Author

Loïc Cousin

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

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Organism:human· 3 Research Focus:drug response / drug discovery· 2 Approach:experimental assay· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Johannes H. WilbertziD· 3 shared Peter SommeriD· 3 shared Amélie Weiss· 2 shared Arnaud OgieriD· 2 shared Aurore VuideliD· 2 shared David Hoffmann· 2 shared Karen SchmittiD· 2 shared Alexandra BenchouaiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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3 shared papersNeuroscience

Johannes H. WilbertzORCID

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3 papers

Recent·Most cited

Morphological profiling reveals neuroprotection via mitochondrial uncoupling in human dopaminergic neurons

Vyron A. Gorgogietas, Amélie Weiss, Loïc Cousin, David Hoffmann, Karen Schmitt, Arnaud Ogier, Peter A. Barbuti, Bruno F. R. Santos, Ibrahim Boussaad, Annika Wittich, Andrea Zaliani, Ole Pleß, Rejko Krüger, Peter Sommer, Johannes H. Wilbertz

The paper identifies compounds that restore morphology in Parkinson's disease neurons by targeting mitochondrial uncoupling.

Scientific Reports · Aug 12, 2025Peer-reviewedNeuroscience

Pharmacological modulation of developmental and synaptic phenotypes in human SHANK3 deficient stem cell-derived neuronal models

Amandine Thibaudeau, Karen Schmitt, Louise François, Laure Chatrousse, David Hoffmann, Loïc Cousin, Amélie Weiss, Aurore Vuidel, Christina B. Jacob, Peter Sommer, Alexandra Benchoua, Johannes H. Wilbertz

This study screens small molecules in SHANK3-deficient neuronal models to identify compounds that rescue developmental and synaptic defects in Phelan-McDermid syndrome.

Translational Psychiatry · Jun 10, 2024Peer-reviewedNeuroscience

Machine learning-aided multidimensional phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons

Aurore Vuidel, Loïc Cousin, Beatrice Weykopf, Simone Haupt, Zahra Hanifehlou, Nicolas Wiest-Daesslé, Michaela Segschneider, Michael Peitz, Arnaud Ogier, Laurent Brino, Oliver Brüstle, Peter Sommer, Johannes H. Wilbertz

The paper uses machine learning to classify Parkinson's disease patient-derived midbrain dopaminergic neurons based on multiple image-based phenotypes and identifies treatable targets.

bioRxiv · Mar 1, 2022 · PreprintNeuroscience