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In JoVE (1)
Other Publications (10)
- Lab on a Chip
- IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
- Journal of Neurophysiology
- Journal of Neurosurgery
- Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
- Epilepsy & Behavior : E&B
- Frontiers in Neuroengineering
- IEEE Transactions on Bio-medical Engineering
- Clinical EEG and Neuroscience : Official Journal of the EEG and Clinical Neuroscience Society (ENCS)
- Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
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Articles by J. Adam Wilson in JoVE
JoVE General
باستخدام EEG المستندة إلى الدماغ الحاسوب واجهة لحركة المؤشر الظاهري مع BCI2000
1Department of Biomedical Engineering, University of Wisconsin-Madison, 2Wadsworth Center, New York State Dept. of Health
في هذا الفيديو ، ونحن لشرح الخطوات المطلوبة لتشغيل تجربة واجهة المخ الكمبيوتر ، بما في ذلك وضع سقف EEG ، معايرة النظام ، وتدريب المستخدم لنقل المؤشر في بعدين باستخدام حركات متوهمة.
Other articles by J. Adam Wilson on PubMed
Integrated Microelectrode Array and Microfluidics for Temperature Clamp of Sensory Neurons in Culture
A device for cell culture is presented that combines MEMS technology and liquid-phase photolithography to create a microfluidic chip that influences and records electrical cellular activity. A photopolymer channel network is formed on top of a multichannel microelectrode array. Preliminary results indicated successful local thermal control within microfluidic channels and control of lamina position over the electrode array. To demonstrate the biological application of such a device, adult dissociated dorsal root ganglion neurons with a subpopulation of thermally-sensitive cells are attached onto the electrode array. Using laminar flow, dynamic control of local temperature of the neural cells was achieved while maintaining a constant chemical culture medium. Recording the expected altered cellular activity confirms the success of the integrated device.
ECoG Factors Underlying Multimodal Control of a Brain-computer Interface
Most current brain-computer interface (BCI) systems for humans use electroencephalographic activity recorded from the scalp, and may be limited in many ways. Electrocorticography (ECoG) is believed to be a minimally-invasive alternative to electroencephalogram (EEG) for BCI systems, yielding superior signal characteristics that could allow rapid user training and faster communication rates. In addition, our preliminary results suggest that brain regions other than the sensorimotor cortex, such as auditory cortex, may be trained to control a BCI system using similar methods as those used to train motor regions of the brain. This could prove to be vital for users who have neurological disease, head trauma, or other conditions precluding the use of sensorimotor cortex for BCI control.
Action Potentials Induce Uniform Calcium Influx in Mammalian Myelinated Optic Nerves
The myelin sheath enables saltatory conduction by demarcating the axon into a narrow nodal region for excitation and an extended, insulated internodal region for efficient spread of passive current. This anatomical demarcation produces a dramatic heterogeneity in ionic fluxes during excitation, a classical example being the restriction of Na influx at the node. Recent studies have revealed that action potentials also induce calcium influx into myelinated axons of mammalian optic nerves. Does calcium influx in myelinated axons show spatial heterogeneity during nerve excitation? To address this, we analyzed spatial profiles of axonal calcium transients during action potentials by selectively staining axons with calcium indicators and subjected the data to theoretical analysis with parameters for axial calcium diffusion empirically determined using photolysis of caged compounds. The results show surprisingly that during action potentials, calcium influx occurs uniformly along an axon of a fully myelinated mouse optic nerve.
Electrocorticographically Controlled Brain-computer Interfaces Using Motor and Sensory Imagery in Patients with Temporary Subdural Electrode Implants. Report of Four Cases
Brain-computer interface (BCI) technology can offer individuals with severe motor disabilities greater independence and a higher quality of life. The BCI systems take recorded brain signals and translate them into real-time actions, for improved communication, movement, or perception. Four patient participants with a clinical need for intracranial electrocorticography (ECoG) participated in this study. The participants were trained over multiple sessions to use motor and/or auditory imagery to modulate their brain signals in order to control the movement of a computer cursor. Participants with electrodes over motor and/or sensory areas were able to achieve cursor control over 2 to 7 days of training. These findings indicate that sensory and other brain areas not previously considered ideal for ECoG-based control can provide additional channels of control that may be useful for a motor BCI.
A Cortical Recording Platform Utilizing MicroECoG Electrode Arrays
Clinical applications of brain implantable devices for recording and interpreting electrical signals from the cortex have grown rapidly in the last decade. For long-term cortical recording, a micro-electrocorticographic (microECoG) electrode and universal platform were developed and evaluated. The electrode diameters and inter-electrode distances of the new device are on the order of 100s of microm, significantly smaller than general ECoG grids, and do not require penetrating the brain. Acute recordings from the device demonstrated that independent brain activity could be recorded from electrodes with a spatial resolution of 1 mm.
A Practical Procedure for Real-time Functional Mapping of Eloquent Cortex Using Electrocorticographic Signals in Humans
Functional mapping of eloquent cortex is often necessary prior to invasive brain surgery, but current techniques that derive this mapping have important limitations. In this article, we demonstrate the first comprehensive evaluation of a rapid, robust, and practical mapping system that uses passive recordings of electrocorticographic signals. This mapping procedure is based on the BCI2000 and SIGFRIED technologies that we have been developing over the past several years. In our study, we evaluated 10 patients with epilepsy from four different institutions and compared the results of our procedure with the results derived using electrical cortical stimulation (ECS) mapping. The results show that our procedure derives a functional motor cortical map in only a few minutes. They also show a substantial concurrence with the results derived using ECS mapping. Specifically, compared with ECS maps, a next-neighbor evaluation showed no false negatives, and only 0.46 and 1.10% false positives for hand and tongue maps, respectively. In summary, we demonstrate the first comprehensive evaluation of a practical and robust mapping procedure that could become a new tool for planning of invasive brain surgeries.
Massively Parallel Signal Processing Using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction
The clock speeds of modern computer processors have nearly plateaued in the past 5 years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card [graphics processing unit (GPU)] was developed for real-time neural signal processing of a brain-computer interface (BCI). The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter), followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a central processing unit-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels of 250 ms in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.
A Procedure for Measuring Latencies in Brain-computer Interfaces
Brain-computer interface (BCI) systems must process neural signals with consistent timing in order to support adequate system performance. Thus, it is important to have the capability to determine whether a particular BCI configuration (i.e., hardware and software) provides adequate timing performance for a particular experiment. This report presents a method of measuring and quantifying different aspects of system timing in several typical BCI experiments across a range of settings, and presents comprehensive measures of expected overall system latency for each experimental configuration.
A Micro-electrocorticography Platform and Deployment Strategies for Chronic BCI Applications
Over the past decade, electrocorticography (ECoG) has been used for a wide set of clinical and experimental applications. Recently, there have been efforts in the clinic to adapt traditional ECoG arrays to include smaller recording contacts and spacing. These devices, which may be collectively called "micro-ECoG" arrays, are loosely defined as intercranial devices that record brain electrical activity on the sub-millimeter scale. An extensible 3D-platform of thin film flexible micro-scale ECoG arrays appropriate for Brain-Computer Interface (BCI) application, as well as monitoring epileptic activity, is presented. The designs utilize flexible film electrodes to keep the array in place without applying significant pressure to the brain and to enable radial subcranial deployment of multiple electrodes from a single craniotomy. Deployment techniques were tested in non-human primates, and stimulus-evoked activity and spontaneous epileptic activity were recorded. Further tests in BCI and epilepsy applications will make the electrode platform ready for initial human testing.
Using General-purpose Graphic Processing Units for BCI Systems
BioMEMS electrode array fabrication techniques are used to develop high-density arrays with hundreds of channels. However, it was previously impossible to process more than a fraction of these channels real-time for online BCI experiments due to computational resource restraints. It is now possible to use graphics processing units (GPUs), which can have several hundred processing cores each, to processes large amounts of data quickly. This paper summarizes advances in using GPUs for BCI processing for EEG, ECoG, and micro-electrode systems, with speedups of more than 30 times that of current state-of-the-art CPU-based BCI implementations.
