TY - JOUR
T1 - SpecSeg is a versatile toolbox that segments neurons and neurites in chronic calcium imaging datasets based on low-frequency cross-spectral power
AU - de Kraker, Leander
AU - Seignette, Koen
AU - Thamizharasu, Premnath
AU - van den Boom, Bastijn J.G.
AU - Ferreira Pica, Ildefonso
AU - Willuhn, Ingo
AU - Levelt, Christiaan N.
AU - Togt, Chris van der
PY - 2022/10/24
Y1 - 2022/10/24
N2 - Imaging calcium signals in neurons of animals using single- or multi-photon microscopy facilitates the study of coding in large neural populations. Such experiments produce massive datasets requiring powerful methods to extract responses from hundreds of neurons. We present SpecSeg, an open-source toolbox for (1) segmentation of regions of interest (ROIs) representing neuronal structures, (2) inspection and manual editing of ROIs, (3) neuropil correction and signal extraction, and (4) matching of ROIs in sequential recordings. ROI segmentation in SpecSeg is based on temporal cross-correlations of low-frequency components derived by Fourier analysis of each pixel with its neighbors. The approach is user-friendly, intuitive, and insightful and enables ROI detection around neurons or neurites. It works for single- (miniscope) and multi-photon microscopy data, eliminating the need for separate toolboxes. SpecSeg thus provides an efficient and versatile approach for analyzing calcium responses in neuronal structures imaged over prolonged periods of time.
AB - Imaging calcium signals in neurons of animals using single- or multi-photon microscopy facilitates the study of coding in large neural populations. Such experiments produce massive datasets requiring powerful methods to extract responses from hundreds of neurons. We present SpecSeg, an open-source toolbox for (1) segmentation of regions of interest (ROIs) representing neuronal structures, (2) inspection and manual editing of ROIs, (3) neuropil correction and signal extraction, and (4) matching of ROIs in sequential recordings. ROI segmentation in SpecSeg is based on temporal cross-correlations of low-frequency components derived by Fourier analysis of each pixel with its neighbors. The approach is user-friendly, intuitive, and insightful and enables ROI detection around neurons or neurites. It works for single- (miniscope) and multi-photon microscopy data, eliminating the need for separate toolboxes. SpecSeg thus provides an efficient and versatile approach for analyzing calcium responses in neuronal structures imaged over prolonged periods of time.
UR - http://www.scopus.com/inward/record.url?scp=85158083839&partnerID=8YFLogxK
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85158083839&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/36313805
U2 - https://doi.org/10.1016/j.crmeth.2022.100299
DO - https://doi.org/10.1016/j.crmeth.2022.100299
M3 - Article
C2 - 36313805
SN - 2667-2375
VL - 2
JO - Cell Reports Methods
JF - Cell Reports Methods
IS - 10
M1 - 100299
ER -