Signal & Data Analysis in Neuroscience (27-505) - Recitation
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Second semester, 2025
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Zoom room- link
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Recitations
Lesson 1, 24.3: Statistics and probability rehearsal- Slides
Lesson 2, 31.3: Signal sampling, firing rate, convolution and stochastic processes- Slides
Lesson 3, 7.4: Tuning curves, stochastic processes, Poisson processes- Slides
Lesson 4, 21.4: Single and Multiple point processes - Slides
Lesson 5, 28.4: PSTH & JPSTH - Slides
Lesson 6, 4.5: Neural Encoding - Slides
Lesson 7, 12.5: Discrimination, Neural decoding & Parameters Estimation - Slides
Lesson 8, 15.6: Information Theory - Slides
Lesson 9, 19.5: PCA+ICA - Slides
Lesson 10, 12.6: Clusters - Slides. Frequency Domain - Slides.
Lesson 11, 16.6: Systems, Filters - Slides
Lesson 12, ​​​
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Previous years hebrew recordings:
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1. Signal sampling, firing rate, convolution, SNR and stochastic processes- recording (2023),recording (2022)
2. Tuning curves, Stochastic processes, Point process- recording (2023),recording (2022)
3. Single and Multiple point processes- recording (2023),recording (2022)
4. PSTH, STA, linear kernels and GLM- recording (2023), recording (2022)
5. ROC and quiz preparation- recording (2023), recording (2022)
6. decoding, population vector and estimators - recording (2023), recording (2022)
7. optimization - recording (2023), recording (2022)
8. information theory- recording (2023), recording (2022)
9. dimensionality redution (PCA and ICA)- recording (2023), recording (2022)
10. clustering- recording (2022)
11. frequency domain I: Nyquist, fourier transform- recording (2022)
12. frequency domain II: Systems, filters- recording (2022)
13. frequency domain III: Spectral analysis- recording (2022)
14. frequency domain IV: Wavelets- recording (2020)