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[Coursera] Computational Neuroscience

CourseraComputationalNeuroscience

种子大小：780.14 MB

收录时间：2014-04-02

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文件列表：128File

  1. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)01 - 1 Neurons as Classifiers and Supervised Learning (25-57)8 - 1 - 1 Neurons as Classifiers and Supervised Learning (2557).mp432.69 MB
  2. 06 - Week 6 Computing with Networks (Rajesh Rao)03 - 3 The Fascinating World of Recurrent Networks (25-35)6 - 3 - 3 The Fascinating World of Recurrent Networks (2535).mp432.05 MB
  3. 06 - Week 6 Computing with Networks (Rajesh Rao)01 - 1 Modeling Connections between Neurons (24-28)6 - 1 - 1 Modeling Connections between Neurons (2428).mp431.06 MB
  4. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)04 - 4 The Electrical Personality of Neurons (23-02)1 - 4 - 4 The Electrical Personality of Neurons (2302).mp430.88 MB
  5. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)05 - Guest Lecture Eric Shea-Brown (22-52)5 - 5 - Guest Lecture Eric Shea-Brown (2252).mp430.33 MB
  6. 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)01 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (24-17)7 - 1 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (2417).mp430.32 MB
  7. 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)03 - 3 Sparse Coding and Predictive Coding (23-54)7 - 3 - 3 Sparse Coding and Predictive Coding (2354).mp430.1 MB
  8. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)03 - 3 Reinforcement Learning Time for Action (19-49)8 - 3 - 3 Reinforcement Learning Time for Action (1949).mp429.27 MB
  9. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)02 - 2 Population Coding and Bayesian Estimation (24-44)3 - 2 - 2 Population Coding and Bayesian Estimation (2444).mp428.23 MB
  10. 06 - Week 6 Computing with Networks (Rajesh Rao)02 - 2 Introduction to Network Models (21-47)6 - 2 - 2 Introduction to Network Models (2147).mp427.4 MB
  11. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)04 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (20-06)8 - 4 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (2006).mp427.31 MB
  12. 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)02 - 2 Introduction to Unsupervised Learning (22-06)7 - 2 - 2 Introduction to Unsupervised Learning (2206).mp427.21 MB
  13. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)03 - 3 Coding Principles (19-09)4 - 3 - 3 Coding Principles (1909).mp423.53 MB
  14. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)04 - 4 A Forest of Dendrites (19-19)5 - 4 - 4 A Forest of Dendrites (1919).mp423.04 MB
  15. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)01 - 1 Information and Entropy (19-12)4 - 1 - 1 Information and Entropy (1912).mp422.8 MB
  16. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)06 - 6 Time to Network Brain Areas and their Function (17-06)1 - 6 - 6 Time to Network Brain Areas and their Function (1706).mp422.35 MB
  17. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)01 - 1 Neural Decoding and Signal Detection Theory (18-55)3 - 1 - 1 Neural Decoding and Signal Detection Theory (1855).mp421.61 MB
  18. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)02 - 2 Calculating Information in Spike Trains (17-25)4 - 2 - 2 Calculating Information in Spike Trains (1725).mp421.1 MB
  19. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)03 - 3 Simplified Model Neurons (18-40)5 - 3 - 3 Simplified Model Neurons (1840).mp420.25 MB
  20. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)05 - 5 Making Connections Synapses (21-59)1 - 5 - 5 Making Connections Synapses (2159).mp418.35 MB
  21. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)04 - Guest Lecture Fred Rieke (14-01)3 - 4 - Guest Lecture Fred Rieke (1401).mp417.42 MB
  22. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)04 - 4 Neural Encoding Variability (23-52)2 - 4 - 4 Neural Encoding Variability (2352).mp417.27 MB
  23. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)02 - 2 Reinforcement Learning Predicting Rewards (13-01)8 - 2 - 2 Reinforcement Learning Predicting Rewards (1301).mp416.37 MB
  24. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)03 - 3 Neural Encoding Feature Selection (22-13)2 - 3 - 3 Neural Encoding Feature Selection (2213).mp415.91 MB
  25. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)1 - 3 - 3 Computational Neuroscience Mechanistic and Interpretive Models (1235).mp415.89 MB
  26. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)02 - 2 Spikes (14-09)5 - 2 - 2 Spikes (1409).mp415.88 MB
  27. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)01 - 1 Modeling Neurons (13-52)5 - 1 - 1 Modeling Neurons (1352).mp415.86 MB
  28. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)03 - 3 Reading Minds Stimulus Reconstruction (11-59)3 - 3 - 3 Reading Minds Stimulus Reconstruction (1159).mp415.1 MB
  29. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)01 - 1 What is the Neural Code (19-18)2 - 1 - 1 What is the Neural Code (1918).mp415.05 MB
  30. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)02 - 2 Computational Neuroscience Descriptive Models (11-50)1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).mp414.95 MB
  31. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)01 - 1 Information and Entropy (19-12)Lecture 4 part 1.pdf8.5 MB
  32. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)01 - 1 Modeling Neurons (13-52)Lecture 5 Part 1.pdf8.3 MB
  33. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)02 - 2 Neural Encoding Simple Models (12-06)2 - 2 - 2 Neural Encoding Simple Models (1206).mp48.19 MB
  34. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)01 - 1 Course Introduction and Logistics (06-05)1 - 1 - 1 Course Introduction and Logistics (0605).mp48.08 MB
  35. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)03 - 3 Coding Principles (19-09)Lecture 4 part 3.pdf7.14 MB
  36. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)04 - 4 A Forest of Dendrites (19-19)Lecture 5 Part 3.pdf4.1 MB
  37. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)03 - 3 Reading Minds Stimulus Reconstruction (11-59)Lecture 3 part 3.pdf3.86 MB
  38. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)03 - 3 Simplified Model Neurons (18-40)Lecture 5 Part 2.pdf3.69 MB
  39. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)02 - 2 Population Coding and Bayesian Estimation (24-44)Lecture 3 part 2.pdf3.66 MB
  40. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)02 - 2 Calculating Information in Spike Trains (17-25)Lecture 4 part 2.pdf3.38 MB
  41. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)01 - 1 Neural Decoding and Signal Detection Theory (18-55)Lecture 3 part 1.pdf3.34 MB
  42. 06 - Week 6 Computing with Networks (Rajesh Rao)03 - 3 The Fascinating World of Recurrent Networks (25-35)6.3slides.pdf2.63 MB
  43. 06 - Week 6 Computing with Networks (Rajesh Rao)02 - 2 Introduction to Network Models (21-47)6.2slides_new.pdf2.36 MB
  44. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)02 - 2 Neural Encoding Simple Models (12-06)Lecture 2 part 2.pdf2.23 MB
  45. 06 - Week 6 Computing with Networks (Rajesh Rao)01 - 1 Modeling Connections between Neurons (24-28)6.1slides.pdf2.14 MB
  46. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)04 - 4 Neural Encoding Variability (23-52)Lecture 2 part 4.pdf2.13 MB
  47. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)01 - 1 What is the Neural Code (19-18)Lecture 2 part 1.pdf2.09 MB
  48. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)03 - 3 Neural Encoding Feature Selection (22-13)Lecture 2 part 3.pdf1.84 MB
  49. 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)03 - 3 Sparse Coding and Predictive Coding (23-54)7.3.pdf1.73 MB
  50. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)01 - 1 Neurons as Classifiers and Supervised Learning (25-57)8.1.pdf1.65 MB
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