Benjamin Dunn
Benjamin Dunn
Department of Mathematics, NTNU
Dirección de correo verificada de - Página principal
Citado por
Citado por
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
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
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
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
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
Correlations and functional connections in a population of grid cells
B Dunn, M Mørreaunet, Y Roudi
PLoS computational biology 11 (2), e1004052, 2015
Multi-neuronal activity and functional connectivity in cell assemblies
Y Roudi, B Dunn, J Hertz
Current Opinion in Neurobiology 32, 38-44, 2015
Learning and inference in a nonequilibrium Ising model with hidden nodes
B Dunn, Y Roudi
Physical Review E 87 (2), 022127, 2013
Decoding of Neural Data Using Cohomological Feature Extraction
E Rybakken, N Baas, B Dunn
Neural Computation, 1-26, 2018
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
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
Action representation in the mouse parieto-frontal network
T Tombaz, BA Dunn, K Hovde, RJ Cubero, B Mimica, P Mamidanna, ...
Scientific Reports 10 (1), 1-14, 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
Score-Based Generative Classifiers
RS Zimmermann, L Schott, Y Song, BA Dunn, DA Klindt
arXiv preprint arXiv:2110.00473, 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
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
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results
A Myers, S Utpala, S Talbar, S Sanborn, C Shewmake, C Donnat, J Mathe, ...
Topological, Algebraic and Geometric Learning Workshops 2022, 269-276, 2022
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles
M Bjerke, L Schott, KT Jensen, C Battistin, DA Klindt, BA Dunn
arXiv preprint arXiv:2210.03155, 2022
Behavioral decomposition reveals rich encoding structure employed across neocortex
B Mimica, T Tombaz, C Battistin, JG Fuglstad, BA Dunn, JR Whitlock
bioRxiv, 2022
Functional reconstruction of a grid cell network
B Dunn
NTNU, 2016
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20