Detecting neuronal activity from calcium imaging data using FRI methods (Conference Presentation)

Stephanie Reynolds; Jon Oñativia; Simon R. Schultz; Pier Luigi Dragotti

doi:10.1117/12.2274043

26 September 2017 Detecting neuronal activity from calcium imaging data using FRI methods (Conference Presentation)

Stephanie Reynolds, Jon Oñativia, Simon R. Schultz, Pier Luigi Dragotti

Proceedings Volume 10394, Wavelets and Sparsity XVII; 103940Z (2017) https://doi.org/10.1117/12.2274043
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

Two-photon calcium imaging can be used to monitor the activity of thousands of neurons across multiple brain areas at single-cell resolution. To harness the power of this imaging technology, neuroscientists require algorithms to detect from the imaging data the time points at which each neuron was active. We present an algorithm based on Finite Rate of Innovation (FRI) theory to detect neuronal spiking activity from this data. By exploiting the parametric structure of the signal, the activity detection problem can be reduced to the classic FRI problem of reconstructing a stream of Diracs.

Conference Presentation

Citation Download Citation

Stephanie Reynolds, Jon Oñativia, Simon R. Schultz, and Pier Luigi Dragotti "Detecting neuronal activity from calcium imaging data using FRI methods (Conference Presentation)", Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940Z (26 September 2017); https://doi.org/10.1117/12.2274043

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