├── README.md ├── Week-0 └── README.md ├── Week-1 ├── Programming-Quizzes │ ├── MATLAB │ │ ├── README.md │ │ ├── solution-1.md │ │ ├── solution-10.md │ │ ├── solution-11.md │ │ ├── solution-12.md │ │ ├── solution-13.md │ │ ├── solution-14.md │ │ ├── solution-2.md │ │ ├── solution-3.md │ │ ├── solution-4.md │ │ ├── solution-5.md │ │ ├── solution-6.md │ │ ├── solution-7.md │ │ ├── solution-8.md │ │ └── solution-9.md │ ├── Python │ │ ├── README.md │ │ └── Solutions │ │ │ ├── 1.md │ │ │ ├── 10.md │ │ │ ├── 11.md │ │ │ ├── 12.md │ │ │ ├── 13.md │ │ │ ├── 14.md │ │ │ ├── 2.md │ │ │ ├── 3.md │ │ │ ├── 4.md │ │ │ ├── 5.md │ │ │ ├── 6.md │ │ │ ├── 7.md │ │ │ ├── 8.md │ │ │ └── 9.md │ └── README.md ├── notes │ ├── 1- overview.md │ ├── 2 - Computational NeuroScience: Descriptive Models.md │ ├── 3 - Computational NeuroScience: Mechanistic and Interpretive Models.md │ └── 4-NeuroBiology-101 │ │ ├── 4-1-Neurons.md │ │ ├── 4-2-Synapses.md │ │ ├── 4-3-Nervous System and Brain regions.md │ │ ├── 4-4-Conclusion.md │ │ └── README.md └── shared │ ├── acronyms.md │ └── lecture.md ├── Week-2 ├── Quiz │ ├── Programming │ │ ├── questions │ │ │ ├── 1.md │ │ │ ├── 2.md │ │ │ ├── 3.md │ │ │ └── 4.md │ │ ├── resources │ │ │ └── references.md │ │ ├── shared_codes │ │ │ ├── Python │ │ │ │ ├── compute_sta.py │ │ │ │ └── quiz2.py │ │ │ ├── README.md │ │ │ └── matlab │ │ │ │ ├── README.md │ │ │ │ ├── compute_sta.m │ │ │ │ └── quiz2.m │ │ └── solutions │ │ │ ├── README.md │ │ │ └── mathlab │ │ │ ├── compute_sta.m │ │ │ ├── output.md │ │ │ └── quiz2.m │ ├── README.md │ └── Theory │ │ ├── 1.md │ │ ├── 2.md │ │ ├── 3.md │ │ ├── 4.md │ │ └── 5.md ├── notes │ ├── 1 - Overview.md │ ├── 2- What is the Neural code?.md │ ├── 3-Neural Coding : Simple Models.md │ ├── 4 - Neural coding : Feature Selection.md │ └── 5 - Neural Coding : Variability.md └── shared │ └── resources.md ├── Week-3 ├── notes │ ├── notes │ │ ├── 1 - Neural Decoding and Signal Detection Theory.md │ │ ├── 2 - Population Coding and Bayesian Estimation.md │ │ ├── 3 - Reading minds : Stimulus Reconstruction.md │ │ └── guest-lecture.md │ └── shared │ │ └── resources.md └── requirements.txt ├── Week-4 ├── Quiz │ ├── Programming │ │ ├── 1.md │ │ ├── 2.md │ │ ├── 3.md │ │ ├── MATLAB │ │ │ └── README.md │ │ ├── Python │ │ │ └── README.md │ │ └── plotting │ │ │ ├── README.md │ │ │ └── output.md │ ├── README.md │ └── Theory │ │ ├── 1.md │ │ ├── 10.md │ │ ├── 2.md │ │ ├── 3.md │ │ ├── 4.md │ │ ├── 5.md │ │ ├── 6.md │ │ ├── 7.md │ │ ├── 8.md │ │ └── 9.md └── notes │ ├── notes │ ├── 1 - Information and Entropy.md │ ├── 2 - Calculating Information in Spike Trains.md │ └── 3 - Coding Principles.md │ └── shared │ └── resources.md ├── Week-5 ├── notes │ ├── notes │ │ ├── 1 - Modeling Neurons.md │ │ ├── 2 - Spikes.md │ │ ├── 3---Simplified-Modeled-Neurons │ │ │ ├── 1 - overview.md │ │ │ ├── 2 - introduction.md │ │ │ ├── 3 - Capturing the basic dynamics of neurons.md │ │ │ ├── 4 - Two-dimensional models.md │ │ │ └── 5 - The Simple Model.md │ │ ├── 4 - A forest of dendrites.md │ │ └── README.md │ └── shared │ │ └── resources.md └── quiz │ └── README.md ├── Week-6 ├── README.md └── notes │ ├── notes │ ├── 1 - Modelling connections between neurons.md │ ├── 2 - Introduction to network models.md │ └── 3 - The World of Recurrent networks.md │ └── shared │ └── resources.md ├── Week-7 ├── notes │ ├── notes │ │ ├── 1 - LTP and LTD.md │ │ ├── 2 - Hebb's rule.md │ │ ├── 3 - Covariance rule.md │ │ ├── 4 - Analyzing learning rules.md │ │ ├── 5 - Oja's Rule.md │ │ ├── 6 - Summary of Hebbian Learning.md │ │ ├── 7 - Statistical Learning.md │ │ ├── 8 - Introduction to unsupervised learning.md │ │ ├── 9 - Sparse coding and Predictive coding.md │ │ └── README.md │ └── shared │ │ └── resources.md └── quizzes │ ├── README.md │ └── programming │ ├── alpha_neuron.m │ └── alpha_neuron.py ├── Week-8 ├── notes │ ├── notes │ │ ├── 1 - Neurons as Classifiers and Supervised Learning.md │ │ ├── 2 - Reinforcement learning: Predicting 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