Andrey R Nikolaev

Dr. Andrey R Nikolaev


Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 1996 in Electroencephalography and Clinical Neurophysiology
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Journal Article
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AAAndrey Anokhin
Andrey Anokhin
NBNiels Birbaumer
Niels Birbaumer
WLWerner Lutzenberger
Werner Lutzenberger
ANAndrey R Nikolaev
Andrey R Nikolaev
FVFriedrich Vogel
Friedrich Vogel

1 August 2016 in Brain and Cognition
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Journal Article
Closed access
ANAndrey R Nikolaev
Andrey R Nikolaev
RMRadha Nila Meghanathan
Radha Nila Meghanathan
CLCees van Leeuwen
Cees van Leeuwen

1 June 2013 in NeuroImage
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Journal Article
Open access
DADavid M. Alexander
David M. Alexander
PJPeter Jurica
Peter Jurica
CTChris Trengove
Chris Trengove
ANAndrey R Nikolaev
Andrey R Nikolaev
SGSergei Gepshtein
Sergei Gepshtein
CLCees van Leeuwen
Cees van Leeuwen
Analyzing single trial brain activity remains a challenging problem in the neurosciences. We gain purchase on this problem by focusing on globally synchronous fields in within-trial evoked brain activity, rather than on localized peaks in the trial-averaged evoked response (ER). We analyzed data from three measurement modalities, each with different spatial resolutions: magnetoencephalogram (MEG), electroencephalogram (EEG) and electrocorticogram (ECoG). We first characterized the ER in terms of summation of phase and amplitude components over trials. Both contributed to the ER, as expected, but the ER topography was dominated by the phase component. This means the observed topography of cross-trial phase will not necessarily reflect the phase topography within trials. To assess the organization of within-trial phase, traveling wave (TW) components were quantified by computing the phase gradient. TWs were intermittent but ubiquitous in the within-trial evoked brain activity. At most task-relevant times and frequencies, the within-trial phase topography was described better by a TW than by the trial-average of phase. The trial-average of the TW components also reproduced the topography of the ER; we suggest that the ER topography arises, in large part, as an average over TW behaviors. These findings were consistent across the three measurement modalities. We conclude that, while phase is critical to understanding the topography of event-related activity, the preliminary step of collating cortical signals across trials can obscure the TW components in brain activity and lead to an underestimation of the coherent motion of cortical fields.

21 January 2015 in Frontiers in Human Neuroscience
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RMRadha Nila Meghanathan
Radha Nila Meghanathan
CLCees van Leeuwen
Cees van Leeuwen
ANAndrey R Nikolaev
Andrey R Nikolaev
Oculomotor behavior reveals, not only the acquisition of visual information at fixation, but also the accumulation of information in memory across subsequent fixations. Two candidate measures were considered as indicators of such dynamic visual memory load: fixation duration and pupil size. While recording these measures, we displayed an arrangement of 3, 4 or 5 targets among distractors. Both occurred in various orientations. Participants searched for targets and reported whether in a subsequent display one of them had changed orientation. We determined to what extent fixation duration and pupil size indicated dynamic memory load, as a function of the number of targets fixated during the search. We found that fixation duration reflects the number of targets, both when this number is within and above the limit of working memory capacity. Pupil size reflects the number of targets only when it exceeds the capacity limit. Moreover, the duration of fixations on successive targets but not on distractors increases whereas pupil size does not. The increase in fixation duration with number of targets both within and above working memory capacity suggests that in free viewing fixation duration is sensitive to actual memory load as well as to processing load, whereas pupil size is indicative of processing load only. Two alternative models relating visual attention and working memory are considered relevant to these results. We discuss the results as supportive of a model which involves a temporary buffer in the interaction of attention and working memory.

10 December 2004 in Biological Cybernetics
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Journal Article
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JIJunji Ito
Junji Ito
ANAndrey R Nikolaev
Andrey R Nikolaev
CLCees van Leeuwen
Cees van Leeuwen

21 February 2007 in Human Brain Mapping
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Journal Article
Closed access
JIJunji Ito
Junji Ito
ANAndrey R Nikolaev
Andrey R Nikolaev
CLCees van Leeuwen
Cees van Leeuwen