Author

Tuomas Puoliväli

University of HelsinkiORCID 0000-0002-4820-0613Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Jaakko Matias PalvaiD· 2 shared Satu PalvaiD· 2 shared Anja ThiedeiD· 1 shared Asoke Kumar NandiiD· 1 shared Brigitte Bogert· 1 shared Elvira BratticoiD· 1 shared Felix SiebenhühneriD· 1 shared Lauri T. ParkkoneniD· 1 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersNeuroscience

Jaakko Matias PalvaORCID

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3 papers

Recent·Most cited

Musicianship can be decoded from magnetic resonance images

Tuomas Puoliväli, Tuomo Sipola, Anja Thiede, Marina Kliuchko, Brigitte Bogert, Petri Toiviainen, Asoke Kumar Nandi, Lauri T. Parkkonen, Elvira Brattico, Tapani Ristaniemi, Tiina M. Parviainen

The paper shows that musicianship can be predicted from brain structure MRI data using machine learning, achieving significant classification accuracy.

bioRxiv · Jul 19, 2020 · PreprintNeuroscience

Influence of multiple hypothesis testing on reproducibility in neuroimaging research

Tuomas Puoliväli, Satu Palva, Jaakko Matias Palva

This study evaluates methods for multiple hypothesis testing in neuroimaging to improve reproducibility, finding permutation testing is most powerful and prior knowledge grouping enhances results.

bioRxiv · Sep 11, 2019 · PreprintNeuroscience

Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses

Sheng Hua Wang, Muriel Lobier, Felix Siebenhühner, Tuomas Puoliväli, Satu Palva, Jaakko Matias Palva

This paper introduces hyperedge bundling to reduce spurious interactions in MEG/EEG source connectivity analyses, improving the accuracy of functional connectivity networks.

NeuroImage · Jan 31, 2018Peer-reviewedNeuroscience