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As a new biometric, the Electroencephalogram (EEG) signal has the advantages of invisibility, non-clonability, and non-coercion compare to traditional biometrics. However, the real-time and stability are the difficulties that the current EEG-based person authentication systems face. In this paper, we design a real-time and stable person authentication system using EEG signals, which are elicited by...
This paper presents a model-based Field Programmable Gates Array (FPGA) design for real-time feature extraction of Electroencephalogram (EEG) signals, which can be used for brainwaves bands classification to track and detect mental status in Brain Computer Interface (BCI) applications and consciousness studies. An model-based design approach is used to implement Short-time Fourier Transform (STFT)...
The fundamental role of the cerebellum in motor learning explains the deficits of cerebellar patients in adaptation to a changing environment. For example, lesions to the cerebellar cortex compromise performance during tasks like reaching a target under a force field perturbation. However, the exact relationship between neural damages and misbehaviors still needs to be clarified. To this aim, it could...
Deep brain stimulation (DBS) is an established therapy for a variety of neurological disorders, including Parkinson's disease, essential tremor, and dystonia. Recent DBS research has pursued methods for closed-loop control to provide more effective management of symptoms, side effects, and device power consumption. Most closed-loop DBS (CLDBS) studies to date use simple threshold-based controllers...
Localizing sounds in our environment is a fundamental perceptual ability. However, methods to assess sound localization ability are often cumbersome, requiring large speaker array systems. In adults with sensorineural hearing loss who are fitted with cochlear implant (CIs), sound localization is known to improve when bilateral CIs are used compared to a single CI. This study proposes a portable virtual...
Retinal prosthetic implants have shown potential to restore partial vision to patients blinded by retinitis pigmentosa or dry age-related macular degeneration, via a camera-driven multielectrode array that electrically stimulates surviving retinal neurons. Commercial epi-retinal prostheses mostly use charge-balanced symmetric cathodic-first biphasic pulses to depolarize retinal ganglion cells (RGCs)...
Multi-target stimulus coding plays an important role in a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). In conventional SSVEP-based BCIs, a large interval between two neighboring stimulus frequencies is often used to improve classification accuracy. Although recent progresses in stimulus coding and target identification methods that have significantly improved...
We present novel hierarchical multiscale Bayesian algorithms for electromagnetic brain imaging using magnetoencephalography (MEG) and electroencephalography (EEG). We define sensor data measurements using a generative probabilistic graphical model that is hierarchical across spatial scales of brain regions and voxels. We then derive Bayesian algorithms for probabilistic inference with this graphical...
A significant and recognized problem in implantable neural recording and stimulation probes is operational lifetime. It is well known that both electrophysiological recording and, to a lesser extent, stimulation probes suffer severe performance degradation over periods ranging from months to a few years. Performance degradation of implantable probes arises due to a number of factors, including systemic...
The NTera2/D1 (NT2) cell line (hNT) is an alternative cell line source for human neurons. In this paper, we demonstrate for the first time how it is possible to record high quality spontaneous spikes from human hNT neurons on gold electrodes in an SU-8 trench. This is comparable to the only other previous hNT neurons recording performed on titanium nitride (TiN) electrodes with commercial systems.
Optical techniques such as two-photon (2p) calcium imaging have the potential to transform the way we interrogate neural circuits, both in the realm of basic neuroscience and in the development of brain-machine interfaces (BMIs). This may be possible by overcoming some of the limitations of electrophysiological methods. Here we ask if optical imaging signals, in particular 2p GCaMP6 calcium imaging...
In this paper, we propose a reconfigurable neural spike classifier based on neuromorphic event-based networks that can be directly interfaced to neural signal conditioning and quantization circuits. The classifier is set as a heterogeneity based, multi-layer computational network to offer wide flexibility in the implementation of plastic and metaplastic interactions, and to increase efficacy in neural...
The Helping Hand (HH) system is a novel grasp rehabilitation platform aimed at simplifying the clinical usage of wearable electrode arrays for neuromuscular electrical stimulation (NMES). In a randomized dose-matched, clinical study we evaluate usability and effectiveness of the HH treatment, and of other enriched upper limb rehabilitation treatments, and compare the outcomes. This paper shows the...
Identification of intended movement type and movement phase of hand grasp shaping are critical features for the control of volitional neuroprosthetics. We demonstrate that neural dynamics during visually-guided imagined grasp shaping can encode intended movement. We apply Procrustes analysis and LASSO regression to achieve 72% accuracy (chance = 25%) in distinguishing between visually-guided imagined...
Investigating intracerebral tissue at single cell level has become increasingly important in animal studies and meanwhile found its way into clinical applications. The stability of single unit activity (SUA) to be recorded can be however quite elusive, which -among others- might be caused by the mechanical mismatch of stiff neural implants and soft brain tissue. Unfortunately, the variety of factors...
Transcutaneous Electrical Nerve Stimulation (TENS) attracts extensive attention in neuromodulation due to its minimal invasiveness. Conventional TENS uses non-invasive surface planar electrodes attached to the skin for delivering the stimulation current to modulate neural circuitries. Previous studies have shown that using these surface planar electrodes in TENS therapy may cause stimulation-induced...
In this paper, the interaction between axons in nerve trunks has been characterized in the statistical sense while the mechanism model is investigated based on two different observation scales. In order to describe the interaction phenomena, a symmetric coupling factor matrix has been presented which is considered as a transverse mode combining the standard cable equation. It has been shown that the...
In rodent's olfactory bulb, different odors evoke distinct glomeruli patterns to form a specific ‘Odor Map’. The optical imaging has the ability to visualize the functional responses in precise spatial and temporal resolution, which provides an opportunity to decipher the functional architecture of the patterns in the olfactory bulb. Here we adapted intrinsic signal imaging to visualize the odor response...
Functional intrinsic brain networks (IBNs) has been widely studied due to its close relationship to different brain functions and diseases. In these studies, linear metrics, e.g., correlation, have been commonly used in identifying brain networks, especially on functional magnetic resonance imaging (fMRI) data. However, nonlinear mechanism is believed to exist in forming brain networks. In the present...
A common problem in Brain-Machine Interface (BMI) is the variations in neural signals over time, leading to significant decrease in decoding performance if the decoder is not re-trained. However, frequent re-training is not practical in real use case. In our work, we found that a temporally more robust system may be achieved through the use of wavelet transform in feature extraction. We used wavelet...
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