Showing papers in "Journal of Neural Engineering in 2009"
TL;DR: The positive characteristics of the proposed SSVEP-based BCI system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.
Abstract: In recent years, there has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain–computer interface (BCI) systems. However, several aspects of current SSVEP-based BCI systems need improvement, specifically in relation to speed, user variation and ease of use. With these improvements in mind, this paper presents an online multi-channel SSVEP-based BCI system using a canonical correlation analysis (CCA) method for extraction of frequency information associated with the SSVEP. The key parameters, channel location, window length and the number of harmonics, are investigated using offline data, and the result used to guide the design of the online system. An SSVEP-based BCI system with six targets, which use nine channel locations in the occipital and parietal lobes, a window length of 2 s and the first harmonic, is used for online testing on 12 subjects. The results show that the proposed BCI system has a high performance, achieving an average accuracy of 95.3% and an information transfer rate of 58 ± 9.6 bit min−1. The positive characteristics of the proposed system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.
694 citations
TL;DR: The results of this study suggest that a local, late onset neurodegenerative disease-like state surrounds the chronic electrodes and is a potential cause for chronic recording failure.
Abstract: Prosthetic devices that are controlled by intracortical electrodes recording one's 'thoughts' are a reality today, and no longer merely in the realm of science fiction. However, widespread clinical use of implanted electrodes is hampered by a lack of reliability in chronic recordings, independent of the type of electrodes used. One major hypothesis has been that astroglial scar electrically impedes the electrodes. However, there is a temporal discrepancy between stabilization of scar's electrical properties and recording failure with recording failure lagging by 1 month. In this study, we test a possible explanation for this discrepancy: the hypothesis that chronic inflammation, due to the persistent presence of the electrode, causes a local neurodegenerative state in the immediate vicinity of the electrode. Through modulation of chronic inflammation via stab wound, electrode geometry and age-matched control, we found that after 16 weeks, animals with an increased level of chronic inflammation were associated with increased neuronal and dendritic, but not axonal, loss. We observed increased neuronal and dendritic loss 16 weeks after implantation compared to 8 weeks after implantation, suggesting that the local neurodegenerative state is progressive. After 16 weeks, we observed axonal pathology in the form of hyperphosphorylation of the protein tau in the immediate vicinity of the microelectrodes (as observed in Alzheimer's disease and other tauopathies). The results of this study suggest that a local, late onset neurodegenerative disease-like state surrounds the chronic electrodes and is a potential cause for chronic recording failure. These results also inform strategies to enhance our capability to attain reliable long-term recordings from implantable electrodes in the CNS.
440 citations
TL;DR: A micromachined 252-channel ECoG (electrocorticogram)-electrode array, which is made of a thin polyimide foil substrate enclosing sputtered platinum electrode sites and conductor paths, designed to cover large parts of a hemisphere of a macaque monkey's cortex.
Abstract: We present a micromachined 252-channel ECoG (electrocorticogram)-electrode array, which is made of a thin polyimide foil substrate enclosing sputtered platinum electrode sites and conductor paths. The array subtends an area of approximately 35 mm by 60 mm and is designed to cover large parts of a hemisphere of a macaque monkey’s cortex. Eight omnetics connectors are directly soldered to the foil. This leads to a compact assembly size which enables a chronic implantation of the array and allows free movements of the animal between the recording sessions. The electrode sites are 1 mm in diameter and were characterized by electrochemical impedance spectroscopy. At 1 kHz, the electrode impedances vary between
407 citations
TL;DR: The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect of feedback on brain activity.
Abstract: Brain–computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications. The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect of feedback on brain activity. In this article we will review the critical steps of the BCI cycle, the present issues and state-of-the-art results. Moreover, we will develop a vision on how recently obtained results may contribute to new insights in neurocognition and, in particular, in the neural representation of perceived stimuli, intended actions and emotions. Now is the right time to explore what can be gained by embracing real-time, online BCI and by adding it to the set of experimental tools already available to the cognitive neuroscientist. We close by pointing out some unresolved issues and present our view on how BCI could become an important new tool for probing human cognition.
327 citations
TL;DR: Together, this work presents methods by which to produce highly aligned fiber scaffolds efficiently and techniques for assessing neurite outgrowth on different Fiber scaffolds, while suggesting that crossing fibers may be detrimental in fostering efficient, directed axonal outgrowth.
Abstract: Aligned, electrospun polymer fibers have shown considerable promise in directing regenerating axons in vitro and in vivo. However, in several studies, final electrospinning parameters are presented for producing aligned fiber scaffolds, and alignment where minimal fiber crossing occurs is not achieved. Highly aligned species are necessary for neural tissue engineering applications to ensure that axonal extension occurs through a regenerating environment efficiently. Axonal outgrowth on fibers that deviate from the natural axis of growth may delay axonal extension from one end of a scaffold to the other. Therefore, producing aligned fiber scaffolds with little fiber crossing is essential. In this study, the contributions of four electrospinning parameters (collection disk rotation speed, needle size, needle tip shape and syringe pump flow rate) were investigated thoroughly with the goal of finding parameters to obtain highly aligned electrospun fibers made from poly-L-lactic acid (PLLA). Using an 8 wt% PLLA solution in chloroform, a collection disk rotation speed of 1000 revolutions per minute (rpm), a 22 gauge, sharp-tip needle and a syringe pump rate of 2 ml h(-1) produced highly aligned fiber (1.2-1.6 microm in diameter) scaffolds verified using a fast Fourier transform and a fiber alignment quantification technique. Additionally, the application of an insulating sheath around the needle tip improved the rate of fiber deposition (electrospinning efficiency). Optimized scaffolds were then evaluated in vitro using embryonic stage nine (E9) chick dorsal root ganglia (DRGs) and rat Schwann cells (SCs). To demonstrate the importance of creating highly aligned scaffolds to direct neurite outgrowth, scaffolds were created that contained crossing fibers. Neurites on these scaffolds were directed down the axis of the aligned fibers, but neurites also grew along the crossed fibers. At times, these crossed fibers even stopped further axonal extension. Highly aligned PLLA fibers generated under optimized electrospinning conditions guided neurite and SC growth along the aligned fibers. Schwann cells demonstrated the bipolar phenotype seen along the fibers. Using a novel technique to determine fiber density, an increase in fiber density correlated to an increase in the number of neurites, but average neurite length was not statistically different between the two different fiber densities. Together, this work presents methods by which to produce highly aligned fiber scaffolds efficiently and techniques for assessing neurite outgrowth on different fiber scaffolds, while suggesting that crossing fibers may be detrimental in fostering efficient, directed axonal outgrowth.
300 citations
TL;DR: It is shown that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger.
Abstract: Brain signals can provide the basis for a non-muscular communication and control system, a brain‐computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function. M This article features online multimedia enhancements (Some figures in this article are in colour only in the electronic version)
279 citations
TL;DR: A novel dual-modality hybrid device, which consists of a tapered coaxial optical waveguide integrated into a 100 element intra-cortical multi-electrode recording array, is reported, which demonstrates the dual optical delivery and electrical recording capability of the single optrode in in vitro preparations of mouse retina.
Abstract: Neural stimulation with high spatial and temporal precision is desirable both for studying the real-time dynamics of neural networks and for prospective clinical treatment of neurological diseases. Optical stimulation of genetically targeted neurons expressing the light sensitive channel protein Channelrhodopsin (ChR2) has recently been reported as a means for millisecond temporal control of neuronal spiking activities with cell-type selectivity. This offers the prospect of enabling local delivery of optical stimulation and the simultaneous monitoring of the neural activity by electrophysiological means, both in the vicinity of and distant to the stimulation site. We report here a novel dual-modality hybrid device, which consists of a tapered coaxial optical waveguide (‘optrode’) integrated into a 100 element intra-cortical multi-electrode recording array. We first demonstrate the dual optical delivery and electrical recording capability of the single optrode in in vitro preparations of mouse retina, photo-stimulating the native retinal photoreceptors while recording light-responsive activities from ganglion cells. The dual-modality array device was then used in ChR2 transfected mouse brain slices. Specifically, epileptiform events were reliably optically triggered by the optrode and their spatiotemporal patterns were simultaneously recorded by the multi-electrode array.
211 citations
TL;DR: In vivo changes in the DBS electrode impedance that occur after implantation and during clinically relevant stimulation could play an important role in the observed functional effects of voltage-controlled DBS and should be considered during clinical stimulation parameter selection and chronic animal research studies.
Abstract: Deep brain stimulation (DBS) represents a powerful clinical technology, but a systematic characterization of the electrical interactions between the electrode and the brain is lacking. The goal of this study was to examine the in vivo changes in the DBS electrode impedance that occur after implantation and during clinically relevant stimulation. Clinical DBS devices typically apply high-frequency voltage-controlled stimulation, and as a result, the injected current is directly regulated by the impedance of the electrode-tissue interface. We monitored the impedance of scaled-down clinical DBS electrodes implanted in the thalamus and subthalamic nucleus of a rhesus macaque using electrode impedance spectroscopy (EIS) measurements ranging from 0.5 Hz to 10 kHz. To further characterize our measurements, equivalent circuit models of the electrode-tissue interface were used to quantify the role of various interface components in producing the observed electrode impedance. Following implantation, the DBS electrode impedance increased and a semicircular arc was observed in the high-frequency range of the EIS measurements, commonly referred to as the tissue component of the impedance. Clinically relevant stimulation produced a rapid decrease in electrode impedance with extensive changes in the tissue component. These post-operative and stimulation-induced changes in impedance could play an important role in the observed functional effects of voltage-controlled DBS and should be considered during clinical stimulation parameter selection and chronic animal research studies.
203 citations
TL;DR: Various changes to the visual aspects of this protocol are explored as well as their effects on classification, and the best performances, across both classifiers, were obtained with the white background (WB) visual protocol.
Abstract: The best known P300 speller brain-computer interface (BCI) paradigm is the Farwell and Donchin paradigm. In this paper, various changes to the visual aspects of this protocol are explored as well as their effects on classification. Changes to the dimensions of the symbols, the distance between the symbols and the colours used were tested. The purpose of the present work was not to achieve the highest possible accuracy results, but to ascertain whether these simple modifications to the visual protocol will provide classification differences between them and what these differences will be. Eight subjects were used, with each subject carrying out a total of six different experiments. In each experiment, the user spelt a total of 39 characters. Two types of classifiers were trained and tested to determine whether the results were classifier dependant. These were a support vector machine (SVM) with a radial basis function (RBF) kernel and Fisher's linear discriminant (FLD). The single-trial classification results and multiple-trial classification results were recorded and compared. Although no visual protocol was the best for all subjects, the best performances, across both classifiers, were obtained with the white background (WB) visual protocol. The worst performance was obtained with the small symbol size (SSS) visual protocol.
192 citations
TL;DR: This paper presents a comprehensive survey of the neural amplifiers described in publications prior to 2008, and methods to achieve high input impedance, low noise and a large time-constant high-pass filter are reviewed.
Abstract: Significant progress has been made in systems that interpret the electrical signals of the brain in order to control an actuator. One version of these systems senses neuronal extracellular action potentials with an array of up to 100 miniature probes inserted into the cortex. The impedance of each probe is high, so environmental electrical noise is readily coupled to the neuronal signal. To minimize this noise, an amplifier is placed close to each probe. Thus, the need has arisen for many amplifiers to be placed near the cortex. Commercially available integrated circuits do not satisfy the area, power and noise requirements of this application, so researchers have designed custom integrated-circuit amplifiers. This paper presents a comprehensive survey of the neural amplifiers described in publications prior to 2008. Methods to achieve high input impedance, low noise and a large time-constant high-pass filter are reviewed. A tutorial on the biological, electrochemical, mechanical and electromagnetic phenomena that influence amplifier design is provided. Areas for additional research, including sub-nanoampere electrolysis and chronic cortical heating, are discussed. Unresolved design concerns, including teraohm circuitry, electrical overstress and component failure, are identified.
176 citations
TL;DR: Two rhesus monkeys trained to move a cursor using neural activity recorded with silicon arrays of 96 microelectrodes implanted in the primary motor cortex achieved high-quality control comparable to the performance of decoding schemes based on sorted spikes.
Abstract: Two rhesus monkeys were trained to move a cursor using neural activity recorded with silicon arrays of 96 microelectrodes implanted in the primary motor cortex. We have developed a method to extract movement information from the recorded single and multi-unit activity in the absence of spike sorting. By setting a single threshold across all channels and fitting the resultant events with a spline tuning function, a control signal was extracted from this population using a Bayesian particle-filter extraction algorithm. The animals achieved high-quality control comparable to the performance of decoding schemes based on sorted spikes. Our results suggest that even the simplest signal processing is sufficient for high-quality neuroprosthetic control.
TL;DR: An NIRS-BCI paradigm based on directly decoding neural correlates of decision making, specifically subjective preference evaluation is proposed, and which drink was preferred on a single-trial basis is decoded.
Abstract: Near-infrared spectroscopy (NIRS) has recently been identified as a safe, portable and relatively low-cost signal acquisition tool for non-invasive brain-computer interface (BCI) development. The ultimate goal of BCI research is for the user to be able to communicate functional intent directly through thoughts. In this paper we propose an NIRS-BCI paradigm based on directly decoding neural correlates of decision making, specifically subjective preference evaluation. Nine subjects were asked to mentally evaluate two possible drinks and decide which they preferred. Frequency domain near-infrared spectroscopy was used to image each subject's prefrontal cortex during the task. Using mean signal amplitudes as features and linear discriminant analysis, we were able to decode which drink was preferred on a single-trial basis with an average accuracy of 80%.
TL;DR: The temporal dependence and spatial non-uniformity of R(f) and C(dl) suggested that a distributed network, with each element of the network having dynamics tailored to a specific stimulus waveform, is required to describe adequately the impedance of the DBS electrode-tissue interface.
Abstract: The objective of this study was to quantify the electrode-tissue interface impedance of electrodes used for deep brain stimulation (DBS). We measured the impedance of DBS electrodes using electrochemical impedance spectroscopy in vitro in a carbonate- and phosphate-buffered saline solution and in vivo following acute implantation in the brain. The components of the impedance, including the series resistance (R(s)), the Faradaic resistance (R(f)) and the double layer capacitance (C(dl)), were estimated using an equivalent electrical circuit. Both R(f) and C(dl) decreased as the sinusoidal frequency was increased, but the ratio of the capacitive charge transfer to the Faradaic charge transfer was relatively insensitive to the change of frequency. R(f) decreased and C(dl) increased as the current density was increased, and above a critical current density the interface impedance became nonlinear. Thus, the magnitude of the interface impedance was strongly dependent on the intensity (pulse amplitude and duration) of stimulation. The temporal dependence and spatial non-uniformity of R(f) and C(dl) suggested that a distributed network, with each element of the network having dynamics tailored to a specific stimulus waveform, is required to describe adequately the impedance of the DBS electrode-tissue interface. Voltage transients to biphasic square current pulses were measured and suggested that the electrode-tissue interface did not operate in a linear range at clinically relevant current amplitudes, and that the assumption of the DBS electrode being ideally polarizable was not valid under clinical stimulating conditions.
TL;DR: It is suggested that global muscle coordination may be a combination of higher order control of robust subject-specific muscle synergies and lower order controlof individuated muscles, and that this control paradigm may be useful in the control of EMG-based technologies, such as artificial limbs and functional electrical stimulation systems.
Abstract: Synchronous muscle synergies have been suggested as a framework for dimensionality reduction in muscle coordination. Many studies have shown that synergies form a descriptive framework for a wide variety of tasks. We examined if a muscle synergy framework could accurately predict the EMG patterns associated with untrained static hand postures, in essence, if they formed a predictive framework. Hand and forearm muscle activities were recorded while subjects statically mimed 33 postures of the American Sign Language alphabet. Synergies were extracted from a subset of training postures using non-negative matrix factorization and used to predict the EMG patterns of the remaining postures. Across the subject population, as few as 11 postures could form an eight-dimensional synergy framework that allowed for at least 90% prediction of the EMG patterns of all 33 postures, including trial-to-trial variations. Synergies were quite robust despite using different postures in the training set, and also despite using a varied number of postures. Estimated synergies were categorized into those which were subject-specific and those which were general to the population. Population synergies were sparser than the subject-specific synergies, typically being dominated by a single muscle. Subject-specific synergies were more balanced in the coactivation of multiple muscles. We suggest as a result that global muscle coordination may be a combination of higher order control of robust subject-specific muscle synergies and lower order control of individuated muscles, and that this control paradigm may be useful in the control of EMG-based technologies, such as artificial limbs and functional electrical stimulation systems.
TL;DR: A topographic analysis of the information related to arm movement direction that can be extracted from single trials of electrocorticographic signals recorded from the human frontal and parietal cortex shows that activity from the primary motor cortex carries most directional information.
Abstract: Information about arm movement direction in neuronal activity of the cerebral cortex can be used for movement control mediated by a brain–machine interface (BMI). Here we provide a topographic analysis of the information related to arm movement direction that can be extracted from single trials of electrocorticographic (ECoG) signals recorded from the human frontal and parietal cortex based on a precise assignment of ECoG recording channels to the subjects’ individual cortical anatomy and function. To this aim, each electrode contact was identified on structural MRI scans acquired while the electrodes were implanted and was thus related to the brain anatomy of each patient. Cortical function was assessed by direct cortical electrical stimulation. We show that activity from the primary motor cortex, in particular from the region showing hand and arm motor responses upon electrical stimulation, carries most directional information. The premotor, posterior parietal and lateral prefrontal cortex contributed gradually less, but still significant information. This gradient was observed for decoding from movement-related potentials, and from spectral amplitude modulations in low frequencies and in the high gamma band. Our findings thus demonstrate a close topographic correlation between cortical functional anatomy and direction-related information in humans that might be used for brain–machine interfacing.
TL;DR: It is shown that typically 100 mW cm(-2) in instantaneous light intensity on the neuron in order to stimulate action potentials is needed, and how this can be reduced down to safe levels to negate thermal and photochromic damage to the eye.
Abstract: The recent discovery that neurons can be photostimulated via genetic incorporation of artificial opsins is creating a revolution in the field of neural stimulation. In this paper we show its potential in the field of retinal prosthesis. We show that we need typically 100 mW cm−2 in instantaneous light intensity on the neuron in order to stimulate action potentials. We also show how this can be reduced down to safe levels in order to negate thermal and photochromic damage to the eye. We also describe a gallium nitride LED light source which is also able to generate patterns of the required intensity in order to transfer reliable images.
TL;DR: In this article, the most important challenges regarding this neuroprosthetic approach and emphasize the need for basic human psychophysical research on the best way of presenting complex stimulating patterns through multiple microelectrodes.
Abstract: Motivated by the success of cochlear implants for deaf patients, we are now facing the goal of creating a visual neuroprosthesis designed to interface with the occipital cortex as a means through which a limited but useful sense of vision could be restored in profoundly blind patients. We review the most important challenges regarding this neuroprosthetic approach and emphasize the need for basic human psychophysical research on the best way of presenting complex stimulating patterns through multiple microelectrodes. Continued research will hopefully lead to the development of and design specifications for the first generation of a cortically based visual prosthesis system.
TL;DR: It is revealed the presence of refractory and overlap effects in the event-related potentials in visual P300 speller datasets, and it is shown that such effects are dependent on stimulus parameters: an alternative stimulus type based on apparent motion suffers less from theRefractory effects and leads to an improved letter prediction performance.
Abstract: We reveal the presence of refractory and overlap effects in the event-related potentials in visual P300 speller datasets, and we show their negative impact on the performance of the system. This finding has important implications for how to encode the letters that can be selected for communication. However, we show that such effects are dependent on stimulus parameters: an alternative stimulus type based on apparent motion suffers less from the refractory effects and leads to an improved letter prediction performance.
TL;DR: It is demonstrated that PPy/PMAS supports nerve cell (PC12) differentiation, and that clinically relevant 250 Hz biphasic current pulses delivered via PPy-PMAS films significantly promote nerve cell differentiation in the presence of nerve growth factor (NGF).
Abstract: The purpose of this work was to investigate for the first time the potential biomedical applications of novel polypyrrole (PPy) composites incorporating a large polyelectrolyte dopant, poly (2-methoxy-5 aniline sulfonic acid) (PMAS). The physical and electrochemical properties were characterized. The PPy/PMAS composites were found to be smooth and hydrophilic and have low electrical impedance. We demonstrate that PPy/PMAS supports nerve cell (PC12) differentiation, and that clinically relevant 250 Hz biphasic current pulses delivered via PPy/PMAS films significantly promote nerve cell differentiation in the presence of nerve growth factor (NGF). The capacity of PPy/PMAS composites to support and enhance nerve cell differentiation via electrical stimulation renders them valuable for medical implants for neurological applications.
TL;DR: A 96-channel fully implantable neural data acquisition system that performs spike detection and extraction within the body and wirelessly transmits data to an external unit and is shown to integrate well into a brain-machine interface.
Abstract: A fully implantable neural data acquisition system is a key component of a clinically viable brain-machine interface. This type of system must communicate with the outside world and obtain power without the use of wires that cross through the skin. We present a 96-channel fully implantable neural data acquisition system. This system performs spike detection and extraction within the body and wirelessly transmits data to an external unit. Power is supplied wirelessly through the use of inductively coupled coils. The system was implanted acutely in sheep and successfully recorded, processed and transmitted neural data. Bidirectional communication between the implanted system and an external unit was successful over a range of 2 m. The system is also shown to integrate well into a brain-machine interface. This demonstration of a high channel-count fully implanted neural data acquisition system is a critical step in the development of a clinically viable brain-machine interface.
TL;DR: An overview of the main design issues including the choice of holographic device, field-of-view, resolution, physical size, generation of two- and three-dimensional patterns and their diffraction efficiency, choice of algorithms and computational effort is presented.
Abstract: Computer-generated holography is an emerging technology for stimulation of neuronal populations with light patterns. A holographic photo-stimulation system may be designed as a powerful research tool or a compact neural interface medical device, such as an optical retinal prosthesis. We present here an overview of the main design issues including the choice of holographic device, field-of-view, resolution, physical size, generation of two- and three-dimensional patterns and their diffraction efficiency, choice of algorithms and computational effort. The performance and characteristics of a holographic pattern stimulation system with kHz frame rates are demonstrated using experimental recordings from isolated retinas.
TL;DR: It is shown that the dynamical multistability of a network of bursting subthalamic neurons, caused by synaptic plasticity has a strong impact on the stimulus-response properties when exposed to weak and short desynchronizing stimuli.
Abstract: We show that the dynamical multistability of a network of bursting subthalamic neurons, caused by synaptic plasticity has a strong impact on the stimulus-response properties when exposed to weak and short desynchronizing stimuli. Intriguingly, such stimuli can reliably shift the network from a stable state with pathological synchrony and connectivity to a stable desynchronized state with down-regulated connectivity. However, unlike in the case of stronger coordinated reset stimulation, after termination of weaker stimulation the network may undergo a transient rebound of synchrony. When the coordinated reset stimulation is even weaker and/or shorter, so that a single stimulation epoch is not effective, the network dynamics and connectivity can still be reshaped in a cumulative manner by repetitive stimulation delivery.
TL;DR: A novel data visualization algorithm and several unique features that address shortcomings in patient neurophysiology and recording conditions are presented and can simplify and standardize the process of localizing the subthalamic nucleus (STN) for neurostimulation.
Abstract: Microelectrode recordings are a useful adjunctive method for subthalamic nucleus localization during deep brain stimulation surgery for Parkinson's disease. Attempts to quantitate and standardize this process, using single computational measures of neural activity, have been limited by variability in patient neurophysiology and recording conditions. Investigators have suggested that a multi-feature approach may be necessary for automated approaches to perform within acceptable clinical standards. We present a novel data visualization algorithm and several unique features that address these shortcomings. The algorithm extracts multiple computational features from the microelectrode neurophysiology and integrates them with tools from unsupervised machine learning. The resulting colour-coded map of neural activity reveals activity transitions that correspond to the anatomic boundaries of subcortical structures. Using these maps, a non-neurophysiologist is able to achieve sensitivities of 90% and 95% for STN entry and exit, respectively, to within 0.5 mm accuracy of the current gold standard. The accuracy of this technique is attributed to the multi-feature approach. This activity map can simplify and standardize the process of localizing the subthalamic nucleus (STN) for neurostimulation. Because this method does not require a stationary electrode for careful recording of unit activity for spike sorting, the length of the operation may be shortened.
TL;DR: The results suggest that this nerve-cuff electrode can be an effective and chronically stable tool for selectively stimulating distal nerve branches in the lower extremities for neuroprosthetic applications.
Abstract: This study describes the stability and selectivity of four-contact spiral nerve-cuff electrodes implanted bilaterally on distal branches of the femoral nerves of a human volunteer with spinal cord injury as part of a neuroprosthesis for standing and transfers. Stimulation charge threshold, the minimum charge required to elicit a visible muscle contraction, was consistent and low (mean threshold charge at 63 weeks post-implantation: 23.3 ± 8.5 nC) for all nerve-cuff electrode contacts over 63 weeks after implantation, indicating a stable interface with the peripheral nervous system. The ability of individual nerve-cuff electrode contacts to selectively stimulate separate components of the femoral nerve to activate individual heads of the quadriceps was assessed with fine-wire intramuscular electromyography while measuring isometric twitch knee extension moment. Six of eight electrode contacts could selectively activate one head of the quadriceps while selectively excluding others to produce maximum twitch responses of between 3.8 and 8.1 N m. The relationship between isometric twitch and tetanic knee extension moment was quantified, and selective twitch muscle responses scaled to between 15 and 35 N m in tetanic response to pulse trains with similar stimulation parameters. These results suggest that this nerve-cuff electrode can be an effective and chronically stable tool for selectively stimulating distal nerve branches in the lower extremities for neuroprosthetic applications.
TL;DR: This novel flexible electrode configuration provides a novel platform for experimentally examining neuronal activity during a range of brain movements and retained mechanical and electrical integrity following both durability studies and large movements within the cortex.
Abstract: Electrical activity is the ultimate functional measure of neuronal tissue and recording that activity remains a key technical challenge in neuroscience. The mechanical mismatch between rigid electrodes and compliant brain tissue is a critical limitation in applications where movement is an inherent component. An electrode that permits recording of neural activity, while minimizing tissue disruption, is beneficial for applications that encompass both normal physiological movements and those which require consistent recording during large tissue displacements. In order to test the extreme of this range of movement, flexible electrodes were developed to record activity during and immediately following cortical impact in the rat. Photolithography techniques were used to fabricate flexible electrodes that were readily insertable into the brain using a parylene C base and gold conduction lines and contact pads, permitting custom geometry. We found that this electrode configuration retained mechanical and electrical integrity following both durability studies and large movements within the cortex. This novel flexible electrode configuration provides a novel platform for experimentally examining neuronal activity during a range of brain movements.
TL;DR: This architecture is thus based on distributed stimulation units that need only a two-wire bus to communicate, regardless of the number of poles of each DSU-driven electrode, which minimizes the required bandwidth between master and distributed units, increases the safety and stimulation features and decreases the complexity of the surgical approach.
Abstract: We present a new system for functional electrical stimulation (FES) applications based on networked stimulation units. They embed an advanced analog circuit, which provides multipolar and multiphasic stimulation profiles, and digital circuits, which ensure safety, locally executed programmed profiles, and communication with the master controller. This architecture is thus based on distributed stimulation units (DSU) that need only a two-wire bus to communicate, regardless of the number of poles of each DSU-driven electrode. This structure minimizes the required bandwidth between master and distributed units, increases the safety and stimulation features and decreases the complexity of the surgical approach. We have successfully tested this network-based stimulation architecture on benchtop stimulators. This original approach allows broad exploration of all possible methods to stimulate peripheral nerves, particularly in the goal of restoring the motor function. It provides a powerful research device to determine the optimal, least aggressive and the most efficient way to activate the peripheral nervous system using an implanted FES system that is less invasive than other existing devices.
TL;DR: The proposed BCI provides a new practical multidimensional method by noninvasive EEG signal associated with human natural behavior, which does not need long-term training.
Abstract: This study aims to explore whether human intentions to move or cease to move right and left hands can be decoded from spatiotemporal features in non-invasive EEG in order to control a discrete two-dimensional cursor movement for a potential multidimensional brain-computer interface (BCI). Five naive subjects performed either sustaining or stopping a motor task with time locking to a predefined time window by using motor execution with physical movement or motor imagery. Spatial filtering, temporal filtering, feature selection and classification methods were explored. The performance of the proposed BCI was evaluated by both offline classification and online two-dimensional cursor control. Event-related desynchronization (ERD) and post-movement event-related synchronization (ERS) were observed on the contralateral hemisphere to the hand moved for both motor execution and motor imagery. Feature analysis showed that EEG beta band activity in the contralateral hemisphere over the motor cortex provided the best detection of either sustained or ceased movement of the right or left hand. The offline classification of four motor tasks (sustain or cease to move right or left hand) provided 10-fold cross-validation accuracy as high as 88% for motor execution and 73% for motor imagery. The subjects participating in experiments with physical movement were able to complete the online game with motor execution at an average accuracy of 85.5 +/- 4.65%; the subjects participating in motor imagery study also completed the game successfully. The proposed BCI provides a new practical multidimensional method by noninvasive EEG signal associated with human natural behavior, which does not need long-term training.
TL;DR: In this paper, the authors used neurotrophic factors to promote the regeneration of the peripheral dendrites of auditory neurons and guide them towards intracochlear electrodes, and then used a stop signal to arrest regeneration once the electrode has been reached.
Abstract: The perceptual performance of cochlear implant recipients seems to have reached a plateau in recent years. This may be attributable to inadequate neural selectivity of available intracochlear electrodes, caused by current spread and electrode interactions. Attempts to improve electrode selectivity have included manipulating the number and configuration of electrodes that are stimulated at any one time, displacing perilymph from the cochlea to restrict current flow along the cochlea, and reducing the distance between electrodes and neurons. One experimental approach by which the distance between neurons and electrodes may be reduced is to use neurotrophic factors to promote the regeneration of the peripheral dendrites of auditory neurons and guide them towards intracochlear electrodes. The likely requirements of a system for regenerating auditory neurons towards the cochlear electrode include either a stable release of neurotrophin, or transient neurotrophin followed by electrical stimulation; a close proximity of electrode to osseous spiral lamina or a polymer to bridge the gap between the two; guidance signals to attract neurons towards the electrode; patterning of the electrode surface to direct dendrites to electrode contacts and a 'stop' signal to arrest regeneration once the electrode has been reached.
TL;DR: This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype.
Abstract: Epilepsy affects more than 1% of the world's population. Responsive neurostimulation is emerging as an alternative therapy for the 30% of the epileptic patient population that does not benefit from pharmacological treatment. Efficient seizure detection algorithms will enable closed-loop epilepsy prostheses by stimulating the epileptogenic focus within an early onset window. Critically, this is expected to reduce neuronal desensitization over time and lead to longer-term device efficacy. This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation. Hippocampal depth-electrode recordings from six kainate-treated rats are used to validate the algorithm and hardware performance in this preliminary study. The design process illustrates crucial trade-offs in translating mathematical models into hardware implementations and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype. Using quantitatively predicted thresholds from the depth-electrode recordings, the auto-updating algorithm performs with an average sensitivity and selectivity of 95.3 ± 0.02% and 88.9 ± 0.01% (mean ± SEα = 0.05), respectively, on untrained data with a detection delay of 8.5 s [5.97, 11.04] from electrographic onset. The hardware implementation is shown feasible using CMOS circuits consuming under 350 nW of power from a 250 mV supply voltage from simulations on the MIT 180 nm SOI process.
TL;DR: The experimental results, along with computer simulations, suggest that astrocytes are a predominant cellular player affecting electrical impedance spectra, and that the largest contribution from reactive astroCytes on impedance Spectra occurs in the first 100 microm from the interface, where electrodes are most likely to record electrical signals.
Abstract: The widespread adoption of neural prosthetic devices is currently hindered by our inability to reliably record neural signals from chronically implanted electrodes. The extent to which the local tissue response to implanted electrodes influences recording failure is not well understood. To investigate this phenomenon, impedance spectroscopy has shown promise for use as a non-invasive tool to estimate the local tissue response to microelectrodes. Here, we model impedance spectra from chronically implanted rats using the well-established Cole model, and perform a correlation analysis of modeled parameters with histological markers of astroglial scar, including glial fibrillary acid protein (GFAP) and 4',6-diamidino-2- phenylindole (DAPI). Correlations between modeled parameters and GFAP were significant for three parameters studied: Py value, Ro and |Z|1 kHz, and in all cases were confined to the first 100 µm from the interface. Py value was the only parameter also correlated with DAPI in the first 100 µm. Our experimental results, along with computer simulations, suggest that astrocytes are a predominant cellular player affecting electrical impedance spectra. The results also suggest that the largest contribution from reactive astrocytes on impedance spectra occurs in the first 100 µm from the interface, where electrodes are most likely to record electrical signals. These results form the basis for future approaches where impedance spectroscopy can be used to evaluate neural implants, evaluate strategies to minimize scar and potentially develop closed-loop prosthetic devices.