Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Kensuke eSekihara"'
Publikováno v:
Frontiers in Neurology, Vol 5 (2014)
The visual P300 brain computer interface (BCI), a popular system for EEG-based BCI, uses the P300 event-related potential to select an icon arranged in a flicker matrix. In earlier studies, we used green/blue luminance and chromatic changes in the P3
Externí odkaz:
https://doaj.org/article/6ec6a248cee84e54a9a455fecf748b8c
Autor:
Leighton B Hinkley, Kensuke eSekihara, Julia Parsons Owen, Kelly eWestlake, Nancy eByl, Srikantan eNagarajan
Publikováno v:
Frontiers in Neurology, Vol 4 (2013)
Resting-state imaging designs are powerful in modeling functional networks in movement disorders because they eliminate task performance related confounds. However, the most common metric for quantifying functional connectivity, i.e. bivariate magnit
Externí odkaz:
https://doaj.org/article/58be05e9533d4030a0525fac7fe03e5f
Publikováno v:
Frontiers in Neuroscience, Vol 6 (2012)
Uncovering brain activity from MEG data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources. Sparse reconstruction algorithms, such as Champagne, show great promise in that they provide foc
Externí odkaz:
https://doaj.org/article/c49217f620d0499ba8609e0645204c78
Publikováno v:
Frontiers in Neuroscience
Frontiers in Neuroscience, Vol 6 (2012)
Frontiers in Neuroscience, Vol 6 (2012)
Uncovering brain activity from magnetoencephalography (MEG) data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources. Sparse reconstruction algorithms, such as Champagne, show great promise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d3ba82a65ddff3be1e681cb1e83f3d5
https://pubmed.ncbi.nlm.nih.gov/23271990
https://pubmed.ncbi.nlm.nih.gov/23271990