3 citations · 5 across the 5 of their papers we have counts for
6 papers
Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos
Polina Turishcheva, Paul G. Fahey, Michaela Vystrčilová +22
Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural…
V1T: large-scale mouse V1 response prediction using a Vision Transformer
Bryan M. Li, Isabel M. Cornacchia, Nathalie L. Rochefort +1
Accurate predictive models of the visual cortex neural response to natural visual stimuli remain a challenge in computational neuroscience. In this work, we introduce V1T, a novel…
Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks
Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort +1
Understanding how activity in neural circuits reshapes following task learning could reveal fundamental mechanisms of learning. Thanks to the recent advances in neural imaging tech…
Synthesising Realistic Calcium Traces of Neuronal Populations Using GAN
Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort +1
Calcium imaging has become a powerful and popular technique to monitor the activity of large populations of neurons in vivo. However, for ethical considerations and despite recent…
Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships
Nina Kudryashova, Theoklitos Amvrosiadis, Nathalie Dupuy +2
One of the main challenges in current systems neuroscience is the analysis of high-dimensional neuronal and behavioral data that are characterized by different statistics and times…
High-fidelity multimode fibre-based endoscopy for deep-brain in vivo imaging
Sergey Turtaev, Ivo T. Leite, Tristan Altwegg-Boussac +3
Progress in neuroscience constantly relies on the development of new techniques to investigate the complex dynamics of neuronal networks. An ongoing challenge is to achieve minimal…