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Alexei Ossadtchi

Researcher at National Research University – Higher School of Economics

Publications -  67
Citations -  2007

Alexei Ossadtchi is an academic researcher from National Research University – Higher School of Economics. The author has contributed to research in topics: Computer science & Decoding methods. The author has an hindex of 13, co-authored 57 publications receiving 1685 citations. Previous affiliations of Alexei Ossadtchi include University of Southern California & Russian Academy of Sciences.

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Reconstruction of Abel-transformable images: The Gaussian basis-set expansion Abel transform method

TL;DR: In this article, a method for reconstructing 3D images with cylindrical symmetry from their two-dimensional projections is presented, which is based on expanding the projection in a basis set of functions that are analytical projections of known well-behaved functions.
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MEG Signatures of a Perceived Match or Mismatch between Individual and Group Opinions

TL;DR: It is argued that distinct valuation and performance-monitoring neural circuits in the medial cortices of the brain may monitor compliance of individual behavior to the perceived group norms.
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Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Tomas Ros, +86 more
- 01 Jun 2020 - 
TL;DR: Over 80 neurofeedback researchers present a consensus-derived checklist – CRED-nf – for reporting and experimental design standards in the field.
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Local linear estimators for the bioelectromagnetic inverse problem

TL;DR: In this article, the authors show that the most widely used linear estimators may be characterized by a choice of norms on signal space and on source space, which depend, in part, on assumptions about the signal and source space covariances.
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Connectivity measures applied to human brain electrophysiological data

TL;DR: This work reviews both formal and informal descriptions of a range of connectivity measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography, and introduces a novel set of cross-time-frequency measures.