AI Article Synopsis

  • Calcium imaging is a technique that allows researchers to monitor activity in large groups of neurons, but it's unclear if standard methods for analyzing spiking activity are suitable for this.
  • The study explores different design choices for dimensionality reduction methods, leading to the development of a new method called Calcium Imaging Linear Dynamical System (CILDS).
  • CILDS effectively recovers low-dimensional time courses from calcium imaging data and outperforms existing techniques in experiments with zebrafish and mice, setting a groundwork for better analysis of neuronal activity.

Article Abstract

Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358781PMC
http://dx.doi.org/10.1038/s43588-022-00390-2DOI Listing

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