Author

Hedi Kebir

Charité – Universitätsmedizin Berlin

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Approach:simulation· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Andreas HeinziD· 3 shared Frauke NeesiD· 3 shared Günter SchumanniD· 3 shared Henrik WalteriD· 3 shared Nilakshi VaidyaiD· 3 shared Sylvane DesrivièresiD· 3 shared Tianye JiaiD· 3 shared Tobias BanaschewskiiD· 3 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersNeuroscience

Andreas HeinzORCID

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Author profile →

3 papers

Recent·Most cited

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness

Yunman Xia, Songjun Peng, Juergen Dukart, Chao Xie, Shitong Xiang, Spase Petkoski, Zilin Li, Joerg F. Hipp, Suresh D Muthukumaraswamy, Anna Forsyth, Tianye Jia, Nilakshi Vaidya, Tristram A. P. Lett, Liyi Qian, Xiao Chang, , Günter Schumann

The paper develops a digital twin brain model that simulates and manipulates functional brain networks to predict mental illness symptoms and responses to interventions.

bioRxiv · Mar 19, 2026 · PreprintNeuroscience

Generating Synthetic Task-based Brain Fingerprints for Population Neuroscience Using Deep Learning

Emin Serin, Kerstin Ritter, Günter Schumann, Tobias Banaschewski, André F. Marquand, Henrik Walter, Andreas Heinz, Markus Ralser, Sven Olaf Twardziok, Nilakshi Vaidya, Antoine Bernas, Marcel Jentsch, Esther Hitchen, Elli Polemiti, Hedi Kebir, , George Ogoh

The paper introduces DeepTaskGen, a deep learning method that generates synthetic task-based contrast maps from resting-state fMRI data, outperforming benchmarks and enabling biomarker development for cognitive tasks.

Communications Biology · Nov 14, 2025Peer-reviewedNeuroscience

Brain Diffusion Transformer for Personalized Neuroscience and Psychiatry

Rongquan Zhai, Yechen Hu, Liping Zheng, Shitong Xiang, Chao Xie, Lei Peng, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Rüdiger Brühl, Sylvane Desrivières, Herta Flor, Hugh Garavan, Penny Anne Gowland, Antoine Grigis, , Tianye Jia

The paper introduces Brain-DiT, a deep generative model for analyzing task-fMRI data, identifying cognitive regions and subgroups linked to psychiatric conditions like depression and alcohol abuse.

bioRxiv · Apr 12, 2025 · PreprintNeuroscience