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Introduction and overview | 1. Introduction of this course | ![]() ![]() |
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overview | Theory of Brain Function | ![]() ![]() |
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overview (1) | Theory of Brain Function | ![]() |
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overview (2) | Theory of Brain Function | ![]() |
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overview (3) | Theory of Brain Function | ![]() |
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Inference | Inference in Perception, Cognition, and Motor Control | ![]() ![]() |
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Inference (1) | Inference in Perception, Cognition, and Motor Control | ![]() |
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Inference (2) | Inference in Perception, Cognition, and Motor Control | ![]() |
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Conventional logic & information | 1. Information flows through molecular sensors 2. Information transformation in sensory-motor pathway |
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Conventional logic & information | 1. Information flows through molecular sensors 2. Information transformation in sensory-motor pathway |
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Frequentist Probability Theory | 1. Importance of Probability and Philosophy 2. Bayesian probability and Frequentist probability |
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Frequentist Probability Theory (1) | 1. Importance of Probability and Philosophy 2. Bayesian probability and Frequentist probability |
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Frequentist Probability Theory (2) | 1. Importance of Probability and Philosophy 2. Bayesian probability and Frequentist probability |
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Jayness Probability Theory | 1. Understanding Bayes theorem 2. Derivation and Application |
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Jayness Probability Theory | 1. Understanding Bayes theorem 2. Derivation and Application |
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Probability and the Brain | 1. Janesian observers 2. B.F Skinner and Behaviorism 3.Theory of Mind |
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Probability and the Brain | 1. Janesian observers 2. B.F Skinner and Behaviorism 3.Theory of Mind |
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Logic in the Brain | 1. Logic as Prescription and Description 2. Sequential logic |
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Logic in the Brain | 1. Logic as Prescription and Description 2. Sequential logic |
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Efficient Coding | 1. Free Energy Principle 2. Baysian inference 3. Efficient coding and mutual information |
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Efficient Coding (1) | 1. Free Energy Principle 2. Baysian inference 3. Efficient coding and mutual information |
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Efficient Coding (2) | 1. Free Energy Principle 2. Baysian inference 3. Efficient coding and mutual information |
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Prediction Error 1: Introduction | 1. A neuron has information about its stimulus 2. Input and Output of Neuron |
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Prediction Error 1: Introduction (1) | 1. A neuron has information about its stimulus 2. Input and Output of Neuron |
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Prediction Error 1: Introduction (2) | 1. A neuron has information about its stimulus 2. Input and Output of Neuron |
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Prediction Error 2: Mechanisms | 1. Prediction error in a single neuron 2. Information and Correlation |
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Prediction Error 2: Mechanisms (1) | 1. Prediction error in a single neuron 2. Information and Correlation |
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Prediction Error 2: Mechanisms (2) | 1. Prediction error in a single neuron 2. Information and Correlation |
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Prediction Error 2: Mechanisms (3) | 1. Prediction error in a single neuron 2. Information and Correlation |
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Theory of Learning | Neurons inputs and Diversity of ion channels | ![]() ![]() |
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Theory of Learning (1) | Neurons inputs and Diversity of ion channels | ![]() |
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Theory of Learning (2) | Neurons inputs and Diversity of ion channels | ![]() |
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Mechanisms of Leaning | Mechanisms for learning and LTP / LTD | ![]() ![]() |
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Mechanisms of Leaning | Mechanisms for learning and LTP / LTD | ![]() |
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Visual System | 1. Physiology of Striate Cortex 2. Mechanism of Forming Receptive fields |
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Visual System | 1. Physiology of Striate Cortex 2. Mechanism of Forming Receptive fields |
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Reward and Attention | Learning to predict reward and 3 term hebbain rule and spike timing depedent plasticity | ![]() ![]() |
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Reward and Attention | Learning to predict reward and 3 term hebbain rule and spike timing depedent plasticity | ![]() |