Author

Sanne H.G. van der Ven

Radboud University NijmegenORCID 0000-0002-4761-0741Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:drug response / drug discovery· 2 Assay:electronic health records· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Nienke E. R. van BuereniD· 3 shared Roi Cohen KadoshiD· 3 shared Evelyn H. KroesbergeniD· 2 shared Francesco SellaiD· 1 shared James G. SheffieldiD· 1 shared Karin Roelofs AiD· 1 shared Michael A. OsborneiD· 1 shared Shachar HochmaniD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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3 shared papersNeuroscience

Nienke E. R. van BuerenORCID

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Author profile →

3 papers

Recent·Most cited

Human Neuronal Excitation/Inhibition Balance Explains and Predicts Neurostimulation Induced Learning Benefits

Nienke E. R. van Bueren, Sanne H.G. van der Ven, Shachar Hochman, Francesco Sella, Roi Cohen Kadosh

The paper examines how the excitation/inhibition (E/I) ratio influences the effectiveness of transcranial random noise stimulation (tRNS) on learning, showing that lower E/I predicts greater learning benefits from tRNS.

PLoS Biology · Aug 31, 2023Peer-reviewedNeuroscience

Predicting Math Ability using Working Memory, Number Sense, and Neurophysiology in Children and Adults

Nienke E. R. van Bueren, Sanne H.G. van der Ven, Karin Roelofs A, Roi Cohen Kadosh, Evelyn H. Kroesbergen

This study examines the relationship between resting-state beta oscillations, working memory, number sense, and mathematical ability in children and adults, finding no mediation but highlighting differences in aperiodic activity.

Brain Sciences · Apr 26, 2022Peer-reviewedNeuroscience

Personalized Closed-Loop Brain Stimulation for Effective Neurointervention Across Participants

Nienke E. R. van Bueren, Thomas L. Reed, Vu Nguyen, James G. Sheffield, Sanne H.G. van der Ven, Michael A. Osborne, Evelyn H. Kroesbergen, Roi Cohen Kadosh

This paper introduces personalized Bayesian optimization for neurointervention, showing it can effectively recommend stimulation parameters based on individual baseline abilities.

PLoS Computational Biology · Sep 9, 2021Peer-reviewedNeuroscience