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Found 4 papers, 2 papers with code
Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks
We develop an end-to-end pipeline to preprocess, train and evaluate calcium fluorescence signals, and a procedure to interpret the resulting deep learning models.
Synthesising Realistic Calcium Imaging Data of Neuronal Populations Using GAN
Calcium imaging has become a powerful and popular technique to monitor the activity of large populations of neurons in vivo.
Synthesising Realistic Calcium Traces of Neuronal Populations Using GAN
Here, we propose a Generative Adversarial Network (GAN) model to generate realistic calcium signals as seen in neuronal somata with calcium imaging.
Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships
When the exact density estimation with a parametric model is not possible, our Copula-GP model is still able to provide reasonable information estimates, close to the ground truth and comparable to those obtained with a neural network estimator.
