search

openworm / neuronal-analysis

Tools to produce, analyse and compare both simulated and recorded neuronal datasets
MIT License
4 stars 4 forks source link

Trouble Recreating Kato-like visualizations from upstream data #3

Open slarson opened 8 years ago

slarson commented 8 years ago

Originally asked by @benjijack over here:

As a step toward that goal, building on @theideasmith's work importing Kato's data, I tried to recreate Kato's visualizations myself (see iPython notebook below), but from one step upstream: I tried to use the fluorescence bleach cancelled timeseries to naively compute the derivative myself, rather than use the fluorescence derivative timeseries directly. After all, if we are to take a timeseries output from c302 and compare it to Kato's results, we will have to reproduce the entire pipeline of analysis that Kato used. One could debate whether this is worth the effort, but it seems that Kato is (at least for the moment) our richest resource for neuron-by-neuron behavior in the real world, and worth comparing against.

I had trouble reproducing Kato's results from the upstream data. Although my approach was naive, it's not immediately clear to me how to fix it or how he cleaned the data so thoroughly. He mentions in the supplemental discussion on p. 9 that "total-variation regularization (Chartrand, 2011) was used to compute de-noised time derivatives...". Maybe someone else can shed more light on this or I can go back and read further on this technique.

Here's my attempt: output_3_1

iPython notebook with code and images: kato_visualization.pdf

slarson commented 8 years ago

@benjijack -- can you include the source for the iPython notebook? Perhaps post as a gist?

BenjiJack commented 8 years ago

Please find the source code for the above visualizations here: A visualization of C. elegans fluorescence data from Kato, et al. (2015)

slarson commented 8 years ago

@BenjiJack Did you ever find a solution for this?