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Brain-Computer interface

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https://www.readbyqxmd.com/read/29331233/a-biophysical-modelling-platform-of-the-cochlear-nucleus-and-other-auditory-circuits-from-channels-to-networks
#1
Paul B Manis, Luke Campagnola
Models of the auditory brainstem have been an invaluable tool for testing hypotheses about auditory information processing and for highlighting the most important gaps in the experimental literature. Due to the complexity of the auditory brainstem, and indeed most brain circuits, the dynamic behavior of the system may be difficult to predict without a detailed, biologically realistic computational model. Despite the sensitivity of models to their exact construction and parameters, most prior models of the cochlear nucleus have incorporated only a small subset of the known biological properties...
December 28, 2017: Hearing Research
https://www.readbyqxmd.com/read/29327652/acquisition-of-a-mental-strategy-to-control-a-virtual-tail-via-brain-computer-interface
#2
Ayaka Fujisawa, Shoko Kasuga, Takaharu Suzuki, Junichi Ushiba
The objective of the present study was to clarify the variation in and properties of mental images and policies used to regulate specific image selection when learning to control a brain-computer interface. Healthy volunteers performed a reaching task with a virtually generated monkey tail-like object on a computer monitor by regulating event-related desynchronization (ERD) on the buttock area of the sensorimotor cortex as recorded by electroencephalogram (EEG). Participants were instructed to find a free image by which the tail was well controlled...
January 12, 2018: Cognitive Neuroscience
https://www.readbyqxmd.com/read/29324784/multiscale-modelling-of-blood-flow-in-cerebral-microcirculation-details-at-capillary-scale-control-accuracy-at-the-level-of-the-cortex
#3
Myriam Peyrounette, Yohan Davit, Michel Quintard, Sylvie Lorthois
Aging or cerebral diseases may induce architectural modifications in human brain microvascular networks, such as capillary rarefaction. Such modifications limit blood and oxygen supply to the cortex, possibly resulting in energy failure and neuronal death. Modelling is key in understanding how these architectural modifications affect blood flow and mass transfers in such complex networks. However, the huge number of vessels in the human brain-tens of billions-prevents any modelling approach with an explicit architectural representation down to the scale of the capillaries...
2018: PloS One
https://www.readbyqxmd.com/read/29324403/performance-of-brain-computer-interfacing-based-on-tactile-selective-sensation-and-motor-imagery
#4
Lin Yao, Xinjun Sheng, Natalie Mrachacz-Kersting, Xiangyang Zhu, Dario Farina, Ning Jiang
A large proportion of users do not achieve adequate control using current non-invasive brain-computer interfaces (BCIs). This issue has being coined "BCI-Illiteracy" and is observed among different BCI modalities. Here, we compare the performance and the BCI-illiteracy rate of a tactile selective sensation (SS) and motor imagery (MI) BCI, for a large subject samples. We analyzed 80 experimental sessions from 57 subjects with two-class SS protocols. For SS, the group average performance was 79.8 ± 10.6%, with 43 out of the 57 subjects (75...
January 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29318256/brain-computer-interfaces-for-augmentative-and-alternative-communication-a-tutorial
#5
Jonathan S Brumberg, Kevin M Pitt, Alana Mantie-Kozlowski, Jeremy D Burnison
Purpose: Brain-computer interfaces (BCIs) have the potential to improve communication for people who require but are unable to use traditional augmentative and alternative communication (AAC) devices. As BCIs move toward clinical practice, speech-language pathologists (SLPs) will need to consider their appropriateness for AAC intervention. Method: This tutorial provides a background on BCI approaches to provide AAC specialists foundational knowledge necessary for clinical application of BCI...
January 9, 2018: American Journal of Speech-language Pathology
https://www.readbyqxmd.com/read/29298521/neural-correlates-of-phrase-quadrature-perception-in-harmonic-rhythm-an-eeg-study-using-a-brain-computer-interface
#6
Alicia Fernández-Sotos, Arturo Martínez-Rodrigo, José Moncho-Bogani, José Miguel Latorre, Antonio Fernández-Caballero
For the sake of establishing the neural correlates of phrase quadrature perception in harmonic rhythm, a musical experiment has been designed to induce music-evoked stimuli related to one important aspect of harmonic rhythm, namely the phrase quadrature. Brain activity is translated to action through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. The results of processing the acquired signals are in line with previous studies that use different musical parameters to induce emotions...
November 13, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29297303/an-improved-discriminative-filter-bank-selection-approach-for-motor-imagery-eeg-signal-classification-using-mutual-information
#7
Shiu Kumar, Alok Sharma, Tatsuhiko Tsunoda
BACKGROUND: Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. METHODS: In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks...
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29296627/single-session-communication-with-a-locked-in-patient-by-functional-near-infrared-spectroscopy
#8
Androu Abdalmalak, Daniel Milej, Loretta Norton, Derek B Debicki, Teneille Gofton, Mamadou Diop, Adrian M Owen, Keith St Lawrence
There is a growing interest in the possibility of using functional neuroimaging techniques to aid in detecting covert awareness in patients who are thought to be suffering from a disorder of consciousness. Immerging optical techniques such as time-resolved functional near-infrared spectroscopy (TR-fNIRS) are ideal for such applications due to their low-cost, portability, and enhanced sensitivity to brain activity. The aim of this case study was to investigate for the first time the ability of TR-fNIRS to detect command driven motor imagery (MI) activity in a functionally locked-in patient suffering from Guillain-Barré syndrome...
October 2017: Neurophotonics
https://www.readbyqxmd.com/read/29286458/surgical-training-for-the-implantation-of-neocortical-microelectrode-arrays-using-a-formaldehyde-fixed-human-cadaver-model
#9
Pierre Mégevand, Alain Woodtli, Aude Yulzari, G Rees Cosgrove, Shahan Momjian, Bojan V Stimec, Marco V Corniola, Jean H D Fasel
This protocol describes a procedure to assist surgeons in training for the implantation of microelectrode arrays into the neocortex of the human brain. Recent technological progress has enabled the fabrication of microelectrode arrays that allow recording the activity of multiple individual neurons in the neocortex of the human brain. These arrays have the potential to bring unique insight onto the neuronal correlates of cerebral function in health and disease. Furthermore, the identification and decoding of volitional neuronal activity opens the possibility to establish brain-computer interfaces, and thus might help restore lost neurological functions...
November 19, 2017: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/29283026/restoring-motor-functions-after-stroke-multiple-approaches-and-opportunities
#10
Estelle Raffin, Friedhelm C Hummel
More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impairment are a priority for stroke survivors and clinicians. While a significant body of evidence supports the use of conventional treatments, such as intensive motor training or constraint-induced movement therapy, the limited and heterogeneous improvements they allow are, for most patients, usually not sufficient to return to full autonomy...
November 1, 2017: Neuroscientist: a Review Journal Bringing Neurobiology, Neurology and Psychiatry
https://www.readbyqxmd.com/read/29282131/cybathlon-experiences-of-the-graz-bci-racing-team-mirage91-in-the-brain-computer-interface-discipline
#11
Karina Statthaler, Andreas Schwarz, David Steyrl, Reinmar Kobler, Maria Katharina Höller, Julia Brandstetter, Lea Hehenberger, Marvin Bigga, Gernot Müller-Putz
BACKGROUND: In this work, we share our experiences made at the world-wide first CYBATHLON, an event organized by the Eidgenössische Technische Hochschule Zürich (ETH Zürich), which took place in Zurich in October 2016. It is a championship for severely motor impaired people using assistive prototype devices to compete against each other. Our team, the Graz BCI Racing Team MIRAGE91 from Graz University of Technology, participated in the discipline "Brain-Computer Interface Race". A brain-computer interface (BCI) is a device facilitating control of applications via the user's thoughts...
December 28, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/29281985/deep-convolutional-neural-networks-for-pan-specific-peptide-mhc-class-i-binding-prediction
#12
Youngmahn Han, Dongsup Kim
BACKGROUND: Computational scanning of peptide candidates that bind to a specific major histocompatibility complex (MHC) can speed up the peptide-based vaccine development process and therefore various methods are being actively developed. Recently, machine-learning-based methods have generated successful results by training large amounts of experimental data. However, many machine learning-based methods are generally less sensitive in recognizing locally-clustered interactions, which can synergistically stabilize peptide binding...
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29281922/development-of-a-ternary-near-infrared-spectroscopy-brain-computer-interface-online-classification-of-verbal-fluency-task-stroop-task-and-rest
#13
Larissa C Schudlo, Tom Chau
The majority of proposed NIRS-BCIs has considered binary classification. Studies considering high-order classification problems have yielded average accuracies that are less than favorable for practical communication. Consequently, there is a paucity of evidence supporting online classification of more than two mental states using NIRS. We developed an online ternary NIRS-BCI that supports the verbal fluency task (VFT), Stroop task and rest. The system utilized two sessions dedicated solely to classifier training...
October 26, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29250108/convolutional-neural-networks-with-3d-input-for-p300-identification-in-auditory-brain-computer-interfaces
#14
Eduardo Carabez, Miho Sugi, Isao Nambu, Yasuhiro Wada
From allowing basic communication to move through an environment, several attempts are being made in the field of brain-computer interfaces (BCI) to assist people that somehow find it difficult or impossible to perform certain activities. Focusing on these people as potential users of BCI, we obtained electroencephalogram (EEG) readings from nine healthy subjects who were presented with auditory stimuli via earphones from six different virtual directions. We presented the stimuli following the oddball paradigm to elicit P300 waves within the subject's brain activity for later identification and classification using convolutional neural networks (CNN)...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/29249952/enhanced-motor-imagery-based-bci-performance-via-tactile-stimulation-on-unilateral-hand
#15
Xiaokang Shu, Lin Yao, Xinjun Sheng, Dingguo Zhang, Xiangyang Zhu
Brain-computer interface (BCI) has attracted great interests for its effectiveness in assisting disabled people. However, due to the poor BCI performance, this technique is still far from daily-life applications. One of critical issues confronting BCI research is how to enhance BCI performance. This study aimed at improving the motor imagery (MI) based BCI accuracy by integrating MI tasks with unilateral tactile stimulation (Uni-TS). The effects were tested on both healthy subjects and stroke patients in a controlled study...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/29249656/brain-computer-interface-with-inhibitory-neurons-reveals-subtype-specific-strategies
#16
Akinori Mitani, Mingyuan Dong, Takaki Komiyama
Brain-computer interfaces have seen an increase in popularity due to their potential for direct neuroprosthetic applications for amputees and disabled individuals. Supporting this promise, animals-including humans-can learn even arbitrary mapping between the activity of cortical neurons and movement of prosthetic devices [1-4]. However, the performance of neuroprosthetic device control has been nowhere near that of limb control in healthy individuals, presenting a dire need to improve the performance. One potential limitation is the fact that previous work has not distinguished diverse cell types in the neocortex, even though different cell types possess distinct functions in cortical computations [5-7] and likely distinct capacities to control brain-computer interfaces...
December 5, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/29247807/real-time-decoding-of-covert-attention-in-higher-order-visual-areas
#17
Jinendra Ekanayake, Chloe Hutton, Gerard Ridgway, Frank Scharnowski, Nikolaus Weiskopf, Geraint Rees
Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online 'winner-takes-all approach' with quadrant-specific parameter estimates, to achieve single-block classification of brain activations...
December 13, 2017: NeuroImage
https://www.readbyqxmd.com/read/29236504/atomristor-non-volatile-resistance-switching-in-atomic-sheets-of-transition-metal-dichalcogenides
#18
Ruijing Ge, Xiaohan Wu, Myungsoo Kim, Jianping Shi, Sushant Sudam Sonde, Li Tao, Yanfeng Zhang, Jack Lee, Deji Akinwande
Recently, two-dimensional (2D) atomic sheets have inspired new ideas in nanoscience including topologically-protected charge transport, spatially-separated excitons, and strongly anisotropic heat transport. Here, we report the intriguing observation of stable non-volatile resistance switching (NVRS) in single-layer atomic sheets sandwiched between metal electrodes. NVRS is observed in the prototypical semiconducting (MX2, M=Mo, W; and X=S, Se) transitional metal dichalcogenides (TMDs), which alludes to the universality of this phenomenon in TMD monolayers, and offers forming-free switching...
December 13, 2017: Nano Letters
https://www.readbyqxmd.com/read/29236042/single-channel-eeg-artifact-identification-using-two-dimensional-multi-resolution-analysis
#19
Mojtaba Taherisadr, Omid Dehzangi, Hossein Parsaei
As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components...
December 13, 2017: Sensors
https://www.readbyqxmd.com/read/29230171/spatial-temporal-feature-analysis-on-single-trial-event-related-potential-for-rapid-face-identification
#20
Lei Jiang, Yun Wang, Bangyu Cai, Yueming Wang, Yiwen Wang
The event-related potential (ERP) is the brain response measured in electroencephalography (EEG), which reflects the process of human cognitive activity. ERP has been introduced into brain computer interfaces (BCIs) to communicate the computer with the subject's intention. Due to the low signal-to-noise ratio of EEG, most ERP studies are based on grand-averaging over many trials. Recently single-trial ERP detection attracts more attention, which enables real time processing tasks as rapid face identification...
2017: Frontiers in Computational Neuroscience
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