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Fig. 1

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ZDB-FIG-221023-7
Publication
Rupprecht et al., 2021 - A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging
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Fig. 1

a, A large and diverse ground truth database obtained by simultaneous calcium imaging and juxtacellular recording (left) can be used 1) for the exploration of the ground truth by a user, 2) for the analysis of the out-ofdataset generalization of spike inference and 3) for the training of a supervised algorithm for spike inference. The right column refers to relevant figures. Colab Notebook refers to relevant cloud-based tools accompanying this paper. b-f, Examples of ground truth recordings with different indicators, different brain regions and species. Left: calcium signal traces (ΔF/F) are shown together with the detected action potentials (APs). Dashed lines indicate breaks during recordings. Traces are representative for recordings from different datasets (see Table 1 for detailed information). Middle: linear kernels of ΔF/F (time scale in seconds) and electrophysiological data (time scale in milliseconds) triggered by single spikes. Right: fluorescence image of the respective neuron, together with the ROI for fluorescence extraction. g, Average spike rate for each neuron of the ground truth database (log scale). 27 datasets (DS) were included in total. Datasets from inhibitory neurons comprise DS#22-27. h, Integral ΔF/F of the spike kernel (first 2 s) for each neuron. Lowest values are observed in PV+ interneurons (DS#23 and #24). See Extended Data Fig. 1 for the underlying kernels.

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This image is the copyrighted work of the attributed author or publisher, and ZFIN has permission only to display this image to its users. Additional permissions should be obtained from the applicable author or publisher of the image. Full text @ Nat. Neurosci.