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Bci interface fmri

Rosaleena Mohanty, Anita M Sinha, Alexander B Remsik, Keith C Dodd, Brittany M Young, Tyler Jacobson, Matthew McMillan, Jaclyn Thoma, Hemali Advani, Veena A Nair, Theresa J Kang, Kristin Caldera, Dorothy F Edwards, Justin C Williams, Vivek Prabhakaran
Interventional therapy using brain-computer interface (BCI) technology has shown promise in facilitating motor recovery in stroke survivors; however, the impact of this form of intervention on functional networks outside of the motor network specifically is not well-understood. Here, we investigated resting-state functional connectivity (rs-FC) in stroke participants undergoing BCI therapy across stages, namely pre- and post-intervention, to identify discriminative functional changes using a machine learning classifier with the goal of categorizing participants into one of the two therapy stages...
2018: Frontiers in Neuroscience
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...
April 1, 2018: NeuroImage
Keith C Dodd, Veena A Nair, Vivek Prabhakaran
Following a stroke, the resulting lesion creates contralateral motor impairment and an interhemispheric imbalance involving hyperexcitability of the contralesional hemisphere. Neuronal reorganization may occur on both the ipsilesional and contralesional hemispheres during recovery to regain motor functionality and therefore bilateral activation for the hemiparetic side is often observed. Although ipsilesional hemispheric reorganization is traditionally thought to be most important for successful recovery, definitive conclusions into the role and importance of the contralesional motor cortex remain under debate...
2017: Frontiers in Human Neuroscience
N N Johnson, J Carey, B J Edelman, A Doud, A Grande, K Lakshminarayan, B He
OBJECTIVE: Combining repetitive transcranial magnetic stimulation (rTMS) with brain-computer interface (BCI) training can address motor impairment after stroke by down-regulating exaggerated inhibition from the contralesional hemisphere and encouraging ipsilesional activation. The objective was to evaluate the efficacy of combined rTMS  +  BCI, compared to sham rTMS  +  BCI, on motor recovery after stroke in subjects with lasting motor paresis. APPROACH: Three stroke subjects approximately one year post-stroke participated in three weeks of combined rTMS (real or sham) and BCI, followed by three weeks of BCI alone...
February 2018: Journal of Neural Engineering
Gopikrishna Deshpande, D Rangaprakash, Luke Oeding, Andrzej Cichocki, Xiaoping P Hu
A Brain-Computer Interface (BCI) is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG) has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI). On the other hand, BCIs based on functional magnetic resonance imaging (fMRI) are more accurate owing to its superior spatial resolution and sensitivity to underlying neuronal processes which are functionally localized...
2017: Frontiers in Neuroscience
Mohammadreza Abtahi, Amir Mohammad Amiri, Dennis Byrd, Kunal Mankodiya
As the number of people diagnosed with movement disorders is increasing, it becomes vital to design techniques that allow the better understanding of human brain in naturalistic settings. There are many brain imaging methods such as fMRI, SPECT, and MEG that provide the functional information of the brain. However, these techniques have some limitations including immobility, cost, and motion artifacts. One of the most emerging portable brain scanners available today is functional near-infrared spectroscopy (fNIRS)...
April 15, 2017: Healthcare (Basel, Switzerland)
Peter E Yoo, Sam E John, Shawna Farquharson, Jon O Cleary, Yan T Wong, Amanda Ng, Claire B Mulcahy, David B Grayden, Roger J Ordidge, Nicholas L Opie, Terence J O'Brien, Thomas J Oxley, Bradford A Moffat
Recent developments in accelerated imaging methods allow faster acquisition of high spatial resolution images. This could improve the applications of functional magnetic resonance imaging at 7 Tesla (7T-fMRI), such as neurosurgical planning and Brain Computer Interfaces (BCIs). However, increasing the spatial and temporal resolution will both lead to signal-to-noise ratio (SNR) losses due to decreased net magnetization per voxel and T1 -relaxation effect, respectively. This could potentially offset the SNR efficiency gains made with increasing temporal resolution...
January 1, 2018: NeuroImage
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...
April 2017: L'Encéphale
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...
February 2017: Journal of Neural Engineering
Mohit Rana, Andrew Q Varan, Anis Davoudi, Ronald A Cohen, Ranganatha Sitaram, Natalie C Ebner
Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age...
2016: Frontiers in Aging Neuroscience
Bettina Sorger, Tabea Kamp, Nikolaus Weiskopf, Judith Caroline Peters, Rainer Goebel
Brain-computer interfaces (BCIs) based on real-time functional magnetic resonance imaging (rtfMRI) are currently explored in the context of developing alternative (motor-independent) communication and control means for the severely disabled. In such BCI systems, the user encodes a particular intention (e.g., an answer to a question or an intended action) by evoking specific mental activity resulting in a distinct brain state that can be decoded from fMRI activation. One goal in this context is to increase the degrees of freedom in encoding different intentions, i...
September 19, 2016: Neuroscience
Teresa Sousa, Bruno Direito, João Lima, Carlos Ferreira, Urbano Nunes, Miguel Castelo-Branco
A major challenge in brain-computer interface (BCI) research is to increase the number of command classes and levels of control. BCI studies often use binary control level approaches (level 0 and 1 of brain activation for each class of control). Different classes may often be achieved but not different levels of activation for the same class. The increase in the number of levels of control in BCI applications may allow for larger efficiency in neurofeedback applications. In this work we test the hypothesis whether more than two modulation levels can be achieved in a single brain region, the hMT+/V5 complex...
2016: PloS One
A A Frolov, D Husek, A V Silchenko, Y Tintera, J Rydlo
With the use of functional MRI (fMRI), we studied the changes in brain hemodynamic activity of healthy subjects during motor imagery training with the use brain-computer interface (BCI), which is based on the recognition of EEG patterns of imagined movements. ANOVA dispersion analysis showed there are 14 areas of the brain where statistically sgnificant changes were registered. Detailed analysis of the activity in these areas before and after training (Student's and Mann-Whitney tests) reduced the amount of areas with significantly changed activity to five; these are Brodmann areas 44 and 45, insula, middle frontal gyrus, and anterior cingulate gyrus...
January 2016: Fiziologiia Cheloveka
Korhan Buyukturkoglu, Hans Roettgers, Jens Sommer, Mohit Rana, Leonie Dietzsch, Ezgi Belkis Arikan, Ralf Veit, Rahim Malekshahi, Tilo Kircher, Niels Birbaumer, Ranganatha Sitaram, Sergio Ruiz
INTRODUCTION: Obsessive-compulsive disorder (OCD) is a common and chronic condition that can have disabling effects throughout the patient's lifespan. Frequent symptoms among OCD patients include fear of contamination and washing compulsions. Several studies have shown a link between contamination fears, disgust over-reactivity, and insula activation in OCD. In concordance with the role of insula in disgust processing, new neural models based on neuroimaging studies suggest that abnormally high activations of insula could be implicated in OCD psychopathology, at least in the subgroup of patients with contamination fears and washing compulsions...
2015: PloS One
Catharina Zich, Stefan Debener, Cornelia Kranczioch, Martin G Bleichner, Ingmar Gutberlet, Maarten De Vos
Motor imagery (MI) combined with real-time electroencephalogram (EEG) feedback is a popular approach for steering brain-computer interfaces (BCI). MI BCI has been considered promising as add-on therapy to support motor recovery after stroke. Yet whether EEG neurofeedback indeed targets specific sensorimotor activation patterns cannot be unambiguously inferred from EEG alone. We combined MI EEG neurofeedback with concurrent and continuous functional magnetic resonance imaging (fMRI) to characterize the relationship between MI EEG neurofeedback and activation in cortical sensorimotor areas...
July 1, 2015: NeuroImage
A A Frolov, D Gusek, P D Bobrov, O A Mokienko, L A Chernikova, R N Konovalov
Studied are sources of brain activity contributing to EEG patterns which correspond to motor imagery. The accuracy of their classification determines the efficiency of brain-computer interface (BCI) allowing for controlling external technical devices directly by brain signals without involving muscle activity. Sources of brain activity are identified by Independent Component Analysis. Those independent components for which the BCI classification accuracy are at maximum are treated as relevant for motor imagery task...
May 2014: Fiziologiia Cheloveka
Sebastian Baecke, Ralf Lützkendorf, Johannes Mallow, Michael Luchtmann, Claus Tempelmann, Jörg Stadler, Johannes Bernarding
Real-time functional Magnetic Resonance Imaging (rtfMRI) is used mainly for neurofeedback or for brain-computer interfaces (BCI). But multi-site rtfMRI could in fact help in the application of new interactive paradigms such as the monitoring of mutual information flow or the controlling of objects in shared virtual environments. For that reason, a previously developed framework that provided an integrated control and data analysis of rtfMRI experiments was extended to enable multi-site rtfMRI. Important new components included a data exchange platform for analyzing the data of both MR scanners independently and/or jointly...
2015: Scientific Reports
Jacques Luauté, Dominique Morlet, Jérémie Mattout
The reestablishment of communication is one of the main goals for patients with disorders of consciousness (DOC). It is now established that many DOC patients retain the ability to process stimuli of varying complexity even in the absence of behavioural response. Motor impairment, fatigue, attention disorders might contribute to the difficulty of communication in this population. Brain-computer interfaces (BCI) might be helpful in restoring some communication ability in these patients. After a definition of the different disorders of consciousness that might benefit from BCI, brain markers able to detect cognitive processes and awareness in the absence of behavioural manifestation are described...
February 2015: Annals of Physical and Rehabilitation Medicine
Alyssa M Batula, Hasan Ayaz, Youngmoo E Kim
This work investigates the potential of a four-class motor-imagery-based brain-computer interface (BCI) using functional near-infrared spectroscopy (fNIRS). Four motor imagery tasks (right hand, left hand, right foot, and left foot tapping) were executed while motor cortex activity was recorded via fNIRS. Preliminary results from three participants suggest that this could be a viable BCI interface, with two subjects achieving 50% accuracy. fNIRS is a noninvasive, safe, portable, and affordable optical brain imaging technique used to monitor cortical hemodynamic changes...
2014: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Moses O Sokunbi, David E J Linden, Isabelle Habes, Stephen Johnston, Niklas Ihssen
Here we present a novel neurofeedback subsystem for the presentation of motivationally relevant visual feedback during the self-regulation of functional brain activation. Our "motivational neurofeedback" approach uses functional magnetic resonance imaging (fMRI) signals elicited by visual cues (pictures) and related to motivational processes such as craving or hunger. The visual feedback subsystem provides simultaneous feedback through these images as their size corresponds to the magnitude of fMRI signal change from a target brain area...
2014: Frontiers in Behavioral Neuroscience
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