Showing papers in "Journal of Neural Engineering in 2007"

A review of classification algorithms for EEG-based brain–computer interfaces

Abstract: In this paper we review classification algorithms used to design brain–computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

Abstract: Neural interface technology has made enormous strides in recent years but stimulating electrodes remain incapable of reliably targeting specific cell types (e.g. excitatory or inhibitory neurons) within neural tissue. This obstacle has major scientific and clinical implications. For example, there is intense debate among physicians, neuroengineers and neuroscientists regarding the relevant cell types recruited during deep brain stimulation (DBS); moreover, many debilitating side effects of DBS likely result from lack of cell-type specificity. We describe here a novel optical neural interface technology that will allow neuroengineers to optically address specific cell types in vivo with millisecond temporal precision. Channelrhodopsin-2 (ChR2), an algal light-activated ion channel we developed for use in mammals, can give rise to safe, light-driven stimulation of CNS neurons on a timescale of milliseconds. Because ChR2 is genetically targetable, specific populations of neurons even sparsely embedded within intact circuitry can be stimulated with high temporal precision. Here we report the first in vivo behavioral demonstration of a functional optical neural interface (ONI) in intact animals, involving integrated fiberoptic and optogenetic technology. We developed a solid-state laser diode system that can be pulsed with millisecond precision, outputs 20 mW of power at 473 nm, and is coupled to a lightweight, flexible multimode optical fiber, ∼200 µm in diameter. To capitalize on the unique advantages of this system, we specifically targeted ChR2 to excitatory cells in vivo with the CaMKIIα promoter. Under these conditions, the intensity of light exiting the fiber (∼380 mW mm −2 ) was sufficient to drive excitatory neurons in vivo and control motor cortex function with behavioral output in intact rodents. No exogenous chemical cofactor was needed at any point, a crucial finding for in vivo work in large mammals. Achieving modulation of behavior with optical control of neuronal subtypes may give rise to fundamental network-level insights complementary to what electrode methodologies have taught us, and the emerging optogenetic toolkit may find application across a broad range of neuroscience, neuroengineering and clinical questions.

A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals.

Abstract: Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention? S This article has associated online supplementary data files

Decoding two-dimensional movement trajectories using electrocorticographic signals in humans.

Abstract: Signals from the brain could provide a non-muscular communication and control system, a brain–computer interface (BCI), for people who are severely paralyzed. A common BCI research strategy begins by decoding kinematic parameters from brain signals recorded during actual arm movement. It has been assumed that these parameters can be derived accurately only from signals recorded by intracortical microelectrodes, but the long-term stability of such electrodes is uncertain. The present study disproves this widespread assumption by showing in humans that kinematic parameters can also be decoded from signals recorded by subdural electrodes on the cortical surface (ECoG) with an accuracy comparable to that achieved in monkey studies using intracortical microelectrodes. A new ECoG feature labeled the local motor potential (LMP) provided the most information about movement. Furthermore, features displayed cosine tuning that has previously been described only for signals recorded within the brain. These results suggest that ECoG could be a more stable and less invasive alternative to intracortical electrodes for BCI systems, and could also prove useful in studies of motor function.

Brain-computer interface using a simplified functional near-infrared spectroscopy system.

Abstract: A brain-computer interface (BCI) is a device that allows a user to communicate with external devices through thought processes alone. A novel signal acquisition tool for BCIs is near-infrared spectroscopy (NIRS), an optical technique to measure localized cortical brain activity. The benefits of using this non-invasive modality are safety, portability and accessibility. A number of commercial multi-channel NIRS system are available; however we have developed a straightforward custom-built system to investigate the functionality of a fNIRS-BCI system. This work describes the construction of the device, the principles of operation and the implementation of a fNIRS-BCI application, 'Mindswitch' that harnesses motor imagery for control. Analysis is performed online and feedback of performance is presented to the user. Mindswitch presents a basic 'on/off' switching option to the user, where selection of either state takes 1 min. Initial results show that fNIRS can support simple BCI functionality and shows much potential. Although performance may be currently inferior to many EEG systems, there is much scope for development particularly with more sophisticated signal processing and classification techniques. We hope that by presenting fNIRS as an accessible and affordable option, a new avenue of exploration will open within the BCI research community and stimulate further research in fNIRS-BCIs.

Complex impedance spectroscopy for monitoring tissue responses to inserted neural implants

Abstract: A series of animal experiments was conducted to characterize changes in the complex impedance of chronically implanted electrodes in neural tissue. Consistent trends in impedance changes were observed across all animals, characterized as a general increase in the measured impedance magnitude at 1 kHz. Impedance changes reach a peak approximately 7 days post-implant. Reactive responses around individual electrodes were described using immuno- and histo-chemistry and confocal microscopy. These observations were compared to measured impedance changes. Several features of impedance changes were able to differentiate between confined and extensive histological reactions. In general, impedance magnitude at 1 kHz was significantly increased in extensive reactions, starting about 4 days post-implant. Electrodes with extensive reactions also displayed impedance spectra with a characteristic change at high frequencies. This change was manifested in the formation of a semi-circular arc in the Nyquist space, suggestive of increased cellular density in close proximity to the electrode site. These results suggest that changes in impedance spectra are directly influenced by cellular distributions around implanted electrodes over time and that impedance measurements may provide an online assessment of cellular reactions to implanted devices.

Neurite outgrowth and branching of PC12 cells on very soft substrates sharply decreases below a threshold of substrate rigidity.

Abstract: Rationally designed matrices for nerve tissue engineering and encapsulated cell therapies critically rely on a comprehensive understanding of neural response to biochemical as well as biophysical cues. Whereas biochemical cues are established mediators of neuronal behavior (e.g., outgrowth), physical cues such as substrate stiffness have only recently been recognized to influence cell behavior. In this work, we examine the response of PC12 neurites to substrate stiffness. We quantified and controlled fibronectin density on the substrates and measured multiple neurite behaviors (e.g., growth, branching, neurites per cell, per cent cells expressing neurites) in a large sample population. We found that PC12 neurons display a threshold response to substrate stiffness. On the softest substrates tested (shear modulus approximately 10 Pa), neurites were relatively few, short in length and unbranched. On stiffer substrates (shear modulus approximately 10(2)-10(4) Pa), neurites were longer and more branched and a greater percentage of cells expressed neurites; significant differences in these measures were not found on substrates with a shear modulus >10(2) Pa. Based on these data and comparisons with published neurobiology and neuroengineering reports of neurite mechanotransduction, we hypothesize that results from studies of neuronal response to compliant substrates are cell-type dependent and sensitive to ligand density, sample size and the range of stiffness investigated.

Electrochemical polymerization of conducting polymers in living neural tissue

Abstract: A number of biomedical devices require extended electrical communication with surrounding tissue. Significant improvements in device performance would be achieved if it were possible to maintain communication with target cells despite the reactive, insulating scar tissue that forms at the device–tissue interface. Here, we report that the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) can be polymerized directly within living neural tissue resulting in an electrically conductive network that is integrated within the tissue. Nano and microscale PEDOT filaments extend out from electrode sites, presumably forming within extracellular spaces. The cloud of PEDOT filaments penetrates out into the tissue far enough that it should be possible to bypass fibrous scar tissue and contact surrounding healthy neurons. These electrically functional, diffuse conducting polymer networks grown directly within tissue signify a new paradigm for creating soft, low impedance implantable electrodes. (Some figures in this article are in colour only in the electronic version)

Suppression of axonal conduction by sinusoidal stimulation in rat hippocampus in vitro

Abstract: Deep brain stimulation (DBS), also known as high frequency stimulation (HFS), is a well-established therapy for Parkinson's disease and essential tremor, and shows promise for the therapeutic control of epilepsy. However, the direct effect of DBS on neural elements close to the stimulating electrode remains an important unanswered question. Computational studies have suggested that HFS has a dual effect on neural elements inhibiting cell bodies, while exciting axons. Prior experiments have shown that sinusoidal HFS (50 Hz) can suppress synaptic and non-synaptic cellular activity in several in vitro epilepsy models, in all layers of the hippocampus. However, the effects of HFS on axons near the electrode are still unclear. In the present study, we tested the hypothesis that HFS suppresses axonal conduction in vitro. Sinusoidal HFS was applied to the alvear axon field of transverse rat hippocampal slices. The results show that HFS suppresses the alvear compound action potential (CAP) as well as the CA1 antidromic evoked potential (AEP). Complete suppression was observed as a 100% reduction in the amplitude of the evoked field potential for the duration of the stimulus. Evoked potential width and latency were not significantly affected by sinusoidal HFS. Suppression was dependent on HFS amplitude and frequency, but independent of stimulus duration and synaptic transmission. The frequency dependence of sinusoidal HFS is similar to that observed in clinical DBS, with maximal suppression between 50 and 200 Hz. HFS produced not only suppression of axonal conduction but also a correlated rise in extracellular potassium. These data provide new insights into the effects of HFS on neuronal elements, and show that HFS can block axonal activity through non-synaptic mechanisms.

Non-rectangular waveforms for neural stimulation with practical electrodes

Abstract: Historically the rectangular pulse waveform has been the choice for neural stimulation. The strength–duration curve is thus defined for rectangular pulses. Not much attention has been paid to alternative waveforms to determine if the pulse shape has an effect on the strength–duration relation. Similarly the charge injection capacity of neural electrodes has also been measured with rectangular pulses. In this study we questioned if non-rectangular waveforms can generate a stronger stimulation effect, when applied through practical electrodes, by minimizing the neural activation threshold and maximizing the charge injection capacity of the electrode. First, the activation threshold parameters were studied with seven different pulse shapes using computer simulations of a local membrane model. These waveforms were rectangular, linear increase and decrease, exponential increase and decrease, Gaussian, and sinusoidal. The chronaxie time was found to be longer with all the non-rectangular pulses and some provided more energy efficient stimulation than the rectangular waveform. Second, the charge injection capacity of titanium nitride microelectrodes was measured experimentally for the same waveforms. Linearly decreasing ramp provided the best charge injection for all pulse widths tested from 0.02 to 0.5 ms. Finally, the most efficient waveform that maximized the charge injection capacity of the electrode while providing the lowest threshold charge for neural activation was searched. Linear and exponential decrease, and Gaussian waveforms were found to be the most efficient pulse shapes.

Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: Concepts and lessons from a computational model

Abstract: Deep brain stimulation (DBS) of the subthalamic nucleus with periodic, high-frequency pulse trains is an increasingly standard therapy for advanced Parkinson's disease. Here, we propose that a closed-loop global optimization algorithm may identify novel DBS waveforms that could be more effective than their high-frequency counterparts. We use results from a computational model of the Parkinsonian basal ganglia to illustrate general issues relevant to eventual clinical or experimental tests of such an algorithm. Specifically, while the relationship between DBS characteristics and performance is highly complex, global search methods appear able to identify novel and effective waveforms with convergence rates that are acceptably fast to merit further investigation in laboratory or clinical settings.

Optoelectronic retinal prosthesis: system design and performance

Abstract: The design of high-resolution retinal prostheses presents many unique engineering and biological challenges. Ever smaller electrodes must inject enough charge to stimulate nerve cells, within electrochemically safe voltage limits. Stimulation sites should be placed within an electrode diameter from the target cells to prevent 'blurring' and minimize current. Signals must be delivered wirelessly from an external source to a large number of electrodes, and visual information should, ideally, maintain its natural link to eye movements. Finally, a good system must have a wide range of stimulation currents, external control of image processing and the option of either anodic-first or cathodic-first pulses. This paper discusses these challenges and presents solutions to them for a system based on a photodiode array implant. Video frames are processed and imaged onto the retinal implant by a head-mounted near-to-eye projection system operating at near-infrared wavelengths. Photodiodes convert light into pulsed electric current, with charge injection maximized by applying a common biphasic bias waveform. The resulting prosthesis will provide stimulation with a frame rate of up to 50 Hz in a central 10 degrees visual field, with a full 30 degrees field accessible via eye movements. Pixel sizes are scalable from 100 to 25 microm, corresponding to 640-10,000 pixels on an implant 3 mm in diameter.

Real and virtual mobility performance in simulated prosthetic vision

Abstract: Wayfinding is an important activity that can be performed with limited visual resources, and thus may be an important application of early visual prostheses. In a pair of experiments we explored minimal visual resolution requirements of a simulated retinal electrode array for mobility in real and virtual environments, experienced by normally sighted subjects in video headsets. In experiment 1, inexperienced and experienced subjects traveled similar routes around a suite of offices with simulated implants of 4 x 4, 6 x 10 and 16 x 16 dots. In experiment 2, the effects of adding dynamic noise and removing a subset of 'phosphenes' from a 6 x 10 dot array on the mobility of experienced subjects through a series of different virtual 10-room buildings were determined. Performance was quantified in terms of time and navigation errors in both experiments, and wall contacts in the real environment; a compound score was also computed for trials in experiment 1. In experiment 1, inexperienced subjects required 16 x 16 dots for adequate performance, while experienced subjects reached similar levels with 6 x 10 dots. In experiment 2, dot removal up to 30% led to modest yet significant performance deterioration, and noise addition to slight but non-significant improvement, while practice led to a reduction in travel time by 50% over the 28-trial experiment. Error counts in experiment 2 were fairly high, but largely randomly distributed, and attributable to the high risk of becoming disoriented in the sparse visual environment. Substantial performance level differences were found between subjects, spanning a threefold range even after practice. The findings suggest that a retinal implant with as few as 60 electrodes may provide independent wayfinding abilities to the adventitiously blind, but that substantial practice and supervision will be required in learning this task.

An electronic device for artefact suppression in human local field potential recordings during deep brain stimulation

Abstract: The clinical efficacy of high-frequency deep brain stimulation (DBS) for Parkinson's disease and other neuropsychiatric disorders likely depends on the modulation of neuronal rhythms in the target nuclei. This modulation could be effectively measured with local field potential (LFP) recordings during DBS. However, a technical drawback that prevents LFPs from being recorded from the DBS target nuclei during stimulation is the stimulus artefact. To solve this problem, we designed and developed 'FilterDBS', an electronic amplification system for artefact-free LFP recordings (in the frequency range 2–40 Hz) during DBS. After defining the estimated system requirements for LFP amplification and DBS artefact suppression, we tested the FilterDBS system by conducting experiments in vitro and in vivo in patients with advanced Parkinson's disease undergoing DBS of the subthalamic nucleus (STN). Under both experimental conditions, in vitro and in vivo, the FilterDBS system completely suppressed the DBS artefact without inducing significant spectral distortion. The FilterDBS device pioneers the development of an adaptive DBS system retroacted by LFPs and can be used in novel closed-loop brain–machine interface applications in patients with neurological disorders.

Responses of ganglion cells to repetitive electrical stimulation of the retina

Abstract: Retinal ganglion cells (RGCs) can be activated electrically either directly or indirectly (via the retinal neural network). Previous studies have shown that RGCs can follow high stimulus rates (> or = 200 pulses s(-1)) when directly activated. In the present study, we investigated how well RGCs can follow repetitive stimulation of the neural network. We studied the responses (spike activity) of RGCs in isolated rabbit retina to stimulation with paired pulses applied at different interpulse intervals and trains of pulses applied at different frequencies. We found that the response amplitude of a RGC to a current pulse applied soon (< or = 400 ms) after a preceding current pulse is diminished. This depression in response amplitude became greater as the interval between pulses became shorter. At an interpulse interval of 15 ms (shortest tested), the response amplitude to the second current pulse was reduced on average 94%. When a train of ten stimulus pulses was applied, further depression was observed, particularly at high stimulation frequencies. The depression with each successive pulse was relatively moderate compared to the depression to the second pulse. The results of this study have implications for the design of electrical stimulation strategies in a retinal prosthesis.

New functional electrical stimulation approaches to standing and walking.

Abstract: Spinal cord injury (SCI) is a devastating neurological trauma that is prevalent predominantly in young individuals. Several interventions in the areas of neuroregeneration, pharmacology and rehabilitation engineering/neuroscience are currently under investigation for restoring function after SCI. In this paper, we focus on the use of neuroprosthetic devices for restoring standing and ambulation as well as improving general health and wellness after SCI. Four neuroprosthetic approaches are discussed along with their demonstrated advantages and their future needs for improved clinical applicability. We first introduce surface functional electrical stimulation (FES) devices for restoring ambulation and highlight the importance of these devices for facilitating exercise activities and systemic physiological activation. Implanted muscle-based FES devices for restoring standing and walking that are currently undergoing clinical trials are then presented. The use of implanted peripheral nerve intraneural arrays of multi-site microelectrodes for providing fine and graded control of force during sit-to-stand maneuvers is subsequently demonstrated. Finally, intraspinal microstimulation (ISMS) of the lumbosacral spinal cord for restoring standing and walking is introduced and its results to date are presented. We conclude with a general discussion of the common needs of the neuroprosthetic devices presented in this paper and the improvements that may be incorporated in the future to advance their clinical utility and user satisfaction.

Prediction of upper limb muscle activity from motor cortical discharge during reaching

Abstract: Movement representation by the motor cortex (M1) has been a theoretical interest for many years, but in the past several years it has become a more practical question, with the advent of the brain–machine interface. An increasing number of groups have demonstrated the ability to predict a variety of kinematic signals on the basis of M1 recordings and to use these predictions to control the movement of a cursor or robotic limb. We, on the other hand, have undertaken the prediction of myoelectric (EMG) signals recorded from various muscles of the arm and hand during button pressing and prehension movements. We have shown that these signals can be predicted with accuracy that is similar to that of kinematic signals, despite their stochastic nature and greater bandwidth. The predictions were made using a subset of 12 or 16 neural signals selected in the order of each signal's unique, output-related information content. The accuracy of the resultant predictions remained stable through a typical experimental session. Accuracy remained above 80% of its initial level for most muscles even across periods as long as two weeks. We are exploring the use of these predictions as control signals for neuromuscular electrical stimulation in quadriplegic patients.

Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

Abstract: We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45–60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjogren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results.

Minocycline increases quality and longevity of chronic neural recordings.

Abstract: Brain/machine interfaces could potentially be used in the treatment of a host of neurological disorders ranging from paralysis to sensory deficits. Insertion of chronic micro-electrode arrays into neural tissue initiates a host of immunological responses, which typically leads to the formation of a cellular sheath around the implant, resulting in the loss of useful signals. Minocycline has been shown to have neuroprotective and neurorestorative effects in certain neural injury and neurodegenerative disease models. This study examined the effects of minocycline administration on the quality and longevity of chronic multi-channel microwire neural implants 1 week and 1 month post-implantation in auditory cortex. The mean signal-to-noise ratio for the minocycline group stabilized at the end of week 1 and remained above 4.6 throughout the following 3 weeks. The control group signal-to-noise ratio dropped throughout the duration of the study and at the end of 4 weeks was 2.6. Furthermore, 68% of electrodes from the minocycline group showed significant stimulus-driven activity at week 4 compared to 12.5% of electrodes in the control group. There was a significant reduction in the number of activated astrocytes around the implant in minocycline subjects, as well as a reduction in total area occupied by activated astrocytes at 1 and 4 weeks.

Amplitude and phase coupling measures for feature extraction in an EEG-based brain-computer interface.

Abstract: Most of the feature extraction methods in existing brain-computer interfaces (BCIs) are based on the dynamic behavior of separate signals, without using the coupling information between different brain regions. In this paper, amplitude and phase coupling measures, quantified by a nonlinear regressive coefficient and phase locking value respectively, were used for feature extraction. The two measures were based on three different coupling methods determined by neurophysiological a priori knowledge, and applied to a small number of electrodes of interest, leading to six feature vectors for classification. Five subjects participated in an online BCI experiment during which they were asked to imagine a movement of either the left or right hand. The electroencephalographic (EEG) recordings from all subjects were analyzed offline. The averaged classification accuracies of the five subjects ranged from 87.4% to 92.9% for the six feature vectors and the best classification accuracies of the six feature vectors ranged between 84.4% and 99.6% for the five subjects. The performance of coupling features was compared with that of the autoregressive (AR) feature. Results indicated that coupling measures are appropriate methods for feature extraction in BCIs. Furthermore, the combination of coupling and AR feature can effectively improve the classification accuracy due to their complementarities.

Thin microelectrodes reduce GFAP expression in the implant site in rodent somatosensory cortex.

Abstract: The objective of this study was to test the hypothesis that neural implants with reduced cross-sectional areas will have less glial scarring associated with implantation injury in long-term experiments. In this study, we implanted nine adult rats with two different implants of 12 microm (n = 6), and 25 microm (n = 6) diameters (cross-sectional areas of 68 microm(2), 232 microm(2) respectively) and the expression of glial fibrilliary acidic protein (GFAP) was assessed after 2 weeks and 4 weeks of implantation. In order to facilitate implantation, the 12 microm diameter implants were coated with poly-glycolic acid (PGA), a biodegradable polymer that degraded within minutes of implantation. In n = 3 animals, 25 microm diameter implants also coated with PGA were implanted and assessed for GFAP expression at the end of 4 weeks of implantation. Statistical analysis of the GFAP expression around the different implants demonstrated that after 2 weeks of implantation there is no statistically significant difference in GFAP expression between the 12 microm and the 25 microm diameter implants. However, after 4 weeks of implantation the implant site of 12 microm diameter implants exhibited a statistically significant reduction in GFAP expression when compared to the implant sites of the 25 microm diameter implants (both with and without the PGA coating). We conclude that in neural implants that are tethered to the skull, implant cross-sectional areas of 68 microm(2) and smaller could lead to a reduced glial scarring under chronic conditions. Future studies with longer implant durations can confirm if this observation remains consistent beyond 4 weeks.

Interaction of embryonic cortical neurons on nanofibrous scaffolds for neural tissue engineering.

Abstract: The interaction of murine embryonic cortical neurons on randomly orientated electrospun scaffolds of poly(L-lactide) (PLLA) and poly(lactide-co-glycolide) (PLGA) is investigated in this study. The scaffolds were surface treated with different concentrations of KOH to partially hydrolyze the surface and therefore change the surface tension. Hydrophilicity did not significantly influence the number of primary and secondary branches; however, it had a considerable effect on neurite extension. For scaffolds with surface tensions of 40–47 dyn cm−1 there was a significantly greater overall neurite length for both the primary and secondary branches compared with more hydrophilic scaffolds. Another major finding of this work was that the interfibre distance influenced how the neurites extended. When the interfibre distance was greater than approximately 15 µm the neurites followed the fibres and avoided regions of very high fibre density. At interfibre distances less than approximately 15 µm, the neurites traversed between the fibres. Therefore, this study provided little evidence that contact guidance was the dominating cue in directing neurite extension, instead inferring that chemical cues, possibly from adjacent neurons had induced directional change.

Limb-state feedback from ensembles of simultaneously recorded dorsal root ganglion neurons

Abstract: Functional electrical stimulation (FES) holds great potential for restoring motor functions after brain and spinal cord injury. Currently, most FES systems are under simple finite state control, using external sensors which tend to be bulky, uncomfortable and prone to failure. Sensory nerve signals offer an interesting alternative, with the possibility of continuous feedback control. To test feasibility, we recorded from ensembles of sensory neurons with microelectrode arrays implanted in the dorsal root ganglion (DRG) of walking cats. Limb position and velocity variables were estimated accurately (average R2 values >0.5) over a range of walking speeds (0.1?0.5 m s?1) using a linear combination of firing rates from 10 or more neurons. We tested the feasibility of sensory control of intraspinal FES by recording from DRG neurons during hindlimb movements evoked by intraspinal microstimulation of the lumbar spinal cord in an anesthetized cat. Although electrical stimulation generated artifacts, this problem was overcome by detecting and eliminating events that occurred synchronously across the array of microelectrodes. The sensory responses to limb movement could then be measured and decoded to generate an accurate estimate of the limb state. Multichannel afferent recordings may thus provide FES systems with the feedback needed for adaptive control and perturbation compensation, though long-term stability remains a challenge.

A single-chip signal processing and telemetry engine for an implantable 96-channel neural data acquisition system.

Abstract: A fully implantable neural data acquisition system is a key component of a clinically viable cortical brain–machine interface. We present the design and implementation of a single-chip device that serves the processing needs of such a system. Our device processes 96 channels of multi-unit neural data and performs all digital processing necessary for bidirectional wireless communication. The implementation utilizes a single programmable logic device that is responsible for performing data reduction on the 96 channels of neural data, providing a bidirectional telemetry interface to a transceiver and performing command interpretation and system supervision. The device takes as input neural data sampled at 31.25 kHz and outputs a line-encoded serial bitstream containing the information to be transmitted by the transceiver. Data can be output in one of the following four modes: (1) streaming uncompressed data from a single channel, (2) extracted spike waveforms from any subset of the 96 channels, (3) 1 ms bincounts for each channel or (4) streaming data along with extracted spikes from a single channel. The device can output up to 2000 extracted spikes per second with latencies suitable for a brain–machine interface application. This device provides all of the digital processing components required by a fully implantable system.

Quasi-trapezoidal pulses to selectively block the activation of intrinsic laryngeal muscles during vagal nerve stimulation.

Abstract: The stimulation of the vagus nerve has been used as an anti-epileptic treatment for over a decade, and its use for depression and chronic heart failure is currently under investigation. Co-activation of the intrinsic laryngeal muscles may limit the clinical use of vagal stimulation, especially in the case of prolonged activation. To prevent this, the use of a selective stimulation paradigm has been tested in seven acute pig experiments. Quasi-trapezoidal pulses successfully blocked the population of the largest and fastest vagal myelinated fibers being responsible for the co-activation. The first response in the vagus compound action potential was reduced by 75 +/- 22% (mean +/- SD) and the co-activated muscle action potential by 67 +/- 25%. The vagal bradycardic effects remained unchanged during the selective block, confirming the leading role of thin nerve fibers for the vagal control of the heart. Quasi-trapezoidal pulses may be an alternative to rectangular pulses in clinical vagal stimulation when the co-activation of laryngeal muscles must be avoided.

The influence of electrolyte composition on the in vitro charge-injection limits of activated iridium oxide (AIROF) stimulation electrodes

Abstract: The effects of ionic conductivity and buffer concentration of electrolytes used for in vitro measurement of the charge-injection limits of activated iridium oxide (AIROF) neural stimulation electrodes have been investigated. Charge-injection limits of AIROF microelectrodes were measured in saline with a range of phosphate buffer concentrations from [PO43−] = 0 to [PO43−] = 103 mM and ionic conductivities from 2–28 mS cm−1. The charge-injection limits were insensitive to the buffer concentration, but varied significantly with ionic conductivity. Using 0.4 ms cathodal current pulses at 50 Hz, the charge-injection limit increased from 0.5 mC cm−2 to 2.1 mC cm−2 as the conductivity was increased from 2 mS cm−1 to 28 mS cm−1. An explanation is proposed in which the observed dependence on ionic conductivity arises from non-uniform reduction and oxidation within the porous AIROF and from uncorrected iR-drops that result in an overestimation of the redox potential during pulsing. Conversely, slow-sweep-rate cyclic voltammograms (CVs) were sensitive to buffer concentration with the potentials of the primary Ir3+/Ir4+ reduction and oxidation reactions shifting ~300 mV as the buffer concentration decreased from [PO43−] = 103 mM to [PO43−] = 0 mM. The CV response was insensitive to ionic conductivity. A comparison of in vitro AIROF charge-injection limits in commonly employed electrolyte models of extracellular fluid revealed a significant dependence on the electrolyte, with more than a factor of 4 difference under some pulsing conditions, emphasizing the need to select an electrolyte model that closely matches the conductivity and ionic composition of the in vivo environment.

Classification of motor imagery by means of cortical current density estimation and Von Neumann entropy

Abstract: The goal of the present study is to employ the source imaging methods such as cortical current density estimation for the classification of left- and right-hand motor imagery tasks, which may be used for brain-computer interface (BCI) applications. The scalp recorded EEG was first preprocessed by surface Laplacian filtering, time-frequency filtering, noise normalization and independent component analysis. Then the cortical imaging technique was used to solve the EEG inverse problem. Cortical current density distributions of left and right trials were classified from each other by exploiting the concept of Von Neumann entropy. The proposed method was tested on three human subjects (180 trials each) and a maximum accuracy of 91.5% and an average accuracy of 88% were obtained. The present results confirm the hypothesis that source analysis methods may improve accuracy for classification of motor imagery tasks. The present promising results using source analysis for classification of motor imagery enhances our ability of performing source analysis from single trial EEG data recorded on the scalp, and may have applications to improved BCI systems.

Free-paced high-performance brain-computer interfaces.

Abstract: Neural prostheses aim to improve the quality of life of severely disabled patients by translating neural activity into control signals for guiding prosthetic devices or computer cursors. We recently demonstrated that plan activity from premotor cortex, which specifies the endpoint of the upcoming arm movement, can be used to swiftly and accurately guide computer cursors to the desired target locations. However, these systems currently require additional, non-neural information to specify when plan activity is present. We report here the design and performance of state estimator algorithms for automatically detecting the presence of plan activity using neural activity alone. Prosthesis performance was nearly as good when state estimation was used as when perfect plan timing information was provided separately (~5 percentage points lower, when using 200 ms of plan activity). These results strongly suggest that a completely neurally-driven high-performance brain?computer interface is possible.

Prosthetic interfaces with the visual system: biological issues

Abstract: The design of effective visual prostheses for the blind represents a challenge for biomedical engineers and neuroscientists. Significant progress has been made in the miniaturization and processing power of prosthesis electronics; however development lags in the design and construction of effective machine–brain interfaces with visual system neurons. This review summarizes what has been learned about stimulating neurons in the human and primate retina, lateral geniculate nucleus and visual cortex. Each level of the visual system presents unique challenges for neural interface design. Blind patients with the retinal degenerative disease retinitis pigmentosa (RP) are a common population in clinical trials of visual prostheses. The visual performance abilities of normals and RP patients are compared. To generate pattern vision in blind patients, the visual prosthetic interface must effectively stimulate the retinotopically organized neurons in the central visual field to elicit patterned visual percepts. The development of more biologically compatible methods of stimulating visual system neurons is critical to the development of finer spatial percepts. Prosthesis electrode arrays need to adapt to different optimal stimulus locations, stimulus patterns, and patient disease states.

Effects of ramped amplitude waveforms on the onset response of high-frequency mammalian nerve block.

Abstract: Though high-frequency alternating current (HFAC) can block nerve conduction, the block is invariably preceded by an onset response which is a period of repetitive nerve firing. We tested the hypothesis that slowly ramping up the amplitude of the HFAC waveform could produce block without this initial onset response. Computer simulations were performed, using the McIntyre-Richardson-Grill (MRG) model of myelinated mammalian axon. A ramped-amplitude HFAC was applied to axons of diameters ranging from 7.3 microm to 16 microm and at frequencies ranging from 3125 Hz to 40 kHz. The ramped-amplitude HFAC was also investigated in vivo in preparations of rat sciatic nerve. Sinusoidal voltage-regulated waveforms, at frequencies between 10 kHz and 30 kHz, were applied with initial amplitudes of 0 V, linearly increasing with time to 10 V. Ramp durations ranged from 0 s to 60 s. In both the MRG model simulations and the experiments, ramping the HFAC waveform did not eliminate the onset response. In the rat experiments, the peak amplitude of the onset response was lessened by ramping the amplitude, but both the onset response duration and the amount of onset activity as measured by the force-time integral were increased.