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Proceedings Paper

Detecting neuronal activity from calcium imaging data using FRI methods (Conference Presentation)
Author(s): Stephanie Reynolds; Jon Oñativia; Simon R. Schultz; Pier Luigi Dragotti
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Paper 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.

Paper Details

Date Published: 26 September 2017
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Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940Z (26 September 2017); doi: 10.1117/12.2274043
Show Author Affiliations
Stephanie Reynolds, Imperial College London (United Kingdom)
Jon Oñativia, Imperial College London (United Kingdom)
Simon R. Schultz, Imperial College London (United Kingdom)
Pier Luigi Dragotti, Imperial College London (United Kingdom)


Published in SPIE Proceedings Vol. 10394:
Wavelets and Sparsity XVII
Yue M. Lu; Dimitri Van De Ville; Manos Papadakis, Editor(s)

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