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Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on

Date 16-19 March 2005

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Displaying Results 1 - 25 of 191
  • Welcome

    Page(s): i
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  • Engineering in medicine and biology society

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  • Table of contents

    Page(s): iv - xix
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  • Implantable Biomimetic Electronics as a Neural Prosthesis for Lost Memory Function

    Page(s): 1
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    Dr. Berger will present results of a collaborative effort on the part of the University of Southern California, Wake Forest University, and the University of Kentucky to develop a nonlinear dynamic model of synaptic transmission in the hippocampus. The model is implemented in very large scale integrated (VLSI) circuitry for use as a neural prosthetic to replace damaged or dysfunctional brain tissue. The hippocampus is a region of the brain responsible for the formation of long-term memories, and frequently is damaged as a result of epilepsy, stroke, and Alzheimer's disease. The components of this multi-laboratory effort will be described, and include: (1) experimental study of neuron and neural network function - how does the hippocampus encode information?, (2) formulation of biologically realistic models of neural system dynamics - can that encoding process be described mathematically to predict how the hippocampus (or a region of the hippocampus) will respond to a particular event?, (3) microchip implementation of neural system models - can the mathematical model be realized as a set of electronic circuits to achieve rapid computational speed and miniaturization?, and (4) hybrid neuron-silicon interfaces - can electronic devices be "functionally connected" to neural tissue for bi-directional communication with the hippocampus?. By integrating solutions to these component problems, the team is realizing a microchip-based model of hippocampal nonlinear dynamics that can perform the same function as a removed, damaged hippocampal region. Through bi-directional communication with other neural tissue that normally provides the inputs and outputs to/from the damaged hippocampal area, the neural model can serve as a neural prosthesis. A proof-of-concept will be presented in which the CA3 region of the hippocampal slice is replaced by a microchip model of CA3 nonlinear dynamics. How the current work in brain slices is being extended to behaving animals also will be des- ribed View full abstract»

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  • Magnetic Resonance Based Ventricle System Classification by Multi-Species Genetic Algorithm

    Page(s): 2 - 5
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    Early detection of medical abnormalities is an essential component in the accurate diagnosis and treatment of disease and disability. Automatically isolating the structure of the brain's ventricle system has the potential to assist neurologists in identifying abnormalities such as tumors, hydrocephalus and damage due to stroke. In this paper we present a multi-species genetic algorithm for isolating the ventricle system from multiple layers of brain images produced by magnetic resonance imaging (MRI) technology. Significant research has been performed on automatic classification of brain components from MRI images. To the best of our knowledge, this is the first approach to utilize multi-species genetic algorithms as a means of classifying brain components from MRI scans whereby the genomes control vertical and horizontal edge detection and locality based information suppression. This method requires a simple set of input data to be used for training the genetic algorithm. The results illustrate an effective method for isolating a patient's ventricle system View full abstract»

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  • MRI Template and Atlas Toolbox for the C57BL/6J Mouse Brain

    Page(s): 6 - 8
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    In order to compare brain-imaging measurements from different subjects, brain-mapping algorithms are commonly used to register individual brain onto a standardized brain atlas. In this study, SPM99 was used to linearly and nonlinearly coregister a spatially standardized T2-weighted template of C57BL/6J to the atlas by Paxinos and Franklin (2001), local accuracy of between atlas and template was evaluated, and a toolbox was developed. This study provides a foundation for the region of interest analysis for mouse brain images View full abstract»

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  • Multislice Brain Mapping and Quantification of Perfusion MRI Data

    Page(s): 9 - 12
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    With the recent development, magnetic resonance imaging went beyond the anatomical and morphological imaging and gave information about physiological properties of the tissues. Anatomical images with high resolution could be get by MRI using a combination of rapid imaging techniques and bolus injection of extracellular contrast agents. Perfusion weighted MRI (PWI) has been used in clinical practices since 1989. The contrast agents cause a signal change and the change over time can be analyzed to evaluate important cerebral hemodynamics like, cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT). In this study, MATLAB software has been used for writing codes for both mathematical equations and graphical user interface. As well as perfusion maps, we aimed to develop an easy-to-use interface so that technicians could run the program on site in a few minutes. User can achieve all operations easily, see information about patient and study, review all MR images in cine-mode, learn the absolute values of the regions, change colormaps of the results and save results in different image formats. All results of 11 patients with different clinical presentations were compared with another commercial software and for these patients three different statistics tables of comparison were given View full abstract»

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  • A Projection Approach of Optical Topographic Maps to the Cortical Surface of the Brain Abstract:

    Page(s): 13 - 16
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    This research is aimed at integrating two-dimensional (2-D) optical topographic maps to anatomical magnetic resonance imaging (MRI) for 3-D functional brain mapping. The uniqueness of this approach is in mapping topographic maps to the cortex surface of the brain based on projections of the results obtained from the skull surface. MRI is known to provide information about the anatomical structure of the brain, while optical topography system (OTS) displays the changes in the cerebral blood flow in the form of a topographic image. The experiment is based on a repeated finger-tapping task using seven volunteers at Miami Children Hospital. The integration of both modalities reveal excellent prospects in localizing the activation that is seen by (OTS) on the 3D brain models constructed from MRI slices. This task demands the development of a computer program that will first identify the region on the 3-D head model from which the topographic image generated by OTS was taken. Second, the topographic images are registered to the 3-D head model. In order to validate our findings, a comparison is made between the fiducial markers (vitamin E) placed on the patients head during the MRI test to localize the probes location and an automated computer program that will detect the probes position. Using the brain extraction tool (BET), the warped topographic maps are then projected onto the cortex surface of the extracted brain. The proposed OTS-MRI integration is deemed an important field in the neuroscience, allowing investigation of a wide range of motor, sensory, and cognitive functions, as well as providing key information about anatomical structure of the brain View full abstract»

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  • Cerebral Hemodynamics Assessed by means of Transcranial Doppler and Near - Infrared Spectroscopy in Healthy Smokers and non-Smokers

    Page(s): 17 - 20
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    The assessment of cerebral vasomotor reactivity (VMR) is a valuable tool for the early detection of risk condition in healthy subjects and for the non-invasive bedside evaluation of patients. Typically, cerebral hemodynamics assessment is performed in correspondence of CO2 reactivity. We studied the VMR of a population of young healthy non-smokers (n=10, age 27 plusmn 4.1) and healthy smokers (n=4, age 28 plusmn 4.5) using a joint approach based on transcranial Doppler ultrasonography and near-infrared spectroscopy, to monitor cerebral blood flow velocity (CBFV) and concentrations of oxygenated (O2Hb) and reduced (CO2Hb) haemoglobin. VMR was induced by means of voluntary breath-holding (BH). We quantified VMR using the breath-holding index (BHI). Smokers BH duration was significantly lower than that of non-smokers (p < 10-4; their BHI did not significantly differ from that of non-smokers in terms of CBFV, but differed in terms of O2Hb and CO2Hb concentrations changes. Specifically, with respect to non-smokers, smokers presented a delayed VMR that took place only around 60% of the apnoea phase. This delayed response could reveal an impaired autoregulatory mechanism and could be a risk condition when the subjects need to compensate an abrupt change in the cerebral blood flow View full abstract»

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  • Significance tests for MEG response detection

    Page(s): 21 - 24
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    Magnetoencephalography (MEG) is a non-invasive neurophysiological technique with high temporal resolution. Nevertheless, low signal to noise ratio may hamper its fullest capability. Many confidence tests already exist to detect strong responses for signals corrupted by noise, and we have explored their use with experimentally obtained MEG signals. We find that the tests demonstrating the most power are the F-test and Rayleigh's phase coherence test. Due to the strongly non-Gaussian nature of the MEG noise, from both neural and external perspective, a signal which is purely noise often fails the marginal tests by exceeding the number of false positive allowed. A variation of the tests is suggested that ensures the average false positive for a large number of responses, excited at frequencies different than the frequency of interest, is below any desired threshold. This is implemented for the F-test, Rayleigh's phase coherence test, and the union of the two View full abstract»

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  • Topographic and energy analysis of resting MEG and photic stimulation responses in control subjects and patients with schizophrenia

    Page(s): 25 - 28
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    To investigate sequential changes in magnetoencephalograms (MEGs) during photic stimulation (PS), we performed a quantitative MEG analysis of the alpha band (related to stimulus frequency) in 19 schizophrenic patients and 18 gender- and age-matched control subjects. Photic stimulation was at an interval of 0.5 Hz, and the frequency band was from 8 to 10.5 Hz. In each session, the interval lasted ten seconds and was repeated ten times for each frequency. In the topographic study, we assessed the differences between the two groups under two conditions (i.e., during PS and inter-PS). During the stimulus, the absolute 8-10.5 Hz band energy of the patient group was higher at the posterior sites throughout the ten-second periods. We compared the energy intensity of each site based on international 10/20 derivation. The energy intensity in the schizophrenic patients was smaller than in the control subjects at each site. We observed a gender difference in the control subjects, but not in the schizophrenic ones. These results suggest that schizophrenic patients show fewer changes in alpha activity during the stimulus, and this continuity of posterior dominance may reflect hyperarousal, which counteracts any decrease in vigilance throughout the PS View full abstract»

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  • MEG Adaptive Noise Suppression using Fast LMS

    Page(s): 29 - 32
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    Magnetoencephalography (MEG) measures magnetic fields generated by electric currents in the brain, non-invasively and with millisecond temporal resolution. Typical signals are 10-13 T, so noise contamination due to external magnetic fields is a serious concern. Digital signal processing is typically required in addition to magnetic shielding. Using three reference channels, displaced from the head, to measure the noise, we apply adaptive filtering to subtract out estimates of the noise, via the block least-mean-square ("fast LMS") method. The algorithm is tested by its effects on the number and distribution of channels which have statistically significant signals (distinguishable from background noise at a specified false-positive rate). We show that fast LMS both increases the number significant channels and reduces the variance of false positives View full abstract»

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  • MEG Responses to Speech and Stimuli With Speechlike Modulations

    Page(s): 33 - 36
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    Acoustic signals can be decomposed into the product of an envelope and its fine structure. The envelope features are critical to speech recognition. Results from human behavioral and psychophysical experiments indicate that magnetoencephalography (MEG) responses can significantly phase-lock to the temporal envelope of an auditory stimulus, and speech comprehension is correlated with this phase locking. The goal of this study is to explore the properties of neural response to the speech and stimuli with complex temporal envelopes. Five auditory stimuli with the same envelope, generated from natural speech, and the same stimuli but with the envelope artificially sped up were presented to two subjects. Auditory evoked responses were recorded with a whole-head 160-channel MEG system. Independent component analysis (ICA), principle component analysis (PCA) and equivalent current dipole fitting were performed to separate and identify the neural sources (and artifacts). The result shows that the location, orientation, and strength of the neural sources are robust across all stimuli, with correlation between auditory responses and the temporal envelope of the stimuli. These results provide support for the premise that neurons in the auditory cortex are particularly sensitive to the envelope and can phase-lock to stimuli with complex temporal and spectrotemporal envelopes View full abstract»

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  • An Algorithm of Nonlinear Interpolation Segmentation Based on Distance Mask Applied to Human Brain 3D Reconstruction

    Page(s): 37 - 40
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    In medical sequence slices, ROI (region of interest) in image need to be extracted and to be 3D reconstructed. An algorithm of nonlinear image interpolation segmentation is proposed in this paper. The algorithm is based on the distance mask. It effectively processes the segmentation of human brain image in which the distribution of intensities overlap one another, and can quickly extract ROI. The experiment shows that perfect results can be obtained by using this algorithm. And this algorithm was successfully applied to the medical image 3D visualization system View full abstract»

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  • A Self-adaptive Brain Image Enhancement Algorithm Based on Wavelet Transform

    Page(s): 41 - 44
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    Taking account of the features of medical images and actual requirements, wavelet analysis and unsharp masking algorithm are combined to solve some problems, such as enhancement of noise and losing details, which appeared by using the common methods of image enhancement. Based on the features of wavelet different scale analysis, an algorithm which can get the self-adaptive threshold value is proposed in this paper. Processing the different scale images, it can enhance image. The experiment shows the method can effectively enhance the image details, preserve the image edge, and improve the visual effect of the image View full abstract»

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  • An Abnormal EEG Simulation Based on The Chay Model of An Excitable Neuron

    Page(s): 45 - 47
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    The work here presents an abnormal EEC simulation by using the electrophysiological model of the neuron. The spike wave and the multi-spike wave of the EEG morphology are reconstructed. The simulation model is derived from the Chay model, which describes the abnormal process in an excitable neuron via bifurcation. The abnormal process, that spiking can be transformed into bursting rapidly, can be observed in some disorder of the nerve system, such as epileptic seizure. The spike wave is simulated by step changes in the bifurcation parameter, which is proportion to the concentration of the intracellular calcium ions (|Ca|1 ). And, when the concentration of (|Ca|1 is sufficiently large, the multi-spike wave can also be reconstructed. The simulation work will be helpful to understand how the EEG morphology is formed from the microcosmic viewpoint View full abstract»

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  • Functional Changes in Sensorimotor Regions of the Brain Following Spinal Injury

    Page(s): 48 - 51
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    Neurorobotics has been successfully used as novel output pathway for patients with severe nerve damage including spinal injury. However, a spinal injury is also a brain injury and it is difficult to assess the mechanisms that allow the injured brain to control an external device such as a cursor on a computer screen. We have therefore been using a rat model of spinal cord injury to assess functional changes in the sensorimotor regions of the brain to spinal cord injury. Arrays of microelectrodes were chronically implanted into the sensorimotor region of the brain and used to monitor neuronal activity before and after spinal cord hemisection. Neurons were recorded while the animal performed a spontaneous reaching task. Population functions were generated to identify forepaw contact and the ability to accurately identify contact on a single trial basis was used as a measure of the ability of the neural circuits to code for sensorimotor motor output. Our data suggest that while there was a significant decrease in the response of these neurons to passive stimulation of their receptive fields after spinal lesion and microstimulation was no longer able to generate coordinated muscle contraction, the population function was able to predict paw contact during spontaneous reaching. Furthermore, the latency of the peak of the response for single trial contact was significantly earlier post-hemisection compared to pre-hemisection. These results are discussed in terms of how they relate to strategies used by the animal to compensate for the loss of passive sensory stimulation View full abstract»

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  • Recursive Segmentation of Minicolums Using Myelinated Bundles

    Page(s): 52 - 55
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    In this study we developed a new method for minicolumnar identification in brain images. We measure width of minicolumns by using myelinated bundles of axons. Using recursive spectral segmentation by Otsu thresholding we separate different parts of neocoretex and extract myelinated bundles. By tracing lines perpendicular to them we measure minicolumnar width. We also measure macrocolumnar width by minicolumnar clusters View full abstract»

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  • Processing of foot pressure images and display of an advanced clinical parameter PR in Diabetic Neuropathy

    Page(s): 56 - 59
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    In diabetic foot, sensation loss predisposes to skin ulceration which may result in amputation, the most feared complication. Therefore, understanding and detection of factors responsible for plantar ulceration and their measurement reproducibly is necessary to save the foot at risk. As peak foot pressure were not sufficiently sensitive, power ratio (PR), a new diagnostic parameter, by analysis of foot pressure distribution in standing and walking images of foot has been developed. PR is related to different levels of sensation loss in the diabetic foot algorithm is developed (in MATLAB) to automatically separate (crop) bitmap files of different foot sizes. Algorithm is also developed (in Visual C ++) to calculate PR of cropped images and display simultaneously PR of all foot sole areas. This display of PR simultaneously in all foot areas helps clinician to effectively discriminate between normal, early and advanced stages of diabetic neuropathic subjects and also in detecting foot sole areas at risk View full abstract»

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  • Large-Scale Neural Interface Technology: Directly Connecting the Brain To the Real World

    Page(s): 60
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    Electronic advances over the last two decades have enabled the development of large-scale neural interface technology. Thus we can now use multielectrode arrays to transmit information out of the brain to directly control computers and robotic devices. More recently we have developed multi-electrode stimulating arrays to input information directly into sensory system of the brain. Since these devices provide direct access to individual neural circuits, one can now study neural information processing with greater precision. This technology also enables a new generation of bidirectional neural prosthetic systems that may alleviate paralysis and other neurological diseases. Finally, we have demonstrated the ability to use simple brain interfaces to remotely guide rodents through inaccessible spaces in order to perform surveillance and sensory detection functions View full abstract»

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  • Engineering New Approaches to Rehabilitation

    Page(s): 61
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    The population in the industrialized world is aging rapidly. Modest growth in national economies coupled with rapidly increasing expenditures for medical goods and services have strained the health care budgets for most of the industrialized world. This means that there will be an increased emphasis on maintaining a productive, older workforce, and that there will be an advantage for health systems that can develop strategies to reduce disabilities, maintain individuals' function and control costs. While there is increased competition for resources from other disciplines, neurorehabilitation has a new set of tools that can begin to create the kind of scientific excitement and major clinical advances that we have seen in other fields. These include functional imaging, gene therapies, tissue engineering, biomechanical modeling, to name just a few. We also are seeing a new generation of investigators and clinicians emerging that are taking on the challenge of developing effective treatments for stroke, brain injury and spinal cord injury. Science is rapidly moving away from the "cottage industry" of the individual investigator working in an isolated laboratory to the collaborative, multidisciplinary model of "big science". To survive, neurorehabilitation must maintain the pace of scientific and clinical innovation while also retaining the essential elements of successful clinical interaction View full abstract»

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  • A Systems Approach for Real-Time Data Compression in Advanced Brain-Machine Interfaces

    Page(s): 62 - 65
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    Advanced array processing techniques are becoming an indispensable requirement for integrating the rapid developments in wireless high-density electronic interfaces to the central nervous system (CNS) with computational neuroscience. This work aims at describing a systems approach for data compression to enable real-time transmission of high volumes of neural data acquired by implantable microelectrode arrays to extra-cutaneous devices. We show that the tradeoff between transmission bit rate and processing complexity requires a smart coding mechanism to yield a fast and efficient neural interface capable of transmitting the information from the CNS in real-time without compromising issues of communication bandwidth and signal fidelity. The results presented demonstrate that on-chip coding offers tremendous savings in communication costs compared to raw data transmission for off-chip analysis. Performance illustrations and experimental neural data examples are described in details View full abstract»

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  • Neural-Ensemble Activity of Spinal Cord L1/L2 During Stepping in a Decerebrate Rat Preparation

    Page(s): 66 - 69
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    Interneuronal networks within the L1-L2 region of the spinal cord are intrinsically capable of coordinating the activation of multiple functional muscle groups as required for locomotion. This paper demonstrates the use of microelectrode arrays for mapping extracellular spike activity and local-field potentials in the lumbar spinal cord of rats. Locomotion was studied in acute decerebrate rats by stimulation of the mesencephalic locomotor region (MLR) to induce stepping. Neural-ensemble activity during stepping was correlated with electromyograms (EMG) from ankle flexors and extensors. To visualize the activity, spatiotemporal population maps were generated from the recorded step cycles. These results will shed light on the organization of locomotor pattern generating circuits and identify active regions for stimulation. In future studies, we will test patterned electrical stimulation of the identified hotspots in spinal-cord-transected rats. These efforts will be directed towards the development of a functional stimulator for locomotion in paralyzed patients View full abstract»

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  • High Frequency Stimulation Suppresses Compound Action Potentials In Vitro

    Page(s): 70 - 73
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    Deep brain stimulation (DBS), also known as high frequency stimulation (HFS), is a promising method for the therapeutic control of epilepsy; although, the way DBS affects neural elements close to the stimulating electrode remains an important question. Sinusoidal HFS (50 Hz) suppresses synaptic and non-synaptic cellular neural activity in several in vitro epilepsy models. Although, the effects of HFS on axonal conduction are not known. In the present study, we tested the hypothesis that HFS suppresses local axonal conduction in vitro. HFS was locally applied to either the CA1 pyramidale cell layer or the alvear axon field of rat hippocampal slices. Complete suppression was indicated by a 100% reduction in amplitude of the field potential for the duration of the HFS. The results show that sinusoidal HFS suppresses the alvear compound action potential (CAP) as well as the CA1 antidromic evoked potential (AEP). Suppression was dependent on HFS amplitude, while HFS frequency was found not to be statistically significant. HFS applied to the alveus was more effective in suppressing the CAP than HFS applied to the CA1 pyramidale cell layer. These data suggest that HFS can block not only cellular neural firing but also activity in the axons of these cells or axons of passage View full abstract»

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  • Predicting reach goal in a continuous workspace for command of a brain-controlled upper-limb neuroprosthesis

    Page(s): 74 - 77
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    A controller for an upper-limb functional electrical stimulation system could use intended reach goal to generate a set of stimulation patterns that would move the hand to the desired location via a reasonably naturalistic velocity profile. Although discrete classifiers have been successfully used to predict movement goal from a fixed number of possible reach locations using neural activity recorded during movement planning, practical implementation of this paradigm for use in upper-limb neuroprostheses requires the ability to predict a reach goal anywhere within a person's workspace. Using neural data collected from monkeys during brain-controlled movements of a virtual cursor and robotic arm, we evaluated how well the direction versus magnitude of the final movement goal could be predicted from varying lengths of neural data collected after the target appeared. Although a majority of the channels were significantly modulated with intended movement direction, only 10-20% showed any significant modulation related to the magnitude of the movement goal. We propose a method of trajectory generation that could use the more reliably encoded directional information in the neural activity to control both magnitude and direction of a goal oriented reaching movement View full abstract»

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