Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

By Pengcheng Zhou, Shanna Resendez, Jose Rodríguez-Romaguera, Jessica C. Jimenez, Shay Q. Neufeld, A. Giovannucci, Johannes Friedrich, Eftychios A. Pnevmatikakis, Garret D. Stuber, R. Hen and 4 more. eLife, 2018

624 citations recorded by the source corpus.

In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal activity from microendoscopic data, because of the very large background fluctuations and high spatial overlaps intrinsic to this recording modality. Here, we describe a new constrained matrix factorization approach to accurately separate the background and then demix and denoise the neuronal signals of interest. We compared the proposed method against previous independent components analysis and constrained nonnegative matrix factorization approaches. On both simulated and experimental data recorded from mice, our method substantially improved the quality of extracted cellular signals and detected more well-isolated neural signals, especially in noisy data regimes. These advances can in turn significantly enhance the statistical power of downstream analyses, and ultimately improve scientific conclusions derived from microendoscopic data.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/7f155238f9fc9b1e49035b09f31c1690d27d0c5a

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

Tracking the Same Neurons across Multiple Days in Ca2+ Imaging Data (2017, methodology): “Although we detected a higher density of cells with CNMF-E, we could, nonetheless, register cells (198,230 neighboring cell-pairs) with certainty levels, false-negative rates, and false-positive rates comparable to those obtained with PCA-ICA (Figures 4G and 4H).”
CaImAn an open source tool for scalable calcium imaging data analysis (2019, methodology): “Apart from these significant algorithmic improvements CAIMAN includes several useful analysis tools such as, a MapReduce and memorymapping compatible implementation of the CNMF-E algorithm for one-photon microendoscopic data (Zhou et al., 2018), a novel efficient algorithm for registration of compon”