N
Nikolay V. Manyakov
Researcher at Janssen Pharmaceutica
Publications - 77
Citations - 1551
Nikolay V. Manyakov is an academic researcher from Janssen Pharmaceutica. The author has contributed to research in topics: Brain–computer interface & Autism. The author has an hindex of 20, co-authored 72 publications receiving 1111 citations. Previous affiliations of Nikolay V. Manyakov include Katholieke Universiteit Leuven & Johnson & Johnson Pharmaceutical Research and Development.
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Journal ArticleDOI
Comparison of classification methods for P300 brain-computer interface on disabled subjects
TL;DR: Tests with a mind typing paradigm based on a P300 brain-computer interface on a group of amyotrophic lateral sclerosis, middle cerebral artery stroke, and subarachnoid hemorrhage patients, suffering from motor and speech disabilities, find that one type of linear classifier yielded a higher classification accuracy.
Journal ArticleDOI
Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-β-induced pathology
Jelle Praet,Nikolay V. Manyakov,Leacky Muchene,Zhenhua Mai,Zhenhua Mai,Vasilis Terzopoulos,Vasilis Terzopoulos,Steve De Backer,An Torremans,Pieter-Jan Guns,Tom Van De Casteele,Astrid Bottelbergs,Bianca Van Broeck,Jan Sijbers,Dirk Smeets,Dirk Smeets,Ziv Shkedy,Luc Bijnens,Darrel J. Pemberton,Mark E. Schmidt,Annemie Van der Linden,Marleen Verhoye +21 more
TL;DR: Using a newly developed platform to co-register the in vivo diffusion-weighted magnetic resonance imaging with multiple 3D histological stacks, high correlations between DK metrics and anti-Aβ antibody, glial fibrillary acidic protein, ionised calcium-binding adapter molecule 1 and myelin basic protein immunohistochemistry are found.
Journal ArticleDOI
Sampled sinusoidal stimulation profile and multichannel fuzzy logic classification for monitor-based phase-coded SSVEP brain–computer interfacing
Nikolay V. Manyakov,Nikolay Chumerin,Arne Robben,Adrien Combaz,Marijn van Vliet,Marc M. Van Hulle +5 more
TL;DR: New stimulation and decoding methods for electroencephalogram (EEG)-based BCIs that have targets flickering at the same frequency but with different phases are introduced and the superiority of the proposed decoding approach demonstrates the importance of preserving the circularity of the data during the decoding stage.
Journal ArticleDOI
Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
Faith Matcham,C Barattieri di San Pietro,Viola Bulgari,G de Girolamo,Richard Dobson,Hans Eriksson,Amos Folarin,Josep Maria Haro,Maximilian Kerz,Femke Lamers,Qingqin Li,Nikolay V. Manyakov,David C. Mohr,Inez Myin-Germeys,Vaibhav A. Narayan,Penninx Bwjh,Yatharth Ranjan,Z. Rashid,Aki Rintala,Sara Siddi,Sara Simblett,Til Wykes,Matthew Hotopf,Sonia Difrancesco,Katie M White,Alina Ivan,Ashley Polhemus,Jose Ferrao,Michiel Ringkjøbing-Elema,Francesco Nobilia,Wolfgang Viechtbauer,Sjaak Peelen,Zulqarnain Rashid,Janneke Boere,Nicholas Cummins,Nick Meyer +35 more
TL;DR: The RADAR-MDD study as mentioned in this paper is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona, where participants were asked to wear a wrist-worn activity tracker and download several apps onto their smartphones.
Proceedings ArticleDOI
Designing a brain-computer interface controlled video-game using consumer grade EEG hardware
Marijn van Vliet,Arne Robben,Nikolay Chumerin,Nikolay V. Manyakov,Adrien Combaz,Marc M. Van Hulle +5 more
TL;DR: This paper describes the first attempt to port a brain-computer interface (BCI), created in a research lab and running on expensive equipment, to consumer grade equipment, allowing one to reach a much broader audience and raise public awareness of this new technology.