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This paper presents a novel biomimetic CMOS two-input non-linear adder circuit to fully emulate computations within dendritic branches of pyramidal neurons. It automatically and dynamically adjusts neuron responses based on the input magnitudes of EPSP potentials. The design is based on CMOS 180nm technology with dual power supplies.
Multi-contact cuff electrodes were implanted in the median, ulnar, and radial nerves of an upper-limb amputee. 19 of 20 contacts produced selective, sensory response in the phantom limb from nerve stimulation. The neural interface has been stable for the duration of this ongoing chronic study, 12 months post-implant, with consistent threshold and impedance measures.
Long-term reliability of an implanted system is an implicit requirement. The catastrophic failure of an implanted device is often the only indication that reliability expectations have not been met. In the design of a wireless EMG sensor, we have integrated three “Reliability Modules” specifically designed to monitor the state of the silicon integrated circuit and its environment.
Strong permanent adhesion between thin-film polyimide (BPDA-PPD) and silicone rubber (MED-1000) was achieved through deposition of a chemically-transitive intermediate adhesion promoting layer. Plasma-enhanced chemical vapor deposition (PECVD) of SiC and SiO2 was used to grow a thin 50 nm layer directly on a 5 μm thin polyimide substrate. The deposition at low pressures permitted the fabrication of...
Working memory (WM) is necessary for higher cognitive functions. To understand the mechanism of WM from the view of network connectivity becomes a hot topic in the field of neuroscience. The purpose of this work is to develop a sparse causal analysis (SCA) based on non-negative matrix factorization (NMF), and to investigate dynamic connections among the multi-channel spikes during WM. 16-channels...
The use of intramuscular EMG for proportional control of prostheses requires an effective means of estimating the magnitude of neural drive to the muscles of interests. This implies the quantification of the motor unit (MU) discharge rate by which the central nervous system encodes information. Algorithms for full decomposition of signals exist, but they are time-consuming and work only at low to...
Early detection of autism spectrum disorder (ASD) in infants is vital in maximizing the impact and potential long-term outcomes of early delivery of rehabilitative therapies. To date no definitive diagnostic test for ASD exists. Electroencephalography is a noninvasive method used to capture underlying electrical changes in brain activity. This proof-of-concept study suggests that recurrence quantification...
The mechanisms behind memory have been studied mainly in artificial neural networks. Several mechanisms have been proposed, but it remains unclear yet if and how these findings can be translated to biological networks. Here we unravel part of the mechanism by showing that cultured neuronal networks develop an activity connectivity balance. External inputs disturb this balance and induce connectivity...
Neural mass models (NMM) provide insights into the neuromodulatory mechanisms underlying alterations of cortical activity as recorded by electroencephalography (EEG). In the human primary motor cortex (M1), neuromodulation can be induced by non-invasive brain stimulation (NIBS). We aimed to capture the origin of NIBS-induced alterations in the EEG power spectrum using a thalamocortical NMM. We found...
In this study, we propose unsupervised learning of the lateral inhibition structure through inhibitory spike-timing dependent plasticity (iSTDP) in a computational model for multivariate data processing inspired by the honeybee antennal lobe. After exposing the network to a sufficient number of input samples, the inhibitory connectivity self-organizes to reflect the correlation between input channels...
A computational model for research on retinal implants is presented. In this model, the electric field produced by a multi-electrode array in a uniform retina is calculated. It is shown how this model can be used to answer questions as to cross talk of activated electrodes, bunching of field lines in monopole and dipole activation, sequential stimulation, multipolar stimulation, etc. The model is...
This paper presents an algorithm to analyze chirp-like signals that occur during seizures. It is based on a reassignment time-frequency representation and image processing technique. Firstly, the reassignment smoothed pseudo Wigner-Ville distribution (RSPWVD) was calculated, and then the Hough transform was executed on the RSPWVD in the time-frequency plane. The algorithm was applied to traditional...
This paper presents a novel approach to estimate internal variables such as gating variables, potassium, sodium and chloride concentrations from the knowledge of voltage of a neuron. This approach is based on the Hodgkin-Huxley neuron dynamics and basic ideas behind a Luenberger observer, and utilizes the full nonlinear dynamics. Results from numerical simulations are presented.
Current BMI technology requires significant development to enable patients with severe motor disabilities to obtain vital degrees of freedom in everyday life. State-of-the-art systems are expensive, require long training times and suffer from low patient uptake. We propose a non-invasive and ultra-low cost alternative — action intention decoding from 3D gaze signals. Building on our previous work,...
A validation of a closed-loop system-on-chip (SoC) for epilepsy treatment is presented. A 12mm2 0.13μm CMOS SoC provides the functionality of neural recording, neural stimulation and early seizure detection based on the bivariate phase synchrony estimation algorithm. The SoC can operate in a closed loop, has 64 neural recording and 64 neural stimulation channels, and dissipates 1.4mW and 1.5mW across...
Many professions place significant mental and/or physical strain on their workers. Some professionals such as firefighters, soldiers, and pilots have an inherent responsibility for the safety of others. Making sure that workers in these professions remain fit for duty is an important health/safety concern for the workers and those they serve. This paper explores the viability of using a Brain-Computer...
Steady state visual evoked potentials (SSVEP) are widely used in EEG research as they offer a relatively high signal to noise ratio allowing the investigation of visual processing at the cortical level. Presentation of a repetitive visual stimulus (flicker, RVS) at a frequency in the range from approximately 1 to 100 Hz, elicits an oscillatory response at the same frequency of the stimulus and/or...
Studies of neuroplasticity indicate that areas of the brain not injured by stroke are able to reorganize neural pathways when actively engaged. We have combined two advanced technologies, a robotic hand therapy device and a control system driven by tongue movements, to determine the effects of the wearable Tongue Drive System paired with the Hand Mentor therapeutic robot (TDS-HM) on improving upper...
In this paper, we focus on identifying the alertness state of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. A supervised classification approach is adopted, where subjects were advised to indicate their alertness states in specified time instances. Two sets of features are considered here to represent the recorded data. The first is based on the wavelet transform...
Many current brain-machine interfaces do not consider the behavioral context of the subject, rather, they assume the subject is constantly engaged in a single task. We investigated how incorporating information about state can improve the performance of a decoder. Unit spiking activity and LFPs were recorded from chronically implanted electrode arrays in primary motor and premotor corticies while...
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