[Coursera] Computational Neuroscience
File List
- 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 32.7 MB
- 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 32.1 MB
- 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 31.1 MB
- 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 30.9 MB
- 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 30.3 MB
- 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 30.3 MB
- 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 30.1 MB
- 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 29.3 MB
- 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 28.2 MB
- 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 27.4 MB
- 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 27.3 MB
- 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 27.2 MB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).mp4 23.5 MB
- 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 23.0 MB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).mp4 22.8 MB
- 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 22.4 MB
- 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 21.6 MB
- 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 21.1 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).mp4 20.2 MB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).mp4 18.3 MB
- 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 17.4 MB
- 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 17.3 MB
- 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 16.4 MB
- 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 15.9 MB
- 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 15.9 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).mp4 15.9 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).mp4 15.9 MB
- 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 15.1 MB
- 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 15.0 MB
- 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 14.9 MB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/Lecture 4 part 1.pdf 8.5 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/Lecture 5 Part 1.pdf 8.3 MB
- 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 8.2 MB
- 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 8.1 MB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/Lecture 4 part 3.pdf 7.1 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/Lecture 5 Part 3.pdf 4.1 MB
- 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/Lecture 3 part 3.pdf 3.9 MB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/Lecture 5 Part 2.pdf 3.7 MB
- 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 3.7 MB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/Lecture 4 part 2.pdf 3.4 MB
- 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 3.3 MB
- 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6.3slides.pdf 2.6 MB
- 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6.2slides_new.pdf 2.4 MB
- 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 2.2 MB
- 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6.1slides.pdf 2.1 MB
- 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/Lecture 2 part 4.pdf 2.1 MB
- 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 2.1 MB
- 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 1.8 MB
- 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 1.7 MB
- 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8.1.pdf 1.6 MB
- 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7.2.pdf 1.5 MB
- 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 1.4 MB
- 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8.3.pdf 1.1 MB
- 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8.2.pdf 865.0 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1.4.pdf 704.0 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1.5-2014.pdf 703.7 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1.2.pdf 605.0 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1.6.pdf 562.3 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1.3.pdf 442.5 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1.1.pdf 338.1 KB
- lectures.html 80.9 KB
- index.html 42.3 KB
- 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 36.2 KB
- 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 33.1 KB
- 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 33.0 KB
- 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 32.7 KB
- 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 32.6 KB
- 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 32.5 KB
- 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 32.1 KB
- 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 31.9 KB
- 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 31.6 KB
- 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 30.2 KB
- 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 30.2 KB
- 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 29.5 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).srt 28.6 KB
- 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 28.3 KB
- 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 28.0 KB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).srt 27.5 KB
- 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 27.2 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).srt 26.9 KB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).srt 25.3 KB
- 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 24.5 KB
- 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 24.3 KB
- 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 22.9 KB
- 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 22.2 KB
- 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 22.1 KB
- 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 22.0 KB
- 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 21.6 KB
- 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 21.5 KB
- 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 21.4 KB
- 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 21.4 KB
- 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 21.2 KB
- 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 21.2 KB
- 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 20.8 KB
- 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 20.0 KB
- 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 19.8 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).srt 19.8 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).srt 19.7 KB
- 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 19.7 KB
- 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 18.9 KB
- 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 18.8 KB
- 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 18.6 KB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).txt 18.2 KB
- 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 18.0 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).txt 17.9 KB
- 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 17.4 KB
- 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).txt 17.3 KB
- 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 16.7 KB
- 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).txt 16.7 KB
- 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 16.6 KB
- 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 16.5 KB
- 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 16.4 KB
- 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 16.3 KB
- 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 15.3 KB
- 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 15.2 KB
- 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 14.2 KB
- compneuro-002-about.json 13.9 KB
- 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 13.9 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).txt 13.2 KB
- 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).txt 13.1 KB
- 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 11.2 KB
- 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 11.0 KB
- 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 11.0 KB
- 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 10.5 KB
- 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 10.2 KB
- 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 8.9 KB
- 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 6.0 KB
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