Automated analysis of cellular signals from large-scale calcium imaging data.

By Eran A. Mukamel, A. Nimmerjahn, Mark J. Schnitzer. Neuron, 2009

705 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4cf1fe897f368f9ef4673457dfacb8b35a65b90e

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Citations in the corpus

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data (2018, neutral): “The existing methods for extracting individual neural activity from microendoscopic data can be divided into two classes: semi-manual ROI analysis (Barbera et al., 2016; Klaus et al., 2017; Pinto and Dan, 2015) and PCA/ICA analysis (Mukamel et al., 2009).”
Closed-loop and activity-guided optogenetic control. (2015, neutral): “…Hä usser, 2010); independent-components analysis applied to volume data (ICA) (Grosenick et al., 2009); spatiotemporal ICA applied to image data (Mukamel et al., 2009); and sparse, structured matrix factorization techniques applied to image data (Andilla and Hamprecht, 2013, 2014; Maruyama et…”
Computer Methods and Programs in Biomedicine (2019, methodology): “The number of principal components used was chosen to be 500 for Dataset 1, 160 for Dataset 2, and 100 for Dataset 3, which is slightly higher than the estimated number of active cells [6] .”
Functional imaging of hippocampal place cells at cellular resolution during virtual navigation (2010, positive): “We used an ICA/PCA algorithm to identify individual neurons based on both their spatial and temporal characteristics 21 .”
Fast nonnegative deconvolution for spike train inference from population calcium imaging. (2009, methodology): “This problem may be considered a special case of bli nd source separation [34, 30].”
A dedicated population for reward coding in the hippocampus (2018, positive): “Cell shapes and fluorescence transient waveforms were identified using a modified version of an existing algorithm (Mukamel et al., 2009).”
CaImAn an open source tool for scalable calcium imaging data analysis (2019, methodology): “To extract temporal traces jointly with the spatial footprints of the components one can use methods that directly represent the full spatio-temporal data using matrix factorization approaches for example independent component analysis (ICA) (Mukamel et al., 2009), constrained eLife digest The human”
Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data (2016, neutral): “We compare our method against the popular PCA/ICA method of Mukamel et al. (2009) and the plain NMF method proposed in Maruyama et al. (2014).”