| Recurrent inhibitory circuitry as a mechanism for grid formation JJ Couey, A Witoelar, SJ Zhang, K Zheng, J Ye, B Dunn, R Czajkowski, ... Nature Neuroscience, 2013 | 464 | 2013 |
| Grid cells require excitatory drive from the hippocampus T Bonnevie, B Dunn, M Fyhn, T Hafting, D Derdikman, JL Kubie, Y Roudi, ... Nature Neuroscience, 2013 | 443 | 2013 |
| Toroidal topology of population activity in grid cells RJ Gardner, E Hermansen, M Pachitariu, Y Burak, NA Baas, BA Dunn, ... Nature 602 (7895), 123-128, 2022 | 285 | 2022 |
| Efficient cortical coding of 3D posture in freely behaving rats B Mimica, BA Dunn, T Tombaz, VS Bojja, JR Whitlock Science 362 (6414), 584-589, 2018 | 118 | 2018 |
| A Novel Mechanism for the Grid-to-Place Cell Transformation Revealed by Transgenic Depolarization of Medial Entorhinal Cortex Layer II BR Kanter, CM Lykken, D Avesar, A Weible, J Dickinson, B Dunn, ... Neuron 93 (6), 1480-1492. e6, 2017 | 116 | 2017 |
| Correlations and functional connections in a population of grid cells B Dunn, M Mørreaunet, Y Roudi PLoS computational biology 11 (2), e1004052, 2015 | 72 | 2015 |
| Decoding of Neural Data Using Cohomological Feature Extraction E Rybakken, N Baas, B Dunn Neural Computation, 1-26, 2018 | 65 | 2018 |
| Multi-neuronal activity and functional connectivity in cell assemblies Y Roudi, B Dunn, J Hertz Current Opinion in Neurobiology 32, 38-44, 2015 | 65 | 2015 |
| Learning and inference in a nonequilibrium Ising model with hidden nodes B Dunn, Y Roudi Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 87 (2 …, 2013 | 56 | 2013 |
| Score-based generative classifiers RS Zimmermann, L Schott, Y Song, BA Dunn, DA Klindt NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 2021 | 54 | 2021 |
| Grid cells show field-to-field variability and this explains the aperiodic response of inhibitory interneurons B Dunn, D Wennberg, Z Huang, Y Roudi arXiv preprint arXiv:1701.04893, 2017 | 28 | 2017 |
| Using persistent homology to reveal hidden covariates in systems governed by the kinetic ising model G Spreemann, B Dunn, MB Botnan, NA Baas Physical Review E 97 (3), 032313, 2018 | 25* | 2018 |
| Behavioral decomposition reveals rich encoding structure employed across neocortex in rats B Mimica, T Tombaz, C Battistin, JG Fuglstad, BA Dunn, JR Whitlock Nature Communications 14 (1), 3947, 2023 | 24* | 2023 |
| Action representation in the mouse parieto-frontal network T Tombaz, BA Dunn, K Hovde, RJ Cubero, B Mimica, P Mamidanna, ... Scientific reports 10 (1), 5559, 2020 | 19 | 2020 |
| Learning with unknowns: analyzing biological data in the presence of hidden variables C Battistin, B Dunn, Y Roudi Current Opinion in Systems Biology 1, 122-128, 2017 | 16 | 2017 |
| Insights into the quantification and reporting of model-related uncertainty across different disciplines EG Simmonds, KP Adjei, CW Andersen, JCH Aspheim, C Battistin, ... Iscience 25 (12), 2022 | 12* | 2022 |
| Uncovering 2-d toroidal representations in grid cell ensemble activity during 1-d behavior E Hermansen, DA Klindt, BA Dunn Nature Communications 15 (1), 5429, 2024 | 10 | 2024 |
| Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience D Gonschorek, L Höfling, KP Szatko, K Franke, T Schubert, B Dunn, ... Advances in Neural Information Processing Systems 34, 3706-3719, 2021 | 10 | 2021 |
| The appropriateness of ignorance in the inverse kinetic Ising model B Dunn, C Battistin Journal of Physics A: Mathematical and Theoretical 50 (12), 124002, 2017 | 9 | 2017 |
| Understanding neural coding on latent manifolds by sharing features and dividing ensembles M Bjerke, L Schott, KT Jensen, C Battistin, DA Klindt, BA Dunn The Eleventh International Conference on Learning Representations ICLR, 2023 | 5 | 2023 |
Yasser RoudiKing's College LondonVerified email at kcl.ac.uk
