Author

Lynn Le

Radboud University Nijmegen

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

Biology Disciplines

Click to filter author papers

Neuroscience· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Organism:non-human primate· 1 Approach:statistical model· 1

Frequent Co-Authors

Marcel A. J. van GerveniD· 3 shared Umut GüçlüiD· 3 shared Yağmur GüçlütürkiD· 3 shared Thirza DadoiD· 2 shared Antonio LozanoiD· 1 shared Feng WangiD· 1 shared Katja SeeligeriD· 1 shared Luca AmbrogioniiD· 1 shared

Activity by Year

2022-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersNeuroscience

Marcel A. J. van GervenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

PAM: Predictive attention mechanism for neural decoding of visual perception

Thirza Dado, Lynn Le, Marcel A. J. van Gerven, Yağmur Güçlütürk, Umut Güçlü

This paper introduces PAM, a predictive attention mechanism for neural decoding of visual perception, achieving state-of-the-art reconstructions and providing interpretative insights through attention weights and values.

bioRxiv · Jun 4, 2024 · PreprintNeuroscience

Brain2GAN: Feature-disentangled neural encoding and decoding of visual perception in the primate brain

Thirza Dado, Paolo Papale, Antonio Lozano, Lynn Le, Feng Wang, Marcel A. J. van Gerven, Pieter R. Roelfsema, Yağmur Güçlütürk, Umut Güçlü

This paper shows that feature-disentangled GAN latents better predict neural responses to visual stimuli than other representations, and can reconstruct visual perception with high fidelity.

PLoS Computational Biology · May 6, 2024Peer-reviewedNeuroscience

Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity

Lynn Le, Luca Ambrogioni, Katja Seeliger, Yağmur Güçlütürk, Marcel A. J. van Gerven, Umut Güçlü

The paper introduces Brain2Pix, a method to reconstruct naturalistic videos from brain activity using fully convolutional networks and retinotopic mappings, showing significant improvement over existing techniques.

Frontiers in Neuroscience · Nov 14, 2022Peer-reviewedNeuroscience