New Stall Catchers dataset: "Structural mapping" 🧠

In record time here comes a fresh new dataset! 😀

As some of you catchers have guessed already, this one is going deeper into the brain to look for stalls. Here's what the Schaffer-Nishimura Lab said about it:

In this dataset, we are trying to evaluate the distribution of stalls throughout the brain. We imaged young and old mice in the cerebral cortex all the way to the white matter (900 um deep), to understand if the distribution of stalls changes as we go deeper into other brain structures.
This study can help us identify if there are brain regions more susceptible for stalls, if the vessel density/connectivity is in different brain areas, as well as the effect of age on these parameters. Stalls contribute to decreased cerebral blood flow and impaired cognition, therefore, understanding the distribution of stalls in different brain areas can help us understand where this blood flow deficit is coming from, and if it affects cognitive tasks in different ways.

This looks like one of the largest datasets we've ever had, so catch on! 😊


This is a companion discussion topic for the original entry at https://blog.hcinst.org/sc-dataset-structural/