I can’t understand how to get information about brain area according to 3d coordinate. For example, if I have the following coordinate: "anterior_posterior_ccf_coordinate " “dorsal_ventral_ccf_coordinate” “left_right_ccf_coordinate”: 7493.0 , 423.0, 7452.0, which brain region does this point belong to?
Ok, I found the way. Given that the highest definition atlas has a resolution of 10µm I am dividing the coordinates by 10 and than rounding them to the nearest integer, I guess that’s right, can somebody confirm it?
Second question: Is there a reason why in the neuropixel dataset cortical channels are not assigned a layer(e.g. VISal1,VISal2/3,VISal4… and not just VISal)? Can I assign it myself using the coordinate?
I guess I can’t really do it, the areas retrieved are quite different.
Hi Roberto – your method for extracting the area labels is correct. There are two reasons for the apparent discrepancy between the labels in the CCF volume and the labels in the Neuropixels dataset:
(1) We replace any white matter tracts (lower case labels) with the next highest brain region along the probe.
(2) We extract the visual area labels from each mouse’s retinotopic map, rather than the CCF volume. If a probe is inserted near the border between two areas, there may be disagreement between the template volume and the individual map.
We chose to call these area labels
ecephys_structure_acronyms, because they do not exactly match the acronyms found at the corresponding locations in the CCF.
To determine cortical layers, it’s reasonable to use the labels from the CCF volume, even if the visual area names don’t match. Indeed, this is what we did to produce Extended Data Figure 10 (Layer-Wise Analysis) of the 2021 Nature paper. However, you should bear in mind that these labels will only be approximate, as they are based on the average template and do not account for individual variations in layer location.