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https://www.readbyqxmd.com/read/27934776/prediction-of-subjective-ratings-of-emotional-pictures-by-eeg-features
#1
Dennis J McFarland, Muhammad A Parvaz, William A Sarnacki, Rita Z Goldstein, Jonathan R Wolpaw
OBJECTIVE: Emotion dysregulation is an important aspect of many psychiatric disorders. Brain-computer interface (BCI) technology could be a powerful new approach to facilitating therapeutic self-regulation of emotions. One possible BCI method would be to provide stimulus-specific feedback based on subject-specific electroencephalographic (EEG) responses to emotion-eliciting stimuli. APPROACH: To assess the feasibility of this approach, we studied the relationships between emotional valence/arousal and three EEG features: amplitude of alpha activity over frontal cortex; amplitude of theta activity over frontal midline cortex; and the late positive potential over central and posterior mid-line areas...
December 9, 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27926827/decoding-hand-gestures-from-primary-somatosensory-cortex-using-high-density-ecog
#2
Mariana P Branco, Zachary V Freudenburg, Erik J Aarnoutse, Martin G Bleichner, Mariska J Vansteensel, Nick F Ramsey
Electrocorticography (ECoG) based Brain-Computer Interfaces (BCIs) have been proposed as a way to restore and replace motor function or communication in severely paralyzed people. To date, most motor-based BCIs have either focused on the sensorimotor cortex as a whole or on the primary motor cortex (M1) as a source of signals for this purpose. Still, target areas for BCI are not confined to M1, and more brain regions may provide suitable BCI control signals. A logical candidate is the primary somatosensory cortex (S1), which not only shares similar somatotopic organization to M1, but also has been suggested to have a role beyond sensory feedback during movement execution...
December 4, 2016: NeuroImage
https://www.readbyqxmd.com/read/27917107/the-berlin-brain-computer-interface-progress-beyond-communication-and-control
#3
REVIEW
Benjamin Blankertz, Laura Acqualagna, Sven Dähne, Stefan Haufe, Matthias Schultze-Kraft, Irene Sturm, Marija Ušćumlic, Markus A Wenzel, Gabriel Curio, Klaus-Robert Müller
The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27917105/eeg-negativity-in-fixations-used-for-gaze-based-control-toward-converting-intentions-into-actions-with-an-eye-brain-computer-interface
#4
Sergei L Shishkin, Yuri O Nuzhdin, Evgeny P Svirin, Alexander G Trofimov, Anastasia A Fedorova, Bogdan L Kozyrskiy, Boris M Velichkovsky
We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27915127/mindedit-a-p300-based-text-editor-for-mobile-devices
#5
Amr S Elsawy, Seif Eldawlatly, Mohamed Taher, Gamal M Aly
Practical application of Brain-Computer Interfaces (BCIs) requires that the whole BCI system be portable. The mobility of BCI systems involves two aspects: making the electroencephalography (EEG) recording devices portable, and developing software applications with low computational complexity to be able to run on low computational-power devices such as tablets and smartphones. This paper addresses the development of MindEdit; a P300-based text editor for Android-based devices. Given the limited resources of mobile devices and their limited computational power, a novel ensemble classifier is utilized that uses Principal Component Analysis (PCA) features to identify P300 evoked potentials from EEG recordings...
November 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27914171/clinical-feasibility-of-brain-computer-interface-based-on-steady-state-visual-evoked-potential-in-patients-with-locked-in-syndrome-case-studies
#6
Han-Jeong Hwang, Chang-Hee Han, Jeong-Hwan Lim, Yong-Wook Kim, Soo-In Choi, Kwang-Ok An, Jun-Hak Lee, Ho-Seung Cha, Seung Hyun Kim, Chang-Hwan Im
Although the feasibility of brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) has been extensively investigated, only a few studies have evaluated its clinical feasibility in patients with locked-in syndrome (LIS), who are the main targets of BCI technology. The main objective of this case report was to share our experiences of SSVEP-based BCI experiments involving five patients with LIS, thereby providing researchers with useful information that can potentially help them to design BCI experiments for patients with LIS...
December 3, 2016: Psychophysiology
https://www.readbyqxmd.com/read/27900953/feedback-control-policies-employed-by-people-using-intracortical-brain-computer-interfaces
#7
Francis R Willett, Chethan Pandarinath, Beata Jarosiewicz, Brian A Murphy, William D Memberg, Christine H Blabe, Jad Saab, Benjamin L Walter, Jennifer A Sweet, Jonathan P Miller, Jaimie M Henderson, Krishna V Shenoy, John D Simeral, Leigh R Hochberg, Robert F Kirsch, A Bolu Ajiboye
OBJECTIVE: When using an intracortical BCI (iBCI), users modulate their neural population activity to move an effector towards a target, stop accurately, and correct for movement errors. We call the rules that govern this modulation a 'feedback control policy'. A better understanding of these policies may inform the design of higher-performing neural decoders. APPROACH: We studied how three participants in the BrainGate2 pilot clinical trial used an iBCI to control a cursor in a 2D target acquisition task...
November 30, 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27900952/a-novel-deep-learning-approach-for-classification-of-eeg-motor-imagery-signals
#8
Yousef Rezaei Tabar, Ugur Halici
OBJECTIVE: Signal classification is an important issue in brain computer interface (BCI) systems. Deep learning approaches have been used successfully in many recent studies to learn features and classify different types of data. However, the number of studies that employ these approaches on BCI applications is very limited. In this study we aim to use deep learning methods to improve classification performance of EEG motor imagery signals. APPROACH: In this study we investigate convolutional neural networks (CNN) and stacked autoencoders (SAE) to classify EEG Motor Imagery signals...
November 30, 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27900950/automated-selection-of-brain-regions-for-real-time-fmri-brain-computer-interfaces
#9
Michael Lührs, Bettina Sorger, Rainer Goebel, Fabrizio Esposito
OBJECTIVE: Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI...
November 30, 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27899774/-a-review-multigene-assays-for-clinical-utility-in-breast-cancer
#10
Kazuhiro Araki, Yoshinori Ito
Multigene assays that simultaneously measure the expression of various breast cancer genes have been developed to guide the use of adjuvant chemotherapy in early breast cancer. The efficacy of adjuvant therapies depends on the recurrence risk for an individual patient. As a result, accurate prediction of the recurrence risk is vital for precise adjuvant chemotherapy in individual breast cancer patients. The recurrence risk as typically assessed by conventional examination of histological data of immuno-histological biomarkers(ER, PR, HER2, and Ki-67)is not sufficient to select subsets of patients...
November 2016: Gan to Kagaku Ryoho. Cancer & Chemotherapy
https://www.readbyqxmd.com/read/27899311/seasonal-biotic-and-abiotic-factors-affecting-hunting-strategy-in-free-living-saharan-sand-vipers-cerastes-vipera
#11
Sefi J A Horesh, Jaim Sivan, Avi Rosenstrauch, Itay Tesler, A Allan Degen, Michael Kam
Sit-and-wait ambushing and active hunting are two strategies used by predators to capture prey. In snakes, hunting strategy is conserved phylogenetically; most species employ only one strategy. Active hunters encounter and capture more prey but invest more energy in hunting and have higher risks of being predated. This trade-off is important to small predators. The small Cerastes vipera employs both modes of hunting, which is unlike most viperids which use only sit-and wait ambushing. This species hibernates in October and emerges in April...
November 27, 2016: Behavioural Processes
https://www.readbyqxmd.com/read/27891199/robust-frequency-recognition-for-ssvep-based-bci-with-temporally-local-multivariate-synchronization-index
#12
Yangsong Zhang, Daqing Guo, Peng Xu, Yu Zhang, Dezhong Yao
Multivariate synchronization index (MSI) has been proved to be an efficient method for frequency recognition in SSVEP-BCI systems. It measures the correlation according to the entropy of the normalized eigenvalues of the covariance matrix of multichannel signals. In the MSI method, the estimation of covariance matrix omits the temporally local structure of samples. In this study, a new spatio-temporal method, termed temporally local MSI (TMSI), was presented. This new method explicitly exploits temporally local information in modelling the covariance matrix...
December 2016: Cognitive Neurodynamics
https://www.readbyqxmd.com/read/27891083/toward-a-p300-based-brain-computer-interface-for-aphasia-rehabilitation-after-stroke-presentation-of-theoretical-considerations-and-a-pilot-feasibility-study
#13
Sonja C Kleih, Lea Gottschalt, Eva Teichlein, Franz X Weilbach
People with post-stroke motor aphasia know what they would like to say but cannot express it through motor pathways due to disruption of cortical circuits. We present a theoretical background for our hypothesized connection between attention and aphasia rehabilitation and suggest why in this context, Brain-Computer Interface (BCI) use might be beneficial for patients diagnosed with aphasia. Not only could BCI technology provide a communication tool, it might support neuronal plasticity by activating language circuits and thereby boost aphasia recovery...
2016: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/27882256/eeg-triggered-functional-electrical-stimulation-therapy-for-restoring-upper-limb-function-in-chronic-stroke-with-severe-hemiplegia
#14
Cesar Marquez-Chin, Aaron Marquis, Milos R Popovic
We report the therapeutic effects of integrating brain-computer interfacing technology and functional electrical stimulation therapy to restore upper limb reaching movements in a 64-year-old man with severe left hemiplegia following a hemorrhagic stroke he sustained six years prior to this study. He completed 40 90-minute sessions of functional electrical stimulation therapy using a custom-made neuroprosthesis that facilitated 5 different reaching movements. During each session, the participant attempted to reach with his paralyzed arm repeatedly...
2016: Case Reports in Neurological Medicine
https://www.readbyqxmd.com/read/27881756/a-combinatorial-approach-to-angiosperm-pollen-morphology
#15
Luke Mander
Angiosperms (flowering plants) are strikingly diverse. This is clearly expressed in the morphology of their pollen grains, which are characterized by enormous variety in their shape and patterning. In this paper, I approach angiosperm pollen morphology from the perspective of enumerative combinatorics. This involves generating angiosperm pollen morphotypes by algorithmically combining character states and enumerating the results of these combinations. I use this approach to generate 3 643 200 pollen morphotypes, which I visualize using a parallel-coordinates plot...
November 30, 2016: Proceedings. Biological Sciences
https://www.readbyqxmd.com/read/27880768/real-time-control-of-an-articulatory-based-speech-synthesizer-for-brain-computer-interfaces
#16
Florent Bocquelet, Thomas Hueber, Laurent Girin, Christophe Savariaux, Blaise Yvert
Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI) controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligible speech in real-time with a reasonable number of control parameters. We present here an articulatory-based speech synthesizer that can be controlled in real-time for future BCI applications. This synthesizer converts movements of the main speech articulators (tongue, jaw, velum, and lips) into intelligible speech...
November 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/27875232/a-novel-algorithm-for-learning-sparse-spatio-spectral-patterns-for-event-related-potentials
#17
Chaohua Wu, Ke Lin, Wei Wu, Xiaorong Gao
Recent years have witnessed brain-computer interface (BCI) as a promising technology for integrating human intelligence and machine intelligence. Currently, event-related potential (ERP)-based BCI is an important branch of noninvasive electroencephalogram (EEG)-based BCIs. Extracting ERPs from a limited number of trials remains challenging due to their low signal-to-noise ratio (SNR) and low spatial resolution caused by volume conduction. In this paper, we propose a probabilistic model for trial-by-trial concatenated EEG, in which the concatenated ERPs are expressed as a linear combination of a set of discrete sine and cosine bases...
November 17, 2016: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/27875130/discriminative-ocular-artifact-correction-for-feature-learning-in-eeg-analysis
#18
Xinyang Li, Cuntai Guan, Haihong Zhang, Kai Keng Ang
Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for ICA-based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact...
November 16, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/27858227/plug-play-brain-computer-interfaces-for-effective-active-and-assisted-living-control
#19
Niccolò Mora, Ilaria De Munari, Paolo Ciampolini, José Del R Millán
Brain-Computer Interfaces (BCI) rely on the interpretation of brain activity to provide people with disabilities with an alternative/augmentative interaction path. In light of this, BCI could be considered as enabling technology in many fields, including Active and Assisted Living (AAL) systems control. Interaction barriers could be removed indeed, enabling user with severe motor impairments to gain control over a wide range of AAL features. In this paper, a cost-effective BCI solution, targeted (but not limited) to AAL system control is presented...
November 17, 2016: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/27857680/spiking-neural-networks-based-on-oxram-synapses-for-real-time-unsupervised-spike-sorting
#20
Thilo Werner, Elisa Vianello, Olivier Bichler, Daniele Garbin, Daniel Cattaert, Blaise Yvert, Barbara De Salvo, Luca Perniola
In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (<1μs) enables real-time spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes...
2016: Frontiers in Neuroscience
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