SIMA: Python Software for Analysis of Dynamic Fluorescence Imaging Data

Overview

Journal Front Neuroinform

Specialty Neurology

Date 2014 Oct 9

PMID 25295002

Citations 117

Authors

Patrick Kaifosh

Jeffrey D Zaremba

Nathan B Danielson

Attila Losonczy

Affiliations

Soon will be listed here.

Abstract

Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/.

Citing Articles

An of Things approach for adaptable control of behavioral and navigation-based experiments.

Bowler J, Zakka G, Yong H, Li W, Rao B, Liao Z Elife. 2025; 13.

PMID: 40008867 PMC: 11867614. DOI: 10.7554/eLife.97433.

Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3.

Moore J, Rashid S, Bicker E, Johnson C, Codrington N, Chklovskii D Nat Commun. 2025; 16(1):1119.

PMID: 39875374 PMC: 11775317. DOI: 10.1038/s41467-025-56289-9.

Synaptic basis of feature selectivity in hippocampal neurons.

Gonzalez K, Negrean A, Liao Z, Terada S, Zhang G, Lee S Nature. 2024; 637(8048):1152-1160.

PMID: 39695232 DOI: 10.1038/s41586-024-08325-9.

A preprocessing toolbox for 2-photon subcellular calcium imaging.

Jiang A, Zhao C, Sheffield M bioRxiv. 2024; .

PMID: 39605689 PMC: 11601315. DOI: 10.1101/2024.10.04.616737.

Recurrent Connectivity Shapes Spatial Coding in Hippocampal CA3 Subregions.

Kong E, Zabeh E, Liao Z, Mihaila T, Wilson C, Santhirasegaran C bioRxiv. 2024; .

PMID: 39574766 PMC: 11581023. DOI: 10.1101/2024.11.07.622379.

References

Dombeck D, Khabbaz A, Collman F, Adelman T, Tank D . Imaging large-scale neural activity with cellular resolution in awake, mobile mice. Neuron. 2007; 56(1):43-57. PMC: 2268027. DOI: 10.1016/j.neuron.2007.08.003. View

Kerr J, Denk W . Imaging in vivo: watching the brain in action. Nat Rev Neurosci. 2008; 9(3):195-205. DOI: 10.1038/nrn2338. View

Mukamel E, Nimmerjahn A, Schnitzer M . Automated analysis of cellular signals from large-scale calcium imaging data. Neuron. 2009; 63(6):747-60. PMC: 3282191. DOI: 10.1016/j.neuron.2009.08.009. View

Campagnola L, Kratz M, Manis P . ACQ4: an open-source software platform for data acquisition and analysis in neurophysiology research. Front Neuroinform. 2014; 8:3. PMC: 3906568. DOI: 10.3389/fninf.2014.00003. View

van der Walt S, Schonberger J, Nunez-Iglesias J, Boulogne F, Warner J, Yager N . scikit-image: image processing in Python. PeerJ. 2014; 2:e453. PMC: 4081273. DOI: 10.7717/peerj.453. View

Schrodel T, Prevedel R, Aumayr K, Zimmer M, Vaziri A . Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light. Nat Methods. 2013; 10(10):1013-20. DOI: 10.1038/nmeth.2637. View

Looger L, Griesbeck O . Genetically encoded neural activity indicators. Curr Opin Neurobiol. 2011; 22(1):18-23. DOI: 10.1016/j.conb.2011.10.024. View

OConnor D, Clack N, Huber D, Komiyama T, Myers E, Svoboda K . Vibrissa-based object localization in head-fixed mice. J Neurosci. 2010; 30(5):1947-67. PMC: 6634009. DOI: 10.1523/JNEUROSCI.3762-09.2010. View

Verveer P, Swoger J, Pampaloni F, Greger K, Marcello M, Stelzer E . High-resolution three-dimensional imaging of large specimens with light sheet-based microscopy. Nat Methods. 2007; 4(4):311-3. DOI: 10.1038/nmeth1017. View

10.

Lovett-Barron M, Kaifosh P, Kheirbek M, Danielson N, Zaremba J, Reardon T . Dendritic inhibition in the hippocampus supports fear learning. Science. 2014; 343(6173):857-63. PMC: 4018419. DOI: 10.1126/science.1247485. View

11.

Schneider C, Rasband W, Eliceiri K . NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012; 9(7):671-5. PMC: 5554542. DOI: 10.1038/nmeth.2089. View

12.

Kaifosh P, Lovett-Barron M, Turi G, Reardon T, Losonczy A . Septo-hippocampal GABAergic signaling across multiple modalities in awake mice. Nat Neurosci. 2013; 16(9):1182-4. DOI: 10.1038/nn.3482. View

13.

Komiyama T, Sato T, OConnor D, Zhang Y, Huber D, Hooks B . Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice. Nature. 2010; 464(7292):1182-6. DOI: 10.1038/nature08897. View

14.

Edelstein A, Amodaj N, Hoover K, Vale R, Stuurman N . Computer control of microscopes using µManager. Curr Protoc Mol Biol. 2010; Chapter 14:Unit14.20. PMC: 3065365. DOI: 10.1002/0471142727.mb1420s92. View

15.

Thevenaz P, Ruttimann U, Unser M . A pyramid approach to subpixel registration based on intensity. IEEE Trans Image Process. 2008; 7(1):27-41. DOI: 10.1109/83.650848. View