ELEC/BIOE 548 | ELEC 483
Fall 2022
Episode 17: Spike sorting intro finale and Clustering with math and stuff!
Introduction. Class & brains
Fundamental neurobiology. How do neurons fire? How/what do we record?
Modeling spike trains. First bit of analysis work and understanding firing properties of neurons.
Classification. Making machines learn. Which direction is a monkey trying to reach? Bayesian decoding.
Point processes. Continued modeling work of neurons.
Clustering/Mixture models. Making machines learn some more. Spike sorting.
Continuous decoding. Kalman filters. Machines continue to learn.
Spectral analysis? LFP interpretation in spectral domain. But also kinda in clustering.
How can we measure neural activity?
What info do neurons encode in trains of action potentials (“spike trains”)?
How can we model “statically” encoded information?
Estimation/”decoding”
Signal conditioning – “spike sorting” (PCA, Expectation-Maximization)
How can we model/decode “dynamic” information? (filtering, Kalman, HMM)
Beyond spike trains (LFP, EEG, imaging)
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???