Author

Ekaterina Dobryakova

Kessler FoundationORCID 0000-0002-6005-2115Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 7 Organism:human· 5 Assay:imaging· 5 Research Focus:benchmarking· 4 Research Focus:cell-cell communication· 2 Research Focus:differential expression· 2 Research Focus:database / resource· 1 Approach:experimental assay· 1

Frequent Co-Authors

Joshua D. SandryiD· 3 shared Alexander OlseniD· 2 shared Andrei Irimia AiD· 2 shared Bharat B. BiswaliD· 2 shared Hannah Michelle LindseyiD· 2 shared Helen M. GenovaiD· 2 shared Karen CaeyenberghsiD· 2 shared Kristen Dams-O’ConnoriD· 2 shared

Activity by Year

2020-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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3 shared papersNeuroscience

Joshua D. SandryORCID

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Author profile →

7 papers

Recent·Most cited

Resting-state Functional Connections with the Hippocampus and with the Caudate Nucleus Predict Working Memory Performance in Multiple Sclerosis

Christopher J. Cagna, Ekaterina Dobryakova, Kai Sucich, Tien T. Tong, Joshua D. Sandry

The paper examines resting-state functional connectivity (RSFC) between the hippocampus and caudate nucleus in MS patients and healthy controls to predict working memory performance.

Multiple Sclerosis and Related Disorders · Aug 16, 2026Peer-reviewedNeuroscience

Accelerated Aging after Traumatic Brain Injury: an ENIGMA Multi-Cohort Mega-Analysis

Emily L. Dennis, Samantha M. Vervoordt, Maheen M. Adamson, Houshang Amiri, Erin D. Bigler, Karen Caeyenberghs, James Howard Cole, Kristen Dams-O’Connor, Evelyn M. Deutscher, Ekaterina Dobryakova, Helen M. Genova, Jordan Henry Grafman, Asta Kristine Haberg, Torgeir Hellstrøm, Andrei Irimia A, , Frank Gerard Hillary

This study examines how brain-age differences (PAD) change over time after traumatic brain injury (TBI) using a large multi-cohort dataset.

Annals of Neurology · Jun 7, 2024Peer-reviewedNeuroscience

Bypassing Striatal Learning Mechanisms Using Delayed Feedback to Circumvent Learning Deficits in TBI

Ekaterina Dobryakova, Tien T. Tong, Olesya Iosipchuk, Anthony H. Lequerica, Veronica Schneider, Nancy D. Chiaravalloti, Joshua D. Sandry

This study investigates how delayed feedback affects learning in individuals with traumatic brain injury (TBI) and identifies brain regions associated with delayed feedback processing.

bioRxiv · Dec 27, 2023 · PreprintNeuroscience

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium

Eamonn Kennedy, Shashank Vadlamani, Hannah Michelle Lindsey, Pui‐Wa Lei, Mary Jo Pugh, Maheen M. Adamson, Martin Alda, Sílvia Alonso-Lana, Sonia Ambrogi, Tim Anderson, Celso Arango, Robert F. Asarnow, Mihai Avram, Rosa Ayesa‐Arriola, Talin Babikian, , Marise B. Parent

The paper demonstrates a data harmonization process for memory testing across 53 studies, reducing inter-site variance while preserving covariate effects.

bioRxiv · Jan 16, 2023 · PreprintNeuroscience

ALFF Response Interaction With Learning During Feedback in Individuals With Multiple Sclerosis

Ekaterina Dobryakova, Rakibul Hafiz, Olesya Iosipchuk, Joshua D. Sandry, Bharat B. Biswal

The paper examines the relationship between ALFF and learning through feedback in individuals with multiple sclerosis, finding differences in brain activation patterns compared to healthy participants.

Multiple Sclerosis and Related Disorders · Jan 6, 2023Peer-reviewedNeuroscience

Reward Enhances Connectivity between the Ventral Striatum and the Default Mode Network

Ekaterina Dobryakova, David Victor Smith

The paper investigates how reward affects connectivity between the default mode network and the ventral striatum during a task, finding it correlates with personality openness.

NeuroImage · Jun 17, 2022Peer-reviewedNeuroscience

Variability in the analysis of a single neuroimaging dataset by many teams

Rotem Botvinik‐Nezer, Felix Holzmeister, Colin F. Camerer, Anna Dreber, Jürgen Huber, Magnus Johannesson, Michael Kirchler, Roni Iwanir, Jeanette A. Mumford, R. Alison Adcock, Paolo Avesani, Błażej M. Bączkowski, Aahana Bajracharya, Leah Bakst, Sheryl B. Ball, , Xiangzhen Kong

The paper shows that different analysis workflows by 70 teams on the same fMRI dataset led to varied results, but meta-analysis found consensus in activated regions.

Nature · May 20, 2020Peer-reviewedNeuroscience