Oct 28, 2014

Supervised learning sets benchmark for robust spike detection from calcium imaging signals

BioRxiv : the Preprint Server for Biology
Lucas TheisMatthias Bethge

Abstract

We present a new data-driven approach to inferring spikes from calcium imaging signals using supervised training of non-linear spiking neuron models. Our technique yields a substantially better performance compared to previous generative modeling approaches, reconstructing spike trains accurately at high temporal resolution even from previously unseen datasets. Future data acquired in new experimental conditions can easily be used to further improve its spike prediction accuracy and generalization performance.

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Mentioned in this Paper

Calcium [EPC]
Entire Retina
Calcium
Neurons
Retinal Diseases
Malignant Neoplasm of Retina
Retina
Benign Neoplasm of Retina
Silo (Dataset)
Calcium Supplements

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