This course explores the problem of intelligence—its nature, how it is produced by the brain and how it could be replicated in machines—using an approach that integrates cognitive science, which studies the mind; neuroscience, which studies the brain; and computer science and artificial intelligence, which study the computations needed to develop intelligent machines. Materials are drawn from the Brains, Minds and Machines Summer Course offered annually at the Marine Biological Laboratory in Woods Hole, MA, taught by faculty affiliated with the Center for Brains, Minds and Machines headquartered at MIT. Elements of the summer course are integrated into the MIT course, 9.523 Aspects of a Computational Theory of Intelligence.
Contributors
This course includes the contributions of many instructors, guest speakers, and a team of iCub researchers. See the complete list of contributors.
Contents
Lesson 1: Neural Circuits of Intelligence
Lesson 1.1: Human Cognitive Neuroscience
Lesson 1.2: Computational Roles of Neural Feedback
Lesson 1.3: Neural Mechanisms of Recognition Part 1
Lecture 1.4: Neural Mechanisms of Recognition Part 2
Lesson 1.5: Primates, Faces, & Intelligence
Lesson 1.6: Hippocampus, Memory, & Sleep Part 1
Lecture 1.7: Hippocampus, Memory, & Sleep Part 2
Seminar 1: Mind in the Fly Brain
Lesson 1: Further Study
Lesson 2: Modeling Human Cognition
Lesson 2.1: Computational Cognitive Science Part 1
Lesson 2.2: Computational Cognitive Science Part 2
Lesson 2.3: Computational Cognitive Science Part 3
Lesson 2: Further Study
Lesson 3: Development of Intelligence
Lesson 3.1: Cognition in Infancy Part 1
Lesson 3.2: Cognition in Infancy Part 2
Lesson 3.3: Developing an Understanding of Communication
Lesson 3.4: Childrens’ Sensitivity to Cost and Value of Information
Seminar 3: Infants’ Sensitivity to Cost and Benefit
Lesson 3.5: The Child as Scientist
Lesson 3 Debate: Tomer Ullman & Laura Schulz
Lesson 4: Visual Intelligence
Lesson 4.1: Development of Visual Concepts
Lesson 4.2: Atoms of Recognition
Lesson 4.3: Predicting Visual Memory
Seminar 4.1: Probing Sensory Representations
Seminar 4.2: Applications of Vision
Lesson 4: Further Study
Lesson 5: Vision and Language
Lesson 5.1: Vision and Language
Lesson 5.2: From Language to Vision and Back Again
Lesson 5.3: Story Understanding
Seminar 5: Neural Representations of Language
Lesson 5: Further Study
Lesson 6: Social Intelligence
Lesson 6.1: Introduction to Social Intelligence
Lesson 6.2: The Social Mind
Lesson 6.3: MVPA: Window on the Mind via fMRI Part 1
Lecture 6.4: MVPA: Window on the Mind via fMRI Part 2
Lesson 6: Further Study
Lesson 7: Audition and Speech
Lesson 7.1: Introduction to Audition Part 1
Lesson 7.2: Introduction to Audition Part 2
Lesson 7.3: Human Auditory Cortex
Lesson 7.4: Auditory Perception in Speech Technology Part-1
Lesson 7.5: Auditory Perception in Speech Technology Part-2
Lesson 7 Panel: Vision and Audition
Lesson 7: Further Study
Lesson 8: Robotics
Lesson 8.1: MIT’s Entry in the DARPA Robotics Challenge
Lesson 8.2: Mapping, Localization, & Self-Driving Vehicles
Lesson 8.3: Control Architecture in Mammals and Robots
Lesson 8.4: Human-Robot Collaboration
Lesson 8.5: Introduction to the iCub Robot
Lesson 8.6: Overview of Research on the iCub Robot
Lesson 8 Panel: Robotics
Lesson 8: Further Study
Lesson 9: Theory of Intelligence
Lesson 9.1: Visual Cortex & Deep Networks
Seminar 9: Statistical Physics of Deep Learning
Lesson 9.2: Sensory Representations in Deep Networks
Lesson 9: Further Study
Tutorial 1: Basic Neuroscience
Tutorial 1.1: Introduction to Visual Neuroscience
Tutorial 1: Further Study
Tutorial 2: MATLAB Programming
Tutorial 2: Further Study
Tutorial 3: Machine Learning
Tutorial 3.1: Machine Learning Tutorial Part 1
Tutorial 3.2: Machine Learning Tutorial Part 2
Tutorial 3.3: Machine Learning Tutorial Part 3
Tutorial 3: Exercises and Further Study
Tutorial 4: Neural Decoding
Tutorial 4.1: Understanding Neural Content via Population Decoding
Tutorial 4: Further Study
Tutorial 5: Church Programming
Tutorial 5.1: Church Programming Language Part 1
Tutorial 5.2: Church Programming Language Part 2
Tutorial 5: Code and Further Study
Tutorial 6: Amazon Mechanical Turk
Tutorial 6.1: Amazon Mechanical Turk
Tutorial 6: Further Study
