Greetings Yunan,

Thank you very much for your question! Concerning your note about spatiotemporal resolution, PIVlab suggests to set the spacing between velocity estimates (interrogation area) to at least four times the maximum displacement between frames (Thielicke and Stamhuis, 2014). For example, if the speeds are 1 µm/min and the time interval is 5 min, then the interrogation area should be at least 20 µm. If the pixel size is 0.31 µm with a 20x objective, then the interrogation area should be at least 64 px. Faster flows would require faster imaging and/or larger interrogation areas. A separate consideration is how incoherent particle movements decrease the image correlation between frames, which could limit estimation of slower flows.

Here, we apply our PIVlab workflow to a published movie of cytoplasmic flows in mouse embryos (Yi et al., 2011). In particular, Supplemental Movie 11 has a time interval of 10 s, a pixel size of 0.22 µm, and flow speeds slower than or comparable to 0.5 µm/min.

  1. Download Supplemental Movie 11 from (Yi et al., 2011).
  2. Convert to 8-bit .bmp image sequence. We converted from .mov to .avi using with the mjpeg video codec setting, then converted to 8-bit .bmp image sequence using Fiji. To test PIV with a time interval of 5 min, we made a substack with every 30th frame.
  3. Import images into PIVlab (version 1.41). Choose Sequencing style 1-2, 2-3, 3-4, …
  4. Analyses settings -> PIV settings
    1. FFT window deformation
    2. Interrogation area: 64 px, Step: 32 px. See first paragraph above and note the interrogation area is greater than 45 px (0.5 µm/min * 5 min * 4 / 0.22 µm/px).
    3. Pass 2: 32 px
  5. Analysis -> Analyze!
  6. Plot -> Modify plot appearance -> Autoscale. Click on the arrows in the image to see the u (horizontal, positive to the right) and v (vertical, positive down) components.
  7. Export the vector fields File -> Save -> All results to MATLAB workspace for subsequent analysis.

We wish you all the best on your research as well!

James and Tim



Thielicke, W., and Stamhuis, E. (2014) PIVlab–towards user-friendly, affordable and accurate digital particle image velocimetry in MATLAB. Journal of open research software 2.

Yi, K., Unruh, J. R., Deng, M., Slaughter, B. D., Rubinstein, B., and Li, R. (2011) Dynamic maintenance of asymmetric meiotic spindle position through Arp2/3-complex-driven cytoplasmic streaming in mouse oocytes. Nature cell biology 13, 1252-1258.