimulation), or sensory stimuli (for example presentation

Objective. Avoidance of the adverse electrochemical reactions at the electrode-electrolyte interface defines the voltage safety window and limits the charge injection capacity (CIC) of an electrode material. For an electrode that is not ideally capacitive, the CIC depends on the waveform of the stimulus. We study the modeling of the charge injection dynamics to optimize the waveforms for efficient

Objective. Recent development of sensory stimulation techniques demonstrates the ability to elicit touch-like phantom sensations in upper limb amputees. The cortical processing of this phantom sensation and the corresponding influences on sensorimotor functional connectivity have not been studied. We hypothesize that sensory stimulation has a profound impact on the sensorimotor cortical functional

Objective. Brain-computer interfaces (BCIs) using electrocorticographic (ECoG) signals have been developed to restore the communication function of severely paralyzed patients. However, the limited amount of information derived from ECoG signals hinders their clinical applications. We aimed to develop a method to decode ECoG signals using spatiotemporal patterns characterizing movement types to increase

Objective. Transcutaneous cervical spinal cord stimulation (tsCSC) has been demonstrated to activate the dorsal root and activate targeted muscles. However, it is unclear whether tsCSC can elicit functionally relevant movements of the upper limb for assistive/rehabilitative purposes. Approach. The current study sought to elicit arm and hand movements by tsCSC by placing an electrode array near the

Objective. Neuromodulation technologies are increasingly used for improving function after neural injury. To achieve a symbiotic relationship between device and user, the device must augment remaining function, and independently adapt to day-to-day changes in function. The goal of this study was to develop predictive control strategies to produce over-ground walking in a model of hemisection spinal

Objective. Repair and regeneration of peripheral nerve defect by engineered conduits have greatly advanced in the past decades while still facing great challenges. Approach. In this work, we fabricated a new highly oriented poly(L-lactic acid) (PLLA)/soy protein isolate (SPI) nanofibrous conduit (HO-PSNC) for nerve regeneration. Main results. Firstly, we observed that SPI could efficiently modify PLLA

Objective . Transcranial magnetic stimulation (TMS) activates brain structures non-invasively. Computational models can be used to elucidate the activation site; however, the exact activation site is controversial. The aim is to present an imaging technique of the TMS activation cortical site estimation using individualized multi-scale realistic head models based on experimentally-derived TMS fields

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Objective. The purpose of this study is to judge whether this combination method of multispectral image and convolutional neural network (CNN) method can be used to distinguish amnestic mild cognitive impairment (aMCI) with Type 2 diabetes mellitus (T2DM) and normal controls (NC) with T2DM effectively. Approach. In this study, the authors first combined EEG signals from aMCI patients with T2DM and

Objective. Growing evidence have linked disorders of consciousness (DOC) with the changes in frequency-specific functional networks. However, the alteration of inter-frequency dynamics in brain networks remain largely unknown. In this study, we investigated the network integration and segregation across frequency bands in a multiplex network framework. Approach. Resting-state EEG data were recorded

BACKGROUND Conscious perception is thought to involve the large-scale, coordinated activation of distant brain regions, a process termed ignition in the Global Workspace Theory and integration in Integrated Information Theory, which are two of the major theories of consciousness. METHODS Here, we provide evidence for this process in humans by combining a magnetically-induced phosphene perception task

OBJECTIVE The auditory brainstem response can be recorded non-invasively from scalp electrodes and serves as an important clinical measure of hearing function. We have recently shown how the brainstem response at the fundamental frequency of continuous, non-repetitive speech can be measured, and have used this measure to demonstrate that the response is modulated by selective attention. However, different

Objective. Daily life tasks can become a significant challenge for motor impaired persons. Depending on the severity of their impairment, they require more complex solutions to retain an independent life. Brain-computer interfaces (BCIs) are targeted to provide an intuitive form of control for advanced assistive devices such as robotic arms or neuroprostheses. In our current study we aim to decode

OBJECTIVE Statistical methods that simultaneously model temporal and spatial variations of fMRI data are promising tools for dynamic functional connectivity (FC) estimation. Although different approaches are available, they need to manually set the parameters, or may disregard some important fMRI features such as the autocorrelation. In addition, no reliable method exists for the validation of dynamic

Objective Recording electrical activity from individual cells in vivo is a key technology for basic neuroscience and has growing clinical applications. To maximize the number of independent recording channels as well as the longevity, and quality of these recordings, researchers often turn to small and flexible electrodes that minimize tissue damage and can isolate signals from individual neurons.

Automatic sleep stage scoring is of great importance for investigating sleep architecture during infancy. In this work, we introduce a novel multichannel approach based on deep learning networks and hidden Markov models (HMM) to improve the accuracy of sleep stage classification in term neonates. The classification performance was evaluated on quiet sleep (QS) and active sleep (AS) stages, each with

OBJECTIVE To infer information flow in the white matter of the brain and recover cortical activity using functional MRI, diffusion MRI, and MEG without a manual selection of the white matter connections of interest. APPROACH A Bayesian network which encodes the priors knowledge of possible brain states is built from imaging data. Diffusion MRI is used to enumerate all possible connections between cortical

The hand - a complex effector comprising dozens of degrees of freedom of movement - endows us with the ability to flexibly, precisely, and effortlessly interact with objects. The neural signals associated with dexterous hand movements in primary motor cortex (M1) and somatosensory cortex (SC) have received comparatively less attention than have those associated with proximal upper limb control. To

OBJECTIVE Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in Brain Computer Interfaces (BCI). ERPs are characterized and typically decoded through a fixed set of components with particular amplitude and latency. However, the classical methods which rely on waveform features achieve a high decoding performance only with standardized and well aligned

OBJECTIVE Neural interfacing technologies could significantly improve quality of life for people living with the loss of a limb. Both motor commands and sensory feedback must be considered; these complementary systems are segregated from one another in the spinal nerve. APPROACH The dorsal root ganglion-ventral root (DRG-VR) complex was targeted chronically with floating microelectrode arrays (FMAs)

Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated using different modalities such as diffusion MRI to capture structural organization of the brain or functional MRI to elaborate brain's functional organization. Understanding links between structural and functional organizations

OBJECTIVE This paper describes the design, testing and use of a novel multichannel block-capable stimulator for acute neurophysiology experiments to study highly selective neural interfacing techniques. This paper demonstrates the stimulator's ability to excite and inhibit nerve activity in the rat sciatic nerve model concurrently using monophasic and biphasic nerve stimulation as well as high-frequency

OBJECTIVE Twisted wire probes (TWPs, e.g. stereotrodes and tetrodes) provide a cheap and reliable method for obtaining high quality, multiple single-unit neural recordings in freely moving animals. Despite their ubiquity, TWPs are constructed using a tedious procedure consisting of manually folding, turning, and fusing microwire. This imposes a significant labor burden on research personnel who use

Tetrode arrays are a standard method for neuronal recordings in behaving animals, especially for chronic recordings of many neurons in freely-moving animals. OBJECTIVE We sought to simplify tetrode drive designs with the aim of enabling building and implanting a 16-tetrode drive in a single day. APPROACH Our design makes use of recently developed technologies to reduce the complexity of the drive while

OBJECTIVE Degradations of transmitted speech have been shown to affect perceptual and cognitive processing in human listeners, as indicated by the P3 component of the event-related brain potential (ERP). However, research suggests that previously observed P3 modulations might actually be traced back to earlier neural modulations in the time range of the P1-N1-P2 complex of the cortical auditory evoked

OBJECTIVES Multiple facets of human emotion underlie diverse and sparse neural mechanisms. Among the many existing models of emotion, the two-dimensional circumplex model of emotion is an important theory. The use of the circumplex model allows us to model variable aspects of emotion; however, such momentary expressions of one's internal mental state still lacks a notion of the third dimension of time

OBJECT For the shared control systems, how to trade off the control weight between robot autonomy and human operator is an important issue, especially for BCI-based systems. However, most of existing shared controllers have paid less attention to the effects caused by subjects with different levels of brain control ability. APPROACH In this paper, a brain state evaluation network, termed BSE-NET, is

Objective Characterize the role of the beta-band (13-30 Hz) in the human hippocampus during the execution of voluntary movement. Approach We recorded electrophysiological activity in human hippocampus during a reach task using stereotactic electroencephalography (SEEG). SEEG has previously been utilized to study the theta band (3-8 Hz) in conflict processing and spatial navigation, but most studies

OBJECTIVE To evaluate the electrochemical properties, biological response, and surface characterization of an electrodeposited Platinum-Iridium (Pt-Ir) electrode coating on cochlear implants subjected to chronic stimulation in vivo. APPROACH Electrochemical impedance spectroscopy (EIS), charge storage capacity (CSC), charge injection limit (CIL), and voltage transient (VT) impedance were measured bench-top

The steady-state visual evoked potential (SSVEP)-based brain computer interface (BCI) has demonstrated relatively high performance with little user training, and thus becomes a popular BCI paradigm. However, due to the performance deterioration over time, its robustness and reliability appear not sufficient to allow a non-expert to use outside laboratory. It would be thus helpful to study what happens

OBJECTIVE Interferential stimulation (IFS) has generated considerable interest recently because of its potential to achieve focal electric fields in deep brain areas with transcranial currents. Conventionally, IFS applies sinusoidal currents through two electrode pairs with close-by frequencies. Here we propose to use an array of electrodes instead of just two electrode pairs; and to use algorithmic

OBJECTIVE A deep convolutional neural network (CNN) is a method for deep learning (DL). It has a powerful ability to automatically extract features and is widely used in classification tasks with scalp electroencephalogram (EEG) signals. However, the small number of samples and low signal-to-noise ratio involved in scalp EEG with low spatial resolution constitute a limitation that might restrict potential

OBJECTIVE Brain Computer Interface (BCI) inefficiency indicates that there would be 10% to 50% of users are unable to operate Motor-Imagery-based BCI systems. Importantly, the almost all previous studieds on BCI inefficiency were based on tests of Sensory Motor Rhythm (SMR) feature. In this work, we assessed the occurrence of BCI inefficiency with SMR and Movement-Related Cortical Potential (MRCP)

In this report we present the fEEGrid, an electrode array applied to the forehead that allows convenient long-term recordings of EEG signals over many hours. Twenty young, healthy participants wore the fEEGrid and completed traditional EEG paradigms in two sessions on the same day. The sessions were eight hours apart, participants performed the same tasks in an early and a late session. For the late

OBJECTIVE Vagus nerve stimulation (VNS) is a nonpharmacologic therapeutic option for patients who have pharmaco-resistant Dravet syndrome (DS). Plentiful efforts have been made for delivering VNS to DS patients, but its effectiveness still requires further verification. We investigated the effectiveness of the VNS treatment of DS patients using brain connectivity analysis with electroencephalography

OBJECTIVE Filter bank canonical correlation analysis (FBCCA) is a widely-used classification approach implemented in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). However, conventional detection algorithms for SSVEP recognition problems, including the FBCCA, were usually based on 'fixed window' strategy. That's to say, these algorithms always analyze data with

A passive brain-computer interface recognizes its operator's cognitive state without an explicitly performed control task. This technique is commonly used in conjunction with consumer-grade EEG devices for detecting the conditions of fatigue, attention, emotional arousal, or motion sickness.While it is easy to mount the sensors in the forehead area, which is not covered with hair, the recorded signals

The performance of brain-computer interface (BCI) systems is influenced by the user's mental state, such as attention diversion. In this study, we propose a novel online BCI system able to adapt with variations in the users' attention during real-time movement execution. Electroencephalography (EEG) signals were recorded from healthy participants and patients with Amyotrophic Lateral Sclerosis (ALS)

Brain-computer interface (BCI) has demonstrated its effectiveness in epilepsy treatment and control. In a BCI-aided epilepsy treatment system, therapic electrical stimulus is delivered in response to the prediction of upcoming seizure onsets, therefore timely and accurate seizure prediction algorithm plays an important role. However, unlike typical signatures such as slow or sharp waves in ictal periods

OBJECTIVE Retinal prostheses aim to restore vision in patients with retinal degenerative diseases, such as age-related macular degeneration and retinitis pigmentosa. By implanting an array of microelectrodes, such a device creates percepts in patients through electrical stimulation of surviving retinal neurons. A challenge for retinal prostheses when trying to return high quality vision is the unintended

Motor imagery-based brain-computer interfaces (BCIs) use an individual's ability to volitionally modulate localized brain activity as a therapy or to probe relations between brain activity and behavior. However, many individuals cannot learn to successfully modulate their brain activity, greatly limiting the efficacy of BCIs. Experiments designed to probe the nature of BCI learning suggest that activity

OBJECTIVE Spinal cord stimulation (SCS) is a common neurostimulation therapy to treat chronic pain. Computational models represent a valuable tool to study the potential mechanisms of action of SCS and to optimize the design and implementation of SCS technologies. However, it is imperative that these computational models include the appropriate level of detail to accurately predict the neural response

OBJECTIVE Intracortical electrical neural recording using solid-state electrodes is a prevalent approach in addressing neurophysiological queries and implementing brain-computer interfacing systems. As a variety of ultradensity microelectrode arrays (ultradensity-MEAs) are being created more recently, this paper answers to the rising demand for a more rigorous theory concerning this new type of neural

OBJECTIVE Electrical neuromodulation is a clinically effective therapeutic instrument, currently expanding into newer indications and larger patient populations. Neuromodulation technologies are also moving towards less invasive approaches to nerve stimulation. In this study, we investigated an enhanced transcutaneous electrical nerve stimulation (eTENS) system that electrically couples a conductive

OBJECTIVE In this study, we proposed a state-based probabilistic method for decoding hand positions during unilateral and bilateral movements using the ECoG signals recorded from the brain of Rhesus monkey. APPROACH A customized electrode array was implanted subdurally in the right hemisphere of the brain covering from the primary motor cortex to the frontal cortex. Three different experimental paradigms

OBJECTIVE Retinal implants have the potential to restore some sight in patients with retinal degeneration. The PRIMA implant's novel design features simpler insertion and no transscleral cabling or extraocular components. This in vitro study investigated PRIMA's durability under real time and accelerated conditions and estimated the device's lifespan in vivo. APPROACH Two potential failure modes were

OBJECTIVE Methods based on Riemannian geometry have proven themselves to be good models for decoding in brain-computer interfacing (BCI). However, these methods suffer from the curse of dimensionality and are not possible to deploy in high-density online BCI systems. In addition, the lack of interpretability of Riemannian methods leaves open the possibility that artifacts drive classification performance

Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these lesions are variable, the initial investigations are usually similar. Patients who are suspected to have a brain tumor will be assessed with computed tomography (CT) and magnetic resonance imaging (MRI). The imaging findings

OBJECTIVE We have recently developed a prototype of a novel human-computer interface for assistive communication based on voluntary shifts of attention (gaze) from a far target to a near target associated with a decrease of pupil size (Pupillary Accommodative Response, PAR), an automatic vegetative response that can be easily recorded. We report here an extension of that approach based on pupillary

OBJECTIVE Evoking haptic sensation on upper limb amputees via peripheral nerve stimulation has been investigated intensively in the past decade, but related studies involving lower limb amputees are limited. This study aimed to evaluate the feasibility of using non-invasive transcutaneous electrical nerve stimulation to evoke haptic sensation along the phantom limb of the amputated foot of transtibial

OBJECTIVE Previous studies have reported that working memory (WM) may be affected by emotions and that the effect may exist in different stages of WM. However, at present it remains controversial whether emotions inhibit or facilitate WM, and how the mechanism of dynamic information transmission in the brain during WM is affected by emotions. APPROACH In this study, we used a video database to induce

OBJECTIVE Neuroprosthetics hold tremendous promise to restore function through brain-computer interfaced devices. However, clinical applications of implantable microelectrodes remain limited given the challenges of maintaining neuronal signals for extended periods of time and with multiple biological mechanisms negatively affecting electrode performance. Acute and chronic inflammation, oxidative stress

OBJECTIVE The analysis of interactions among local populations of neurons in the cerebral cortex (e.g. within cortical microcolumns) requires high resolution and high channel count recordings from chronically implanted laminar microelectrode arrays. The request for high-density recordings of a large number of recording sites can presently only be accomplished by probes realized using complementary

OBJECTIVE Carbon fiber electrodes may enable better long-term brain implants, minimizing the tissue response commonly seen with silicon-based electrodes. The small diameter fiber may enable high-channel count brain-machine interfaces capable of reproducing dexterous movements. Past carbon fiber electrodes exhibited both high fidelity single unit recordings and a healthy neuronal population immediately

OBJECTIVE Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI's analog

OBJECTIVE Fractional calculus plays a key role in the analysis of neural dynamics. In particular, fractional calculus has been recently exploited for analyzing complex biological systems and capturing intrinsic phenomena. Also, artificial neural networks have been shown to have complex neuronal dynamics and characteristics that can be modeled by fractional calculus. Moreover, for a neural microcircuit