Pre-start
Announcements
- Office hours tomorrow morning 10ish-noonish BRC Cafe
- Any homework questions?
Neural Signal Processing & Machine Learning
ELEC/BIOE 548 | ELEC 483
Fall 2022
Episode 16: And so we begin to cluster!
1
Introduction. Class & brains
2
Fundamental neurobiology. How do neurons fire? How/what do we record?
3
Modeling spike trains. First bit of analysis work and understanding firing properties of neurons.
5
Classification. Making machines learn. Which direction is a monkey trying to reach? Bayesian decoding.
4
Point processes. Continued modeling work of neurons.
6
Clustering/Mixture models. Making machines learn some more. Spike sorting.
Bi-weekly Schedule
7
Continuous decoding. Kalman filters. Machines continue to learn.
8
Spectral analysis? LFP interpretation in spectral domain. But also kinda in clustering.
Brain Signals!
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How can we measure neural activity?
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What info do neurons encode in trains of action potentials (“spike trains”)?
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How can we model “statically” encoded information?
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Estimation/”decoding”
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Signal conditioning – “spike sorting” (PCA, Expectation-Maximization)
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How can we model/decode “dynamic” information? (filtering, Kalman, HMM)
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Beyond spike trains (LFP, EEG, imaging)
The Journey
- Recognizing patterns and making machines learn!
- Chapter 4. Classification!
Quick recap
K = num targets/classes
N = num trials
D = num neurons
\((x_n)_d!\)
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???
What is Clustering???
