Search Results for author: Arno Onken

Found 12 papers, 4 papers with code

Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks

no code implementations25 Nov 2021 Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken

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.

Building population models for large-scale neural recordings: opportunities and pitfalls

no code implementations3 Feb 2021 Cole Hurwitz, Nina Kudryashova, Arno Onken, Matthias H. Hennig

Modern recording technologies now enable simultaneous recording from large numbers of neurons.

Synthesising Realistic Calcium Imaging Data of Neuronal Populations Using GAN

1 code implementation1 Jan 2021 Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken

Calcium imaging has become a powerful and popular technique to monitor the activity of large populations of neurons in vivo.

CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of Neuronal Populations

1 code implementation6 Sep 2020 Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken

Calcium imaging has become a powerful and popular technique to monitor the activity of large populations of neurons in vivo.

Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships

no code implementations3 Aug 2020 Nina Kudryashova, Theoklitos Amvrosiadis, Nathalie Dupuy, Nathalie Rochefort, Arno Onken

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.

Density Estimation

Neural System Identification with Spike-triggered Non-negative Matrix Factorization

no code implementations12 Aug 2018 Shanshan Jia, Zhaofei Yu, Arno Onken, Yonghong Tian, Tiejun Huang, Jian. K. Liu

Furthermore, we show that STNMF can separate spikes of a ganglion cell into a few subsets of spikes where each subset is contributed by one presynaptic bipolar cell.

Synthesizing realistic neural population activity patterns using Generative Adversarial Networks

1 code implementation ICLR 2018 Manuel Molano-Mazon, Arno Onken, Eugenio Piasini, Stefano Panzeri

The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing.

Mixed vine copulas as joint models of spike counts and local field potentials

no code implementations NeurIPS 2016 Arno Onken, Stefano Panzeri

Our methods hold the promise to considerably improve statistical analysis of neural data recorded simultaneously at different scales.

Mutual Information Estimation

Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies

no code implementations NeurIPS 2009 Arno Onken, Steffen Grünewälder, Klaus Obermayer

The linear correlation coefficient is typically used to characterize and analyze dependencies of neural spike counts.

Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex

no code implementations NeurIPS 2008 Arno Onken, Steffen Grünewälder, Matthias Munk, Klaus Obermayer

Furthermore, copulas place a wide range of dependence structures at the disposal and can be used to analyze higher order interactions.

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