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Brain-Computer interface

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https://www.readbyqxmd.com/read/28101424/detection-and-classification-of-three-class-initial-dips-from-prefrontal-cortex
#1
Amad Zafar, Keum-Shik Hong
In this paper, the use of initial dips using functional near-infrared spectroscopy (fNIRS) for brain-computer interface (BCI) is investigated. Features and window sizes for detecting initial dips are also discussed. Three mental tasks including mental arithmetic, mental counting, and puzzle solving are performed in obtaining fNIRS signals from the prefrontal cortex. Vector-based phase analysis method combined with a threshold circle, as a decision criterion, are used to detect the initial dips. Eight healthy subjects participate in experiment...
January 1, 2017: Biomedical Optics Express
https://www.readbyqxmd.com/read/28100828/an-integrated-modelling-framework-for-neural-circuits-with-multiple-neuromodulators
#2
Alok Joshi, Vahab Youssofzadeh, Vinith Vemana, T M McGinnity, Girijesh Prasad, KongFatt Wong-Lin
Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours...
January 2017: Journal of the Royal Society, Interface
https://www.readbyqxmd.com/read/28098561/decoding-of-intended-saccade-direction-in-an-oculomotor-brain-computer-interface
#3
Nan Jia, Scott Brincat, Andrés Salazar-Gómez, Mikhail Panko, Frank Guenther, Earl Miller
OBJECTIVE: To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from of hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system...
January 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28092565/a-passive-eeg-bci-for-single-trial-detection-of-changes-in-mental-state
#4
Andrew Myrden, Tom Chau
Traditional brain-computer interfaces often exhibit unstable performance over time. It has recently been proposed that passive brain-computer interfaces may provide a way to complement and stabilize these traditional systems. In this study, we investigated the feasibility of a passive brain-computer interface that uses electroencephalography to monitor changes in mental state on a single-trial basis. We recorded cortical activity from 15 locations while 11 able-bodied adults completed a series of challenging mental tasks...
January 9, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28091397/a-novel-stimulation-method-for-multi-class-ssvep-bci-using-intermodulation-frequencies
#5
Xiaogang Chen, Yijun Wang, Shangen Zhang, Shangkai Gao, Yong Hu, Xiaorong Gao
OBJECTIVE: Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has been widely investigated because of its easy system configuration, high information transfer rate (ITR) and little user training. However, due to the limitations of brain responses and the refresh rate of a monitor, the available stimulation frequencies for practical BCI application are generally restricted. APPROACH: This study introduced a novel stimulation method using intermodulation frequencies for SSVEP-BCIs that had targets flickering at the same frequency but with different additional modulation frequencies...
January 16, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28091395/a-novel-onset-detection-technique-for-brain-computer-interfaces-using-sound-production-related-cognitive-tasks-in-simulated-online-system
#6
YoungJae Song, Francisco Sepulveda
OBJECTIVE: Self-paced EEG-based BCIs (SP-BCIs) have traditionally been avoided due to two sources of uncertainty: (1) precisely when an intentional command is sent by the brain, i.e., the command onset detection problem, and (2) how different the intentional command is when compared to non-specific (or idle) states. Performance evaluation is also a problem and there are no suitable standard metrics available. In this paper we attempted to tackle these issues. APPROACH: Self-paced covert sound-production cognitive tasks (i...
February 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28087767/trial-by-trial-motor-cortical-correlates-of-a-rapidly-adapting-visuomotor-internal-model
#7
Sergey D Stavisky, Jonathan C Kao, Stephen I Ryu, Krishna V Shenoy
: Accurate motor control is mediated by internal models of how neural activity generates movement. We examined neural correlates of an adapting internal model of visuomotor gain in motor cortex while two macaques performed a reaching task in which the gain scaling between the hand and a presented cursor was varied. Previous studies of cortical changes during visuomotor adaptation focused on preparatory and peri-movement epochs and analyzed trial-averaged neural data. Here, we recorded simultaneous neural population activity using multielectrode arrays and focused our analysis on neural differences in the period before the target appeared...
January 13, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28086889/hybrid-brain-computer-interface-for-biomedical-cyber-physical-system-application-using-wireless-embedded-eeg-systems
#8
Rifai Chai, Ganesh R Naik, Sai Ho Ling, Hung T Nguyen
BACKGROUND: One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. METHODS: This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels...
January 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28071599/unsupervised-frequency-recognition-method-of-ssveps-using-a-filter-bank-implementation-of-binary-subband-cca
#9
Md Rabiul Islam, Md Molla, Masaki Nakanishi, Toshihisa Tanaka
OBJECTIVE: Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, as the number of commands increases. This paper develops a novel unsupervised method based on canonical correlation analysis (CCA) for accurate detection of stimulus frequency. APPROACH: A novel unsupervised technique termed as binary subband CCA (BsCCA) is implemented in a multiband approach to enhance the frequency recognition performance of SSVEP...
January 10, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28065938/efficient-implementation-of-a-real-time-estimation-system-for-thalamocortical-hidden-parkinsonian-properties
#10
Shuangming Yang, Bin Deng, Jiang Wang, Huiyan Li, Chen Liu, Chris Fietkiewicz, Kenneth A Loparo
Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization...
January 9, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28061886/circadian-course-of-the-p300-erp-in-patients-with-amyotrophic-lateral-sclerosis-implications-for-brain-computer-interfaces-bci
#11
Helena Erlbeck, Ursula Mochty, Andrea Kübler, Ruben G L Real
BACKGROUND: Accidents or neurodegenerative diseases like amyotrophic lateral sclerosis (ALS) can lead to progressing, extensive, and complete paralysis leaving patients aware but unable to communicate (locked-in state). Brain-computer interfaces (BCI) based on electroencephalography represent an important approach to establish communication with these patients. The most common BCI for communication rely on the P300, a positive deflection arising in response to rare events. To foster broader application of BCIs for restoring lost function, also for end-users with impaired vision, we explored whether there were specific time windows during the day in which a P300 driven BCI should be preferably applied...
January 7, 2017: BMC Neurology
https://www.readbyqxmd.com/read/28060906/steady-state-motion-visual-evoked-potential-ssmvep-based-on-equal-luminance-colored-enhancement
#12
Wenqiang Yan, Guanghua Xu, Min Li, Jun Xie, Chengcheng Han, Sicong Zhang, Ailing Luo, Chaoyang Chen
Steady-state visual evoked potential (SSVEP) is one of the typical stimulation paradigms of brain-computer interface (BCI). It has become a research approach to improve the performance of human-computer interaction, because of its advantages including multiple objectives, less recording electrodes for electroencephalogram (EEG) signals, and strong anti-interference capacity. Traditional SSVEP using light flicker stimulation may cause visual fatigue with a consequent reduction of recognition accuracy. To avoid the negative impacts on the brain response caused by prolonged strong visual stimulation for SSVEP, steady-state motion visual evoked potential (SSMVEP) stimulation method was used in this study by an equal-luminance colored ring-shaped checkerboard paradigm...
2017: PloS One
https://www.readbyqxmd.com/read/28057684/ismart-a-toolkit-for-a-comprehensive-analysis-of-small-rna-seq-data
#13
Riccardo Panero, Antonio Rinaldi, Domenico Memoli, Giovanni Nassa, Maria Ravo, Francesca Rizzo, Roberta Tarallo, Luciano Milanesi, Alessandro Weisz, Giorgio Giurato
: The interest in investigating the biological roles of small non-coding RNAs (sncRNAs) is increasing, due to the pleiotropic effects of these molecules exert in many biological contexts. While several methods and tools are available to study microRNAs (miRNAs), only few focus on novel classes of sncRNAs, in particular PIWI-interacting RNAs (piRNAs). To overcome these limitations, we implemented iSmaRT (integrative Small RNA Tool-kit), an automated pipeline to analyze smallRNA-Seq data...
January 5, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28055887/eeg-based-strategies-to-detect-motor-imagery-for-control-and-rehabilitation
#14
Kai Keng Ang, Cuntai Guan
Advances in Brain-Computer Interface (BCI) technology have facilitated the detection of Motor Imagery (MI) from electroencephalography (EEG). First, we present three strategies of using BCI to detect MI from EEG: operant conditioning that employed a fixed model, machine learning that employed a subject-specific model computed from calibration, and adaptive strategy that continuously compute the subjectspecific model. Second, we review prevailing works that employed the operant conditioning and machine learning strategies...
December 30, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28041692/neurofeedback-one-of-today-s-techniques-in-psychiatry
#15
M Arns, J-M Batail, S Bioulac, M Congedo, C Daudet, D Drapier, T Fovet, R Jardri, M Le-Van-Quyen, F Lotte, D Mehler, J-A Micoulaud-Franchi, D Purper-Ouakil, F Vialatte
OBJECTIVES: Neurofeedback is a technique that aims to teach a subject to regulate a brain parameter measured by a technical interface to modulate his/her related brain and cognitive activities. However, the use of neurofeedback as a therapeutic tool for psychiatric disorders remains controversial. The aim of this review is to summarize and to comment the level of evidence of electroencephalogram (EEG) neurofeedback and real-time functional magnetic resonance imaging (fMRI) neurofeedback for therapeutic application in psychiatry...
December 29, 2016: L'Encéphale
https://www.readbyqxmd.com/read/28028495/evaluation-of-a-low-cost-and-low-noise-active-dry-electrode-for-long-term-biopotential-recording
#16
Ali Pourahmad, Amin Mahnam
Wet Ag/AgCl electrodes, although very popular in clinical diagnosis, are not appropriate for expanding applications of wearable biopotential recording systems which are used repetitively and for a long time. Here, the development of a low-cost and low-noise active dry electrode is presented. The performance of the new electrodes was assessed for recording electrocardiogram (ECG) and electroencephalogram (EEG) in comparison with that of typical gel-based electrodes in a series of long-term recording experiments...
October 2016: Journal of Medical Signals and Sensors
https://www.readbyqxmd.com/read/28026782/a-hybrid-cmos-memristor-neuromorphic-synapse
#17
Mostafa Rahimi Azghadi, Bernabe Linares-Barranco, Derek Abbott, Philip H W Leong
Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics to realize a brain-inspired platform. This paper proposes a high-performance nano-scale Complementary Metal Oxide Semiconductor (CMOS)-memristive circuit, which mimics a number of essential learning properties of biological synapses. The proposed synaptic circuit that is composed of memristors and CMOS transistors, alters its memristance in response to timing differences among its pre- and post-synaptic action potentials, giving rise to a family of Spike Timing Dependent Plasticity (STDP)...
December 22, 2016: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/28026777/local-and-remote-cooperation-with-virtual-and-robotic-agents-a-p300-bci-study-in-healthy-and-people-living-with-spinal-cord-injury
#18
Emmanuele Tidoni, Mohammad Abu-Alqumsan, Daniele Leonardis, Christoph Kapeller, Gabriele Fusco, Christoph Guger, Cristoph Hintermueller, Angelika Peer, Antonio Frisoli, Franco Tecchia, Massimo Bergamasco, Salvatore M Aglioti
The development of technological applications that allow people to control and embody external devices within social interaction settings represents a major goal for current and future brain-computer interface (BCI) systems.
December 23, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28018162/a-bidirectional-brain-machine-interface-featuring-a-neuromorphic-hardware-decoder
#19
Fabio Boi, Timoleon Moraitis, Vito De Feo, Francesco Diotalevi, Chiara Bartolozzi, Giacomo Indiveri, Alessandro Vato
Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28012854/discriminative-spatial-frequency-temporal-feature-extraction-and-classification-of-motor-imagery-eeg-an-sparse-regression-and-weighted-na%C3%A3-ve-bayesian-classifier-based-approach
#20
Minmin Miao, Hong Zeng, Aimin Wang, Changsen Zhao, Feixiang Liu
BACKGROUND: Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. NEW METHOD: This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction...
December 21, 2016: Journal of Neuroscience Methods
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