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The 2025 version of the course has M/W lectures, but that hasn't allowed enough time to get into the mathematical derivations of the algorithms. I had to rush the coordinate ascent steps for the spike sorting by deconvolution and calcium demixing lectures. Perhaps the next iteration should have three lectures per week.
For the spike sorting by deconvolution lecture (and possibly also for the notes)
- Introduce the basic model without normalization and rank constraints on the templates first
- Encourage students to realize the non-identifiability problem and propose normalization
- Then encourage students to think about number of free parameters and propose constraints on template
We could follow the same approach in the online book.
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