28 citations · 54 across the 4 of their papers we have counts for
5 papers
TRACE: Contrastive learning for multi-trial time-series data in neuroscience
Lisa Schmors, Dominic Gonschorek, Jan Niklas Böhm +9
Modern neural recording techniques such as two-photon imaging or Neuropixel probes allow to acquire vast time-series datasets with responses of hundreds or thousands of neurons. Co…
Learning From Brains How to Regularize Machines
Zhe Li, Wieland Brendel, Edgar Y. Walker +7
Despite impressive performance on numerous visual tasks, Convolutional Neural Networks (CNNs) --- unlike brains --- are often highly sensitive to small perturbations of their input…
A rotation-equivariant convolutional neural network model of primary visual cortex
Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis +7
Classical models describe primary visual cortex (V1) as a filter bank of orientation-selective linear-nonlinear (LN) or energy models, but these models fail to predict neural respo…
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
E. Kelly Buchanan, Ian Kinsella, Ding Zhou +17
Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large…
Supervised learning sets benchmark for robust spike detection from calcium imaging signals
Lucas Theis, Philipp Berens, Emmanouil Froudarakis +6
A fundamental challenge in calcium imaging has been to infer the timing of action potentials from the measured noisy calcium fluorescence traces. We systematically evaluate a range…