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[Coursera] Computational Neuroscience

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File Name
Size
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
33 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 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 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
31 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 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 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 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 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 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 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 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 MB
04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).mp4
24 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 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
23 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 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
22 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 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 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 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 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 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 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
16 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
16 MB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).mp4
16 MB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).mp4
16 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 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 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
15 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 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1.4.pdf
704 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1.5-2014.pdf
704 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1.2.pdf
605 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 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1.3.pdf
442 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1.1.pdf
338 kB
lectures.html
81 kB
index.html
42 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 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 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 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
33 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
33 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 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 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
32 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
32 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 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 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
30 kB
01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).srt
29 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 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 kB
04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).srt
28 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 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).srt
27 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 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 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 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
23 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 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 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 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
22 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
22 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 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 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 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 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
21 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 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
20 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).srt
20 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).srt
20 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
20 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
19 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
19 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
19 kB
04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).txt
18 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 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).txt
18 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 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 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
17 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
17 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
17 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 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 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 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 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 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 kB
compneuro-002-about.json
14 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
14 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).txt
13 kB
05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).txt
13 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 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 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 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 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 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
_README.txt
2.4 kB