SpineJ: A software tool for quantitative analysis of nanoscale spine morphology.

Super-resolution microscopy provides diffraction-unlimited optical access to the intricate morphology of neurons in living brain tissue, resolving their finest structural details, which are critical for neuronal function. However, as existing image analysis software tools have been developed for diffraction-limited images, they are generally not well suited for quantifying nanoscale structures like dendritic spines. We present SpineJ, a semi-automatic ImageJ plugin that is specifically designed for this purpose. SpineJ offers an intuitive and user-friendly graphical user interface, facilitating fast, accurate, and unbiased analysis of spine morphology.

[1]  W. Brent Lindquist,et al.  Automated Algorithms for Multiscale Morphometry of Neuronal Dendrites , 2004, Neural Computation.

[2]  Jochen Herms,et al.  The Role of APP in Structural Spine Plasticity , 2017, Front. Mol. Neurosci..

[3]  U Valentin Nägerl,et al.  Two-photon excitation STED microscopy in two colors in acute brain slices. , 2013, Biophysical journal.

[4]  Peter W. Kalivas,et al.  Automated quantification of dendritic spine density and spine head diameter in medium spiny neurons of the nucleus accumbens , 2008, Brain Structure and Function.

[5]  U Valentin Nägerl,et al.  Two-color STED microscopy of living synapses using a single laser-beam pair. , 2011, Biophysical journal.

[6]  Bernardo L. Sabatini,et al.  Supraresolution Imaging in Brain Slices using Stimulated-Emission Depletion Two-Photon Laser Scanning Microscopy , 2009, Neuron.

[7]  Carlo Sala,et al.  Dendritic spines: the locus of structural and functional plasticity. , 2014, Physiological reviews.

[8]  E Meijering,et al.  Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images , 2004, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[9]  Stephen T. C. Wong,et al.  Robust 3D reconstruction and identification of dendritic spines from optical microscopy imaging , 2009, Medical Image Anal..

[10]  W. Webb,et al.  Precise nanometer localization analysis for individual fluorescent probes. , 2002, Biophysical journal.

[11]  Katrin I Willig,et al.  Nanoscopy of filamentous actin in cortical dendrites of a living mouse. , 2014, Biophysical journal.

[12]  Bernardo L Sabatini,et al.  Live-cell superresolution imaging by pulsed STED two-photon excitation microscopy. , 2013, Biophysical journal.

[13]  U Valentin Nägerl,et al.  Chronic 2P-STED imaging reveals high turnover of dendritic spines in the hippocampus in vivo , 2018, eLife.

[14]  Stephen T. C. Wong,et al.  Automatic dendritic spine analysis in two‐photon laser scanning microscopy images , 2007, Cytometry Part A.

[15]  Yasushi Miyashita,et al.  Dendritic spine geometry is critical for AMPA receptor expression in hippocampal CA1 pyramidal neurons , 2001, Nature Neuroscience.

[16]  Gerald Farin,et al.  Curves and surfaces for computer aided geometric design , 1990 .

[17]  Stefan W. Hell,et al.  Nanoscopy in a Living Mouse Brain , 2012, Science.

[18]  T. Bonhoeffer,et al.  Live-cell imaging of dendritic spines by STED microscopy , 2008, Proceedings of the National Academy of Sciences.

[19]  U. Nägerl,et al.  Spine neck plasticity regulates compartmentalization of synapses , 2014, Nature Neuroscience.

[20]  Richard Kronland-Martinet,et al.  A real-time algorithm for signal analysis with the help of the wavelet transform , 1989 .

[21]  Christel Genoud,et al.  Automated analysis of spine dynamics on live CA1 pyramidal cells , 2015, Medical Image Anal..

[22]  K. Svoboda,et al.  Experience-dependent structural synaptic plasticity in the mammalian brain , 2009, Nature Reviews Neuroscience.

[23]  Gabriel Wittum,et al.  SpineLab: tool for three-dimensional reconstruction of neuronal cell morphology. , 2012, Journal of biomedical optics.

[24]  Douglas B. Ehlenberger,et al.  Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images , 2008, PloS one.

[25]  U. Nägerl,et al.  Superresolution imaging reveals activity-dependent plasticity of axon morphology linked to changes in action potential conduction velocity , 2017, Proceedings of the National Academy of Sciences.

[26]  U. Valentin Nägerl,et al.  Superresolution imaging for neuroscience , 2013, Experimental Neurology.

[27]  Jan Tønnesen,et al.  Considerations for Imaging and Analyzing Neural Structures by STED Microscopy. , 2019, Methods in molecular biology.

[28]  Rafael Yuste,et al.  Genesis of dendritic spines: insights from ultrastructural and imaging studies , 2004, Nature Reviews Neuroscience.

[29]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[30]  D W Tank,et al.  Direct Measurement of Coupling Between Dendritic Spines and Shafts , 1996, Science.

[31]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[32]  B. Sakmann,et al.  Nonlinear anisotropic diffusion filtering of three-dimensional image data from two-photon microscopy. , 2004 .