neurofeedback therapy for enhancing visual attention: state-of-the-art and challenges

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2016
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Abstract
We have witnessed a rapid development of brain-computer interfaces (BCIs) linking the brain to external devices. BCIs can be utilized to treat neurological conditions and even to augment brain functions. BCIs offer a promising treatment for mental disorders, including disorders of attention. Here we review the current state of the art and challenges of attention-based BCIs, with a focus on visual attention. Attention-based BCIs utilize electroencephalograms (EEGs) or other recording techniques to generate neurofeedback, which patients use to improve their attention, a complex cognitive function. Although progress has been made in the studies of neural mechanisms of attention, extraction of attention-related neural signals needed for BCI operations is a difficult problem. To attain good BCI performance, it is important to select the features of neural activity that represent attentional signals. BCI decoding of attention-related activity may be hindered by the presence of different neural signals. Therefore, BCI accuracy can be improved by signal processing algorithms that dissociate signals of interest from irrelevant activities. Notwithstanding recent progress, optimal processing of attentional neural signals remains a fundamental challenge for the development of efficient therapies for disorders of attention.
Reference Key
ordikhani-seyedlar2016frontiersneurofeedback Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Mehdi Ordikhani-Seyedlar;Mikhail A. Lebedev;Mikhail A. Lebedev;Helge B.D. Sorensen;Sadasivan Puthusserypady
Journal Journal of enzyme inhibition and medicinal chemistry
Year 2016
DOI 10.3389/fnins.2016.00352
URL
http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00352/full
Keywords
visual attention feature extraction ssvep electroencephalography (eeg) brain-computer interface (bci) neuropsychiatry biological psychiatry erps (event-related potentials)neurosciences

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