Signal & Data Analysis in Neuroscience (27-505) - Recitation
Second semester, 2024
Zoom room- link
Important links:
Recitation instructions and gradings- link
Projects and Recitation Quizzes grades - link
Youtube channel- link
Recitations
Self learning: Statistics and probability rehearsal- notes, quiz
Lesson 1, 8.5: Signal sampling, firing rate, convolution, SNR and stochastic processes- notes, quiz
Lesson 2, 15.5: Tuning curves, stochastic processes, Poisson processes- notes, quiz
Lesson 3, 22.5: Single and Multiple point processes- notes, quiz
Lesson 4, 29.5: PSTH, STA, linear kernels and GLM, ROC- notes, quiz
Lesson 5, 5.6: Rehearsal and decoding: population vector and estimators- notes
Lesson 6, 19.6: decoding: population vector and estimators, Information theory- notes, quiz
Lesson 7, 3.7: frequency domain I: Nyquist, Fourier transform, Systems- notes, quiz
Lesson 8, 7.7,10.7: frequency domain II: Systems, filters- notes, quiz
Lesson 9, 17.7: frequency domain III: Spectral analysis- notes, quiz
Previous years hebrew recordings:
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)