Hello All,

We're a research team out of the University of New Mexico, attempting to plot microplastics abundance onto brain sections. I've been trying to figure out the best way to do this and figured it would be worth asking the experts here. For some background, I've analyzed multi-omics data and tried my hand at molecular docking analysis, but this is solidly outside my wheelhouse.

For a visual explanation, each brain section analyzed is about 9mm thick from front to back (see picture below).

Unfortunately, there was too much material in most of the sections, and these had to be subdivided into regions per slice from left to right and top to bottom (see below). The subregions are named B1 for slice 1, C1-C2 for slice 2, D1-D4 for slice 3, E1-E7 for slice 4,..., all the way to AB1 for slice 27.

During the analysis, we sectioned off grey matter from white matter to increase data resolution, and some regions of interest were noted during dissection (corpus callosum, basal ganglia, amygdala, etc.) which are anotated in the master csv. 

For the data itself, metadata include columns:
Region -> the slice number

Known Subregion -> any region of interest, like corpus callosum

Slice -> master column for subregions from left to right and top to bottom as well as the gm (grey matter) and wm (white matter)

Subregion -> corresponds to the orientation from left to right and top to bottom, populated from Slice column

Matter -> Grey or White matter, populated from Slice column

PE: N66 -> microplastic abundance for each microplastic type measured

My attempt so far: I've downloaded each image from front to back, then wrote a function in R to apply a heatmap overlay of microplastic abundance. Smoothed the values between regions (left, right, top, bottom), then downloaded that image. The eventual goal would be to upload these as overlays onto the mni152 and smoothe between each 9mm section from front to back. 

We also have the data for cerebellum sections and brain stem sections using a similar approach, but I figure it would be most beneficial to determine an accurate methodology for the main brain first and then adapt that methodology to the cerebellum and brain stem after. 

Is there a more accurate way to do this than I've been trying so far? Is there a script that I can write to apply the heatmap data while keeping the white matter and grey matter data intact?

More broadly, how would you go about applying these tabular data onto the mni152? 

And if you're interested in collaborating on the data analysis portion, happy to chat as well.