I'm aware that K Means is not an ideal method of doing this. I'm just looking to provide a comparison against a better and more specific algorithm.
Using K Means clustering to identify coactivation of neurons
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Hi, I want to identify clusters of brain cells (cells firing in synchrony) in a data set of 15989x36 (15989 frames of video for 36 cells). The matrix consists only of 1s and 0s, being 1 where a cell has activated and 0 everywhere else. My problem lies in how to display these clusters, since their spatial positions are stored in a completely different matrix than their activation spikes.
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Image Analyst
on 6 Apr 2021
"My problem lies in how to display these clusters" <=== use plot3() or scatter3().
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Image Analyst
on 7 Apr 2021
What do the different columns of binary represent?
But then if your data is x, y, time, shouldn't you only pass in the third column into the kmeans()? Why are you having it cluster off of combination of spatial coordinates and time?
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