Dataset Open Access

Averaged results of blood flow simulations with discrete RBC tracking for microvascular networks

Franca Schmid

Jenny, Patrick; Weber, Bruno; Kleinfeld, David

The dataset contains the results for blood flow simulations in 3 cerebral micorvascular networks.The microvascular networks are from the mouse parietal cortex (Tsai et al., 2009) and embedded in a tissue volume of approximately 1 cubic mm. For the blood flow simulations we used a numercial model with discrete tracking of RBCs which is described in Schmid et al., 2017.

For each network the following data are provided:
- Microvascular network with averaged flow and pressure field, as well as averaged values for the distribution and motion of red blood cells (RBCs).
- RBC trajectories describing the motion of individual RBCs through the microvascular networks.

Data format (pickle - files, python):
Microvascular networks:
edgesDict.pkl: dictionary with edge related data (flow, diameter, ... )
verticesDict.pkl: dictionary with vertex related data (pressure, coordinates, ...)
RBC trajectories:
RBC_trajectories.pkl: dictonary for each RBC with the relevant tracking data.


Files (861.1 MB)
Name Size
249.9 MB Download
467.4 MB Download
143.8 MB Download
  • Blinder P, Tsai PS, Kaufhold JP, Knutsen PM, Suhl H, Kleinfeld D. The cortical angiome: an interconnected vascular network with noncolumnar patterns of blood flow. Nature Neurosci. 2013;16(7):889–897
  • Schmid F, Tsai PS, Kleinfeld D, Jenny P, Weber B. Depth-Dependent Flow and Pressure Characteristics in Cortical Microvascular Networks. PLOS Computational Biology. 2017. doi: 10.1371/journal.pcbi.1005392
  • Tsai PS, Kaufhold JP, Blinder P, Friedman B, Drew PJ, Karten HJ, et al. Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels. The Journal of Neuroscience. 2009;29(46):14553–14570


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