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There has been an increase in research interest for brain-computer interface (BCI) technology as an alternate mode of communication and environmental control for the disabled, such as patients suffering from amyotrophic lateral sclerosis (ALS), brainstem stroke and spinal cord injury. Disabled patients with appropriate physical care and cognitive ability to(More)
Neurofeedback of functional magnetic resonance imaging (fMRI) can be used to acquire selective control over activation in circumscribed brain areas, potentially inducing behavioral changes, depending on the functional role of the targeted cortical sites. In the present study, we used fMRI-neurofeedback to train subjects to enhance regional activation in the(More)
The dopaminergic system is involved in reward encoding and reinforcement learning. Dopaminergic neurons from this system in the substantia nigra/ventral tegmental area complex (SN/VTA) fire in response to unexpected reinforcing cues. The goal of this study was to investigate whether individuals can gain voluntary control of SN/VTA activity, thereby(More)
Recent advances in functional magnetic resonance imaging (fMRI) data acquisition and processing techniques have made real-time fMRI (rtfMRI) of localized brain areas feasible, reliable and less susceptible to artefacts. Previous studies have shown that healthy subjects learn to control local brain activity with operant training by using rtfMRI-based(More)
In February of 2012, the first international conference on real time functional magnetic resonance imaging (rtfMRI) neurofeedback was held at the Swiss Federal Institute of Technology Zurich (ETHZ), Switzerland. This review summarizes progress in the field, introduces current debates, elucidates open questions, and offers viewpoints derived from the(More)
Functional near-infrared spectroscopy (NIRS) and functional magnetic resonance imaging (fMRI) are non-invasive methods for acquiring hemodynamic signals from the brain with the primary benefit of anatomical specificity of signals. Recently, there has been a surge of studies with NIRS and fMRI for the implementation of a brain-computer interface (BCI), for(More)
BACKGROUND A promising new approach to cognitive neuroscience based on real-time functional magnetic resonance imaging (rtfMRI) demonstrated that the learned regulation of the neurophysiological activity in circumscribed brain regions can be used as an independent variable to observe its effects on behavior. Here, for the first time, we investigated the(More)
Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available(More)
Functional magnetic resonance imaging (fMRI) has been limited by time-consuming data analysis and a low signal-to-noise ratio, impeding online analysis. Recent advances in acquisition techniques, computational power and algorithms increased the sensitivity and speed of fMRI significantly, making real-time analysis and display of fMRI data feasible. So far,(More)
Real-time functional magnetic resonance imaging (rtfMRI) is a novel technique that has allowed subjects to achieve self-regulation of circumscribed brain regions. Despite its anticipated therapeutic benefits, there is no report on successful application of this technique in psychiatric populations. The objectives of the present study were to train(More)