Robustness of spike deconvolution for calcium imaging of neural spiking.

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bioRxiv. 2017 Jun 27;:156786. doi: https://doi.org/10.1101/156786

Robustness of spike deconvolution for calcium imaging of neural spiking. Pachitariu Lab

Pachitariu M, Stringer C, Harris KD

Note: Research in this publication was not performed at Janelia.

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Abstract

Calcium imaging is a powerful method to record the activity of neural populations, but inferring spike times from calcium signals is a challenging problem. We compared multiple approaches using multiple datasets with ground truth electrophysiology, and found that simple non-negative deconvolution (NND) outperformed all other algorithms. We introduce a novel benchmark applicable to recordings without electrophysiological ground truth, based on the correlation of responses to two stimulus repeats, and used this to show that unconstrained NND also outperformed the other algorithms when run on 'zoomed out' datasets of ~10,000 cell recordings. Finally, we show that NND-based methods match the performance of a supervised method based on convolutional neural networks, while avoiding some of the biases of such methods, and at much faster running times. We therefore recommend that spikes be inferred from calcium traces using simple NND, due to its simplicity, efficiency and accuracy.

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Robustness of spike deconvolution for calcium imaging of neural spiking.

Note: Research in this publication was not performed at Janelia.

Abstract