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    자연과학 >생물ㆍ화학ㆍ환경 >생명과학
  • 강의학기
    2013년 1학기
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    6,035
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This course will introduce the general theory of brain function. It will focus on the organization and flow of information within the nervous system, at the levels of molecules, single neurons, and networks of neurons. The basic biophysical structure and function of the nervous system is now moderately well understood. However, the textbooks that

describe the biology of the nervous system generally do not discuss information, even though it is universally agreed that the nervous system is an information processing system. The course will relate the biophysical structure and function of the nervous system to the processing of information. In doing so, the course will discuss the fundamental principles of the nervous system that should be helpful in designing intelligent machines that are capable of unsupervised learning. The course will include aspects of cellular and systems neurophysiology. Students are expected to have already taken a course that covers basic neurobiology, although past students without a background in neurobiology have done moderately well. Only a minimal knowledge of mathematics is needed.
overview (1)
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1. 문서 Introduction and overview 1. Introduction of this course 소스URL
2. 문서 overview Theory of Brain Function 소스URL
비디오 overview (1) Theory of Brain Function URL
비디오 overview (2) Theory of Brain Function URL
비디오 overview (3) Theory of Brain Function URL
3. 문서 Inference Inference in Perception, Cognition, and Motor Control 소스URL
비디오 Inference (1) Inference in Perception, Cognition, and Motor Control URL
비디오 Inference (2) Inference in Perception, Cognition, and Motor Control URL
4. 문서 Conventional logic & information 1. Information flows through molecular sensors
2. Information transformation in sensory-motor pathway
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비디오 Conventional logic & information 1. Information flows through molecular sensors
2. Information transformation in sensory-motor pathway
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5. 문서 Frequentist Probability Theory 1. Importance of Probability and Philosophy
2. Bayesian probability and Frequentist probability
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비디오 Frequentist Probability Theory (1) 1. Importance of Probability and Philosophy
2. Bayesian probability and Frequentist probability
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비디오 Frequentist Probability Theory (2) 1. Importance of Probability and Philosophy
2. Bayesian probability and Frequentist probability
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6. 문서 Jayness Probability Theory 1. Understanding Bayes theorem
2. Derivation and Application
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비디오 Jayness Probability Theory 1. Understanding Bayes theorem
2. Derivation and Application
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7. 문서 Probability and the Brain 1. Janesian observers
2. B.F Skinner and Behaviorism
3.Theory of Mind
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비디오 Probability and the Brain 1. Janesian observers
2. B.F Skinner and Behaviorism
3.Theory of Mind
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8. 문서 Logic in the Brain 1. Logic as Prescription and Description
2. Sequential logic
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비디오 Logic in the Brain 1. Logic as Prescription and Description
2. Sequential logic
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9. 문서 Efficient Coding 1. Free Energy Principle
2. Baysian inference
3. Efficient coding and mutual information
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비디오 Efficient Coding (1) 1. Free Energy Principle
2. Baysian inference
3. Efficient coding and mutual information
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비디오 Efficient Coding (2) 1. Free Energy Principle
2. Baysian inference
3. Efficient coding and mutual information
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10. 문서 Prediction Error 1: Introduction 1. A neuron has information about its stimulus
2. Input and Output of Neuron
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비디오 Prediction Error 1: Introduction (1) 1. A neuron has information about its stimulus
2. Input and Output of Neuron
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비디오 Prediction Error 1: Introduction (2) 1. A neuron has information about its stimulus
2. Input and Output of Neuron
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11. 문서 Prediction Error 2: Mechanisms 1. Prediction error in a single neuron
2. Information and Correlation
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비디오 Prediction Error 2: Mechanisms (1) 1. Prediction error in a single neuron
2. Information and Correlation
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비디오 Prediction Error 2: Mechanisms (2) 1. Prediction error in a single neuron
2. Information and Correlation
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비디오 Prediction Error 2: Mechanisms (3) 1. Prediction error in a single neuron
2. Information and Correlation
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12. 문서 Theory of Learning Neurons inputs and Diversity of ion channels 소스URL
비디오 Theory of Learning (1) Neurons inputs and Diversity of ion channels URL
비디오 Theory of Learning (2) Neurons inputs and Diversity of ion channels URL
13. 문서 Mechanisms of Leaning Mechanisms for learning and LTP / LTD 소스URL
비디오 Mechanisms of Leaning Mechanisms for learning and LTP / LTD URL
14. 문서 Visual System 1. Physiology of Striate Cortex
2. Mechanism of Forming Receptive fields
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비디오 Visual System 1. Physiology of Striate Cortex
2. Mechanism of Forming Receptive fields
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15. 문서 Reward and Attention Learning to predict reward and 3 term hebbain rule and spike timing depedent plasticity 소스URL
비디오 Reward and Attention Learning to predict reward and 3 term hebbain rule and spike timing depedent plasticity URL

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