Dataset Information

Detecting and correcting false transients in calcium imaging.

ABSTRACT: Population recordings of calcium activity are a major source of insight into neural function. Large datasets require automated processing, but this can introduce errors that are difficult to detect. Here we show that popular time course-estimation algorithms often contain substantial misattribution errors affecting 10-20% of transients. Misattribution, in which fluorescence is ascribed to the wrong cell, arises when overlapping cells and processes are imperfectly defined or not identified. To diagnose misattribution, we develop metrics and visualization tools for evaluating large datasets. To correct time courses, we introduce a robust estimator that explicitly accounts for contaminating signals. In one hippocampal dataset, removing contamination reduced the number of place cells by 15%, and 19% of place fields shifted by over 10 cm. Our methods are compatible with other cell-finding techniques, empowering users to diagnose and correct a potentially widespread problem that could alter scientific conclusions.

SUBMITTER: Gauthier JL

PROVIDER: S-EPMC10715860 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Detecting and correcting false transients in calcium imaging.

Gauthier Jeffrey L JL Koay Sue Ann SA Nieh Edward H EH Tank David W DW Pillow Jonathan W JW Charles Adam S AS

Nature methods 20220328 4

Population recordings of calcium activity are a major source of insight into neural function. Large datasets require automated processing, but this can introduce errors that are difficult to detect. Here we show that popular time course-estimation algorithms often contain substantial misattribution errors affecting 10-20% of transients. Misattribution, in which fluorescence is ascribed to the wrong cell, arises when overlapping cells and processes are imperfectly defined or not identified. To di ...[more]

PMID: 35347320

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Project description:One of the main topics of cardiovascular research is the study of calcium (Ca2+) handling, as even small changes in Ca2+ concentration can alter cell functionality (Bers, Annu Rev Physiol, 2014, 76, 107-127). Ionic calcium (Ca2+) plays the role of a second messenger in eukaryotic cells, associated with cellular functions such as cell cycle regulation, transport, motility, gene expression, and regulation. The use of fluorometric techniques in isolated cells loaded with Ca2+-sensitive fluorescent probes allows quantitative measurement of dynamic events occurring in living, functioning cells. The Cardiomyocytes Images Analyzer Python (CardIAP) application addresses the need to analyze and retrieve information from confocal microscopy images systematically, accurately, and rapidly. Here we present CardIAP, an open-source tool developed entirely in Python, freely available and useable in an interactive web application. In addition, CardIAP can be used as a standalone Python library and freely installed via PIP, making it easy to integrate into biomedical imaging pipelines. The images that can be generated in the study of the heart have the particularity of requiring both spatial and temporal analysis. CardIAP aims to open the field of cardiomyocytes and intact hearts image processing. The improvement in the extraction of information from the images will allow optimizing the usage of resources and animals. With CardIAP, users can run the analysis to both, the complete image, and portions of it in an easy way, and replicate it on a series of images. This analysis provides users with information on the spatial and temporal changes in calcium releases and characterizes them. The web application also allows users to extract calcium dynamics data in downloadable tables, simplifying the calculation of alternation and discordance indices and their classification. CardIAP aims to provide a tool that could assist biomedical researchers in studying the underlying mechanisms of anomalous calcium release phenomena.

Project description:Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify calcium signal candidates. The highly sensitive calcium event definition is based on identification of peaks in 1D data through analysis of a 2D wavelet transform surface. For spatial analysis, the tool uses a grid to separate the x,y-image field in independently analyzed grid windows. A document containing a graphical summary of the data is automatically created and displays the loci of activity for a wide range of signal intensities. Furthermore, the number of activity events is summed up to create an estimated total activity value, which can be used to compare different experimental situations, such as calcium activity before or after an experimental treatment. All traces and data of active loci become documented. The tool can also compute the signal variance in a sliding window to visualize activity-dependent signal fluctuations. We applied the calcium signal detector to monitor activity states of cultured mouse neurons. Our data show that both the total activity value and the variance area created by a sliding window can distinguish experimental manipulations of neuronal activity states. Notably, the tool is powerful enough to compute local calcium events and 'signal-close-to-noise' activity in small loci of distal neurites of neurons, which remain during pharmacological blockade of neuronal activity with inhibitors such as tetrodotoxin, to block action potential firing, or inhibitors of ionotropic glutamate receptors. The tool can also offer information about local homeostatic calcium activity events in neurites.

Dataset Information

Detecting and correcting false transients in calcium imaging.

Publications

Detecting and correcting false transients in calcium imaging.

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