Author

Anna B. Rebreikina

Russian Academy of SciencesORCID 0000-0001-5714-2040Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Olga MartynovaiD· 3 shared Galina V. PortnovaiD· 2 shared Alexander Ledovsky· 1 shared Ekaterina V. LarionovaiD· 1 shared Gurgen A. SoghoyaniD· 1 shared Maxim NekrashevichiD· 1 shared Maxim SharaeviD· 1 shared Olga SysoevaiD· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 29 mutual co-author links

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3 shared papersNeuroscience

Olga MartynovaORCID

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3 papers

Recent·Most cited

NeuroscienceScientific ReportsPeer-reviewedMar 30, 2024

Electrophysiological signatures of spelling sensitivity development from primary school age to adulthood

Ekaterina V. Larionova, Anna B. Rebreikina, Olga Martynova

The paper examines how electrophysiological responses to spelling errors develop from childhood to adulthood, finding distinct ERP patterns in different age groups.

9 citationstop 4%

humanelectronic health records

𝕏 PostBluesky

NeuroscienceFrontiers in NeuroinformaticsPeer-reviewedDec 2, 2021

A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography (ALICE)

Gurgen A. Soghoyan, Alexander Ledovsky, Maxim Nekrashevich…·Maxim Sharaev

The paper introduces ALICE, a toolbox and crowdsourcing platform for automatic labeling of EEG independent components using machine learning and expert input.

32 citations

electronic health recordsmachine learning (classical)

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NeuroscienceApplied Neuropsychology ChildPeer-reviewedSep 24, 2021

The ages of zone of proximal development for retrospective time assessment and anticipation of time event

Galina V. Portnova, Anna B. Rebreikina, Olga Martynova

This study assesses children's ability to estimate and anticipate time intervals, finding that accuracy improves with age and is linked to attention and memory scores.

4 citations

humanstatistical model

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