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Address: 3 Krivokolenny Pereulok, room 3-316
ORCID: 0000-0002-6040-2154
Scopus AuthorID: 57214074688
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A. Ossadtchi
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Daria Kleeva

  • Daria Kleeva has been at HSE University since 2020.


Processing of MEG/EEG data

Awards and Accomplishments

Winner of the HSE University Best Russian Research Paper Competition – 2023

Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Researchers" (2022-2023)

Postgraduate Studies

3rd year of study
Approved topic of thesis: Estimation of functional connectivity from MEG/EEG data and anatomical priors
Academic Supervisor: Ossadtchi, Alexey

Courses (2023/2024)

Courses (2022/2023)

Courses (2021/2022)


Timetable for today

Full timetable

Our article was published in the NeuroImage!

The article "PSIICOS projection optimality for EEG and MEG based functional coupling detection" was published in the journal NeuroImage.

Authors: Dmitrii Altukhov, Daria Kleeva, Alexei Ossadtchi.

Congratulations to Dariya Kleeva on winning the Contest of the best Russian-language scientific and popular science papers of the National Research University Higher School of Economics in the direction of "Psychology" !

Early-Career HSE Researchers to Attend Neuroscience School

Two of the winners, Konstantin Sorokin, doctoral student and visiting lecturer of the HSE Faculty of Computer Science and research assistant at the HSE International Laboratory of Algebraic Topology and its Applications, and Daria Kleeva, doctoral student of the HSE Faculty of Social Sciences and research assistant at the HSE Institute of Cognitive Neuroscience Centre for Bioelectric Interfaces, spoke to the HSE News Service about why attending the School matters so much for them.

Russian Scientists Create Biomimetic Algorithm to Find Epileptogenic Areas of the Brain

Researchers from the HSE University Centre for Bioelectric Interfaces have designed a new method for detecting diagnostic markers of epilepsy, called interictal spikes, using EEG and MEG. Capable of accounting for various errors and artefacts, this method constitutes a valuable addition to the arsenal of means for automatic analysis of electrophysiological recordings in epilepsy patients, especially when the data are noisy. Precise localisation of epileptogenic cortical structures can enhance the effectiveness of neurosurgical interventions. The study was published in the Journal of Neural Engineering.