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Neural prosthetics

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https://www.readbyqxmd.com/read/28060708/characterization-and-decoding-the-spatial-patterns-of-hand-extension-flexion-using-high-density-ecog
#1
Tianxiao Jiang, Tao Jiang, Taylor Wang, Shanshan Mei, Qingzhu Liu, Yunlin Li, Xiaofei Wang, Sujit Prabhu, Zhiyi Sha, Nuri F Ince
During awake brain surgeries, electrocorticogram (ECoG) was recorded using a high density electrode grid from the motor cortex of two subjects while they were asked to execute spontaneous hand extension and flexion. Firstly, we characterized the spatio-spectral patterns of high-density ECoG during the hand movements. In both subjects, we observed event related desynchronization (ERD) in low frequency band (LFB:8-32Hz) and event related synchronization (ERS) in high frequency band (HFB:60-200Hz) where HFB-ERS was more spatially localized and movement specific compared to LFB-ERD...
January 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28018160/a-sliced-inverse-regression-sir-decoding-the-forelimb-movement-from-neuronal-spikes-in-the-rat-motor-cortex
#2
Shih-Hung Yang, You-Yin Chen, Sheng-Huang Lin, Lun-De Liao, Henry Horng-Shing Lu, Ching-Fu Wang, Po-Chuan Chen, Yu-Chun Lo, Thanh Dat Phan, Hsiang-Ya Chao, Hui-Ching Lin, Hsin-Yi Lai, Wei-Chen Huang
Several neural decoding algorithms have successfully converted brain signals into commands to control a computer cursor and prosthetic devices. A majority of decoding methods, such as population vector algorithms (PVA), optimal linear estimators (OLE), and neural networks (NN), are effective in predicting movement kinematics, including movement direction, speed and trajectory but usually require a large number of neurons to achieve desirable performance. This study proposed a novel decoding algorithm even with signals obtained from a smaller numbers of neurons...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27992344/brain-machine-interface-control-algorithms
#3
Maryam M Shanechi
Motor brain-machine interfaces (BMI) allow subjects to control external devices by modulating their neural activity. BMIs record the neural activity, use a mathematical algorithm to estimate the subject's intended movement, actuate an external device, and provide visual feedback of the generated movement to the subject. A critical component of a BMI system is the control algorithm, termed decoder. Significant progress has been made in the design of BMI decoders in recent years resulting in proficient control in non-human primates and humans...
December 14, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27927962/selective-neuronal-activation-by-cochlear-implant-stimulation-in-auditory-cortex-of-awake-primate
#4
Luke A Johnson, Charles C Della Santina, Xiaoqin Wang
: Despite the success of cochlear implants (CIs) in human populations, most users perform poorly in noisy environments and music and tonal language perception. How CI devices engage the brain at the single neuron level has remained largely unknown, in particular in the primate brain. By comparing neuronal responses with acoustic and CI stimulation in marmoset monkeys unilaterally implanted with a CI electrode array, we discovered that CI stimulation was surprisingly ineffective at activating many neurons in auditory cortex, particularly in the hemisphere ipsilateral to the CI...
December 7, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27915125/artificial-neural-networks-as-a-powerful-numerical-tool-to-classify-specific-features-of-a-tooth-based-on-3d-scan-data
#5
Stefan Raith, Eric Per Vogel, Naeema Anees, Christine Keul, Jan-Frederik Güth, Daniel Edelhoff, Horst Fischer
Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image data of dental surfaces. Artificial Neural Networks (ANNs) arenumerical methods primarily used to mimic the complex networks of neural connections in the natural brain. Our hypothesis is that an ANNcan be developed that is capable of classifying dental cusps with sufficient accuracy...
November 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27833537/forward-prediction-in-the-posterior-parietal-cortex-and-dynamic-brain-machine-interface
#6
He Cui
While remarkable progress has been made in brain-machine interfaces (BMIs) over the past two decades, it is still difficult to utilize neural signals to drive artificial actuators to produce predictive movements in response to dynamic stimuli. In contrast to naturalistic limb movements largely based on forward planning, brain-controlled neuroprosthetics mainly rely on feedback without prior trajectory formation. As an important sensorimotor interface integrating multisensory inputs and efference copy, the posterior parietal cortex (PPC) might play a proactive role in predictive motor control...
2016: Frontiers in Integrative Neuroscience
https://www.readbyqxmd.com/read/27780207/visual-bold-response-in-late-blind-subjects-with-argus-ii-retinal-prosthesis
#7
E Castaldi, G M Cicchini, L Cinelli, L Biagi, S Rizzo, M C Morrone
Retinal prosthesis technologies require that the visual system downstream of the retinal circuitry be capable of transmitting and elaborating visual signals. We studied the capability of plastic remodeling in late blind subjects implanted with the Argus II Retinal Prosthesis with psychophysics and functional MRI (fMRI). After surgery, six out of seven retinitis pigmentosa (RP) blind subjects were able to detect high-contrast stimuli using the prosthetic implant. However, direction discrimination to contrast modulated stimuli remained at chance level in all of them...
October 2016: PLoS Biology
https://www.readbyqxmd.com/read/27760395/carbon-nanotube-electrodes-for-retinal-implants-a-study-of-structural-and-functional-integration-over-time
#8
Cyril G Eleftheriou, Jonas B Zimmermann, Henrik D Kjeldsen, Moshe David-Pur, Yael Hanein, Evelyne Sernagor
The choice of electrode material is of paramount importance in neural prosthetic devices. Electrodes must be biocompatible yet able to sustain repetitive current injections in a highly corrosive environment. We explored the suitability of carbon nanotube (CNT) electrodes to stimulate retinal ganglion cells (RGCs) in a mouse model of outer retinal degeneration. We investigated morphological changes at the bio-hybrid interface and changes in RGC responses to electrical stimulation following prolonged in vitro coupling to CNT electrodes...
January 2017: Biomaterials
https://www.readbyqxmd.com/read/27669264/a-wireless-32-channel-implantable-bidirectional-brain-machine-interface
#9
Yi Su, Sudhamayee Routhu, Kee S Moon, Sung Q Lee, WooSub Youm, Yusuf Ozturk
All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex...
2016: Sensors
https://www.readbyqxmd.com/read/27619326/maze-learning-by-a-hybrid-brain-computer-system
#10
Zhaohui Wu, Nenggan Zheng, Shaowu Zhang, Xiaoxiang Zheng, Liqiang Gao, Lijuan Su
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity...
2016: Scientific Reports
https://www.readbyqxmd.com/read/27590967/multisession-noninvasive-closed-loop-neuroprosthetic-control-of-grasping-by-upper-limb-amputees
#11
H A Agashe, A Y Paek, J L Contreras-Vidal
Upper limb amputation results in a severe reduction in the quality of life of affected individuals due to their inability to easily perform activities of daily living. Brain-machine interfaces (BMIs) that translate grasping intent from the brain's neural activity into prosthetic control may increase the level of natural control currently available in myoelectric prostheses. Current BMI techniques demonstrate accurate arm position and single degree-of-freedom grasp control but are invasive and require daily recalibration...
2016: Progress in Brain Research
https://www.readbyqxmd.com/read/27581624/combining-two-open-source-tools-for-neural-computation-biopatrec-and-netlab-improves-movement-classification-for-prosthetic-control
#12
Cosima Prahm, Korbinian Eckstein, Max Ortiz-Catalan, Georg Dorffner, Eugenijus Kaniusas, Oskar C Aszmann
BACKGROUND: Controlling a myoelectric prosthesis for upper limbs is increasingly challenging for the user as more electrodes and joints become available. Motion classification based on pattern recognition with a multi-electrode array allows multiple joints to be controlled simultaneously. Previous pattern recognition studies are difficult to compare, because individual research groups use their own data sets. To resolve this shortcoming and to facilitate comparisons, open access data sets were analysed using components of BioPatRec and Netlab pattern recognition models...
August 31, 2016: BMC Research Notes
https://www.readbyqxmd.com/read/27539560/brain-computer-interfaces-for-communication-and-rehabilitation
#13
REVIEW
Ujwal Chaudhary, Niels Birbaumer, Ander Ramos-Murguialday
Brain-computer interfaces (BCIs) use brain activity to control external devices, thereby enabling severely disabled patients to interact with the environment. A variety of invasive and noninvasive techniques for controlling BCIs have been explored, most notably EEG, and more recently, near-infrared spectroscopy. Assistive BCIs are designed to enable paralyzed patients to communicate or control external robotic devices, such as prosthetics; rehabilitative BCIs are designed to facilitate recovery of neural function...
September 2016: Nature Reviews. Neurology
https://www.readbyqxmd.com/read/27510732/electrical-identification-and-selective-microstimulation-of-neuronal-compartments-based-on-features-of-extracellular-action-potentials
#14
Milos Radivojevic, David Jäckel, Michael Altermatt, Jan Müller, Vijay Viswam, Andreas Hierlemann, Douglas J Bakkum
A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation...
2016: Scientific Reports
https://www.readbyqxmd.com/read/27484713/neural-speech-recognition-continuous-phoneme-decoding-using-spatiotemporal-representations-of-human-cortical-activity
#15
David A Moses, Nima Mesgarani, Matthew K Leonard, Edward F Chang
OBJECTIVE: The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography...
October 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27457752/autonomous-control-for-mechanically-stable-navigation-of-microscale-implants-in-brain-tissue-to-record-neural-activity
#16
Sindhu Anand, Swathy Sampath Kumar, Jit Muthuswamy
Emerging neural prosthetics require precise positional tuning and stable interfaces with single neurons for optimal function over a lifetime. In this study, we report an autonomous control to precisely navigate microscale electrodes in soft, viscoelastic brain tissue without visual feedback. The autonomous control optimizes signal-to-noise ratio (SNR) of single neuronal recordings in viscoelastic brain tissue while maintaining quasi-static mechanical stress conditions to improve stability of the implant-tissue interface...
August 2016: Biomedical Microdevices
https://www.readbyqxmd.com/read/27456271/neuroprosthetics-and-the-science-of-patient-input
#17
REVIEW
Heather L Benz, Eugene F Civillico
Safe and effective neuroprosthetic systems are of great interest to both DARPA and CDRH, due to their innovative nature and their potential to aid severely disabled populations. By expanding what is possible in human-device interaction, these devices introduce new potential benefits and risks. Therefore patient input, which is increasingly important in weighing benefits and risks, is particularly relevant for this class of devices. FDA has been a significant contributor to an ongoing stakeholder conversation about the inclusion of the patient voice, working collaboratively to create a new framework for a patient-centered approach to medical device development...
January 2017: Experimental Neurology
https://www.readbyqxmd.com/read/27445672/in-vivo-characterization-of-amorphous-silicon-carbide-as-a-biomaterial-for-chronic-neural-interfaces
#18
Gretchen L Knaack, Daniel G McHail, German Borda, Beomseo Koo, Nathalia Peixoto, Stuart F Cogan, Theodore C Dumas, Joseph J Pancrazio
Implantable microelectrode arrays (MEAs) offer clinical promise for prosthetic devices by enabling restoration of communication and control of artificial limbs. While proof-of-concept recordings from MEAs have been promising, work in animal models demonstrates that the obtained signals degrade over time. Both material robustness and tissue response are acknowledged to have a role in device lifetime. Amorphous Silicon carbide (a-SiC), a robust material that is corrosion resistant, has emerged as an alternative encapsulation layer for implantable devices...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27445663/intracortical-brain-machine-interfaces-advance-sensorimotor-neuroscience
#19
REVIEW
Karen E Schroeder, Cynthia A Chestek
Brain-machine interfaces (BMIs) decode brain activity to control external devices. Over the past two decades, the BMI community has grown tremendously and reached some impressive milestones, including the first human clinical trials using chronically implanted intracortical electrodes. It has also contributed experimental paradigms and important findings to basic neuroscience. In this review, we discuss neuroscience achievements stemming from BMI research, specifically that based upon upper limb prosthetic control with intracortical microelectrodes...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27445660/fascicular-topography-of-the-human-median-nerve-for-neuroprosthetic-surgery
#20
Ignacio Delgado-Martínez, Jordi Badia, Arán Pascual-Font, Alfonso Rodríguez-Baeza, Xavier Navarro
One of the most sought-after applications of neuroengineering is the communication between the arm and an artificial prosthetic device for the replacement of an amputated hand or the treatment of peripheral nerve injuries. For that, an electrode is placed around or inside the median nerve to serve as interface for recording and stimulation of nerve signals coming from the fascicles that innervate the muscles responsible for hand movements. Due to the lack of a standard procedure, the electrode implantation by the surgeon is strongly based on intuition, which may result in poor performance of the neuroprosthesis because of the suboptimal location of the neural interface...
2016: Frontiers in Neuroscience
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