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[Coursera] Computational Neuroscience

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  • 最近下载:2021-01-20 14:12:27
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  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).mp4 33MB
  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).mp4 32MB
  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).mp4 31MB
  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).mp4 31MB
  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).mp4 30MB
  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).mp4 30MB
  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).mp4 30MB
  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).mp4 29MB
  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).mp4 28MB
  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).mp4 27MB
  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).mp4 27MB
  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).mp4 27MB
  13. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).mp4 24MB
  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).mp4 23MB
  15. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).mp4 23MB
  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).mp4 22MB
  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).mp4 22MB
  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).mp4 21MB
  19. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).mp4 20MB
  20. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).mp4 18MB
  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).mp4 17MB
  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).mp4 17MB
  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).mp4 16MB
  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).mp4 16MB
  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).mp4 16MB
  26. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).mp4 16MB
  27. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).mp4 16MB
  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).mp4 15MB
  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).mp4 15MB
  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).mp4 15MB
  31. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/Lecture 4 part 1.pdf 9MB
  32. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/Lecture 5 Part 1.pdf 8MB
  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).mp4 8MB
  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).mp4 8MB
  35. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/Lecture 4 part 3.pdf 7MB
  36. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/Lecture 5 Part 3.pdf 4MB
  37. 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/Lecture 3 part 3.pdf 4MB
  38. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/Lecture 5 Part 2.pdf 4MB
  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.pdf 4MB
  40. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/Lecture 4 part 2.pdf 3MB
  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.pdf 3MB
  42. 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6.3slides.pdf 3MB
  43. 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6.2slides_new.pdf 2MB
  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.pdf 2MB
  45. 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6.1slides.pdf 2MB
  46. 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/Lecture 2 part 4.pdf 2MB
  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.pdf 2MB
  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.pdf 2MB
  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.pdf 2MB
  50. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8.1.pdf 2MB
  51. 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7.2.pdf 1MB
  52. 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.pdf 1MB
  53. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8.3.pdf 1MB
  54. 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8.2.pdf 865KB
  55. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1.4.pdf 704KB
  56. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1.5-2014.pdf 704KB
  57. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1.2.pdf 605KB
  58. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1.6.pdf 562KB
  59. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1.3.pdf 443KB
  60. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1.1.pdf 338KB
  61. lectures.html 81KB
  62. index.html 42KB
  63. 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).srt 36KB
  64. 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).srt 33KB
  65. 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).srt 33KB
  66. 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).srt 33KB
  67. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/05 - Guest Lecture Eric Shea-Brown (22-52)/5 - 5 - Guest Lecture Eric Shea-Brown (2252).srt 33KB
  68. 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).srt 33KB
  69. 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).srt 32KB
  70. 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6 - 1 - 1 Modeling Connections between Neurons (2428).srt 32KB
  71. 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).srt 32KB
  72. 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).srt 30KB
  73. 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).srt 30KB
  74. 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).srt 30KB
  75. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).srt 29KB
  76. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/5 - 4 - 4 A Forest of Dendrites (1919).srt 28KB
  77. 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6 - 2 - 2 Introduction to Network Models (2147).srt 28KB
  78. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).srt 28KB
  79. 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).srt 27KB
  80. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).srt 27KB
  81. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).srt 25KB
  82. 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).srt 25KB
  83. 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).srt 24KB
  84. 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).srt 23KB
  85. 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).txt 22KB
  86. 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).txt 22KB
  87. 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).txt 22KB
  88. 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).txt 22KB
  89. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/05 - Guest Lecture Eric Shea-Brown (22-52)/5 - 5 - Guest Lecture Eric Shea-Brown (2252).txt 22KB
  90. 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).srt 21KB
  91. 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).txt 21KB
  92. 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6 - 1 - 1 Modeling Connections between Neurons (2428).txt 21KB
  93. 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).txt 21KB
  94. 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).srt 21KB
  95. 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).txt 20KB
  96. 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).txt 20KB
  97. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).srt 20KB
  98. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).srt 20KB
  99. 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).txt 20KB
  100. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/5 - 4 - 4 A Forest of Dendrites (1919).txt 19KB
  101. 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6 - 2 - 2 Introduction to Network Models (2147).txt 19KB
  102. 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).txt 19KB
  103. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).txt 18KB
  104. 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).txt 18KB
  105. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).txt 18KB
  106. 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).srt 17KB
  107. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).txt 17KB
  108. 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).srt 17KB
  109. 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).txt 17KB
  110. 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).srt 17KB
  111. 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).srt 17KB
  112. 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).txt 16KB
  113. 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).txt 16KB
  114. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).srt 15KB
  115. 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).txt 15KB
  116. 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).txt 14KB
  117. compneuro-002-about.json 14KB
  118. 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).txt 14KB
  119. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).txt 13KB
  120. 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).txt 13KB
  121. 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).txt 11KB
  122. 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).txt 11KB
  123. 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).txt 11KB
  124. 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).txt 11KB
  125. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).txt 10KB
  126. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1 - 1 - 1 Course Introduction and Logistics (0605).srt 9KB
  127. 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1 - 1 - 1 Course Introduction and Logistics (0605).txt 6KB