| Table of Contents |
|---|
Overall Workflow
In general, workflow looks like this:
- Set up your account for TACC and 3DEM.org.
- A stack of serial tSEM images (a complete set of original images with optimized focus, brightness, and contrast; Don't forget to take an image of a calibration grid!)
- Image alignment with AlignEM-SWiFT or Fiji/TrakEM2
- Stack-crop the aligned images, export as .tif files
- Assign a series code and rename image files
- Get a spreadsheet ready for series data collection
- Import aligned images into RECONSTRUCT
- Manually fine-tune alignment, if necessary
- Calibration: x-y (pixel size) with a calibration grid image; z (section thickness) by the cylindrical mitochondria method
- Choose and trace neuropil elements (and organelles) of interest
- Data analysis
- Publication, etc.
See here for KH lab specific information.
Things to do before Reconstructing:
Learn about neuropil ultrastructure
!IMPORTANT! How familiar are you with EM images? Can you identify neuropil, synapses, organelles, etc.?
- Atlas of Ultrastructural Neurocytology and Tutorials
- Peters A, Palay SL, Webster H. (1991) The Fine Structure of the Nervous System (3rd Ed). Oxford University Press, New York. ISBN 0-19-506571-9.
Get your TACC account
!IMPORTANT! Make sure you have access to the 3DEM.org portal at TACC (James Carson is the current contact person).
Pre-processing of serial section EM images before importing into RECONSTRUCT
- Upload serial section EM images to 3DEM.org (stampede2.tacc.utexas.edu)
- Command line instructions (Harris lab specific; restricted access)
- Alignment of serial section EM images using AlignEM-SWiFT
- Assign a series code (Harris lab specific; restricted access)
- Rename aligned serial EM image files with Bulk Rename Utility
- Suggested format: XXXXX_### (XXXXX = series code; ### = section number; 000 = calibration grid image)
Protocols for Reconstruct (and other analysis tools):
- Get your Reconstruct here! (Use 32-bit version; 64-bit may be buggy)
- Instructions for new users of Reconstruct: Reconstruct: Intro for Beginners, Reconstruct Basics, User Manual.
- Starting a New Series
- Section Thickness
- Calibration Error Correction Strategy
- Alignment by Correlation
- Adjusting brightness/contrast
- Editing Trace Pallettes
- Importing Traces
- Unbiased 3D stereology
- Grey wall tracing
- Same-dendrite-same-axon analysis
- Dendrites:
- Counting or Tracing Mictotubules
- Tracing Z-Lengths
- Tracing plinn (linear nearest-neighbor distance between protrusions)
- Spines:
- Stamping Dendritic Protrusions
- Cutting off spines and spine heads: Reconstruct / Blender (with Python add-on described in Bartol et al., 2016)
- Synapses:
- Identifying Symmetric and Asymmetric Synapses
- Tracing synapses (nascent and active zones)
- Axons:
- Organelles:
- Exporting quantitative data
- RECONSTRUCT color scheme
- pyRECONSTRUCT merge tool
- CellBlender: Github | MCell and CellBlender | Tutorial | Neuropil Tools
- NeuroMorph: httphttps://cvlabneuromorph.epfl.ch/NeuroMorph
- Recompanion Protocol
Data Analysis and Statistics:
- Data Entry and Dendrite Analysis Spreadsheet
- Statistical Analyses with STATISTICA
- Making Box and Whisker Plots in Excel
- Data Transforms
- Statistics for Biologists (Nature collection)
- Considerations and recommendations for experimental designs (Journal of Neuroscience)
Consideration of Sample Size in Neuroscience Studies (Journal of Neuroscience)
- Ask an Expert: Estimation Statistics and Statistical Power (Society for Neuroscience)
- Power Analysis:
- Introduction to power analysis (UCLA)
- Sample size determination and power analysis using the G*Power software (J Educ Eval Health Prof, Vol 18, 2021)
- G*Power (Heinrich-Heine-Universität Düsseldorf)