Author

Gabriele M. T. D’Eleuterio

University of TorontoORCID 0000-0002-7747-8235Unclaimed 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· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Approach:simulation· 1

Frequent Co-Authors

Milad LankaranyiD· 3 shared David CromptoniD· 1 shared Edward M. BelloiD· 1 shared Frances K. SkinneriD· 1 shared Loïc J. Azzalini· 1 shared Matthew D. JohnsoniD· 1 shared Miloš R. PopovićiD· 1 shared Srikar Saradhi· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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3 shared papersNeuroscience

Milad LankaranyORCID

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3 papers

Recent·Most cited

Computational simulation reveals the critical role of spike-timing-dependent plasticity in synchrony

Yunqi Huang, Milad Lankarany, Gabriele M. T. D’Eleuterio

The paper uses computational simulations to show that spike-timing-dependent plasticity (STDP) regulates synchronization and desynchronization dynamics, resolving the synchronization/desynchronization conundrum.

bioRxiv · Sep 22, 2026 · PreprintNeuroscience

Model-Based Closed-Loop Control of Thalamic Deep Brain Stimulation

Yupeng Tian, Srikar Saradhi, Edward M. Bello, Matthew D. Johnson, Gabriele M. T. D’Eleuterio, Miloš R. Popović, Milad Lankarany

This paper proposes a model-based closed-loop DBS controller for essential tremor using EMG signals, showing it finds DBS frequencies that align with clinical studies.

Frontiers in Network Physiology · Apr 8, 2024Peer-reviewedNeuroscience

Adaptive Unscented Kalman Filter for Neuronal State and Parameter Estimation

Loïc J. Azzalini, David Crompton, Gabriele M. T. D’Eleuterio, Frances K. Skinner, Milad Lankarany

This paper introduces an adaptive unscented Kalman filter for neuronal state and parameter estimation, showing improved accuracy and robustness compared to standard variants.

Journal of Computational Neuroscience · Mar 1, 2023Peer-reviewedNeuroscience