Brains, Minds and Machines Summer Course

Topics

• Introduction to the study of intelligence in brains, minds and machines
• Introduction to human cognitive neuroscience
• Computational roles of feedback and recurrent connections in visual cortex
• Neural mechanisms underlying visual object recognition: The convergence of computer vision and biological vision (Part 1)
• Neural mechanisms underlying visual object recognition: The convergence of computer vision and biological vision (Part 2)
• Of primates, faces, and intelligence
• Hippocampus, memory, and sleep (Part 1)
• Hippocampus, memory, and sleep (Part 2)
• A mind in the fly brain
• Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 1)
• Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 2)
• Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 3)
• Cognition in infancy (Part 1)
• Cognition in infancy (Part 2)
• Developing an understanding of communication
• Children’s sensitivity to the cost and value of information
• Infants’ sensitivity to cost and benefit
• The child as scientist
• Debate: Theories, imagination, and the generation of ideas
• From simple innate biases to complex visual concepts
• Atoms of recognition in human and computer vision
• Predicting visual memory: Behavioral, neuroscience, and computational accounts
• Probing sensory representations with metameric stimuli
• Computer vision, wearable computing, and the future of transportation
• Vision and language
• From language to vision and back again
• The story understanding story: The truth about human intelligence
• Neural representations of language meaning
• Social intelligence
• The social mind
• MVPA: Opening a new window on the mind via fMRI (Part 1)
• MVPA: Opening a new window on the mind via fMRI (Part 2)
• Introduction to biological audition (Part 1)
• Introduction to biological audition (Part 2)
• Functional specialization in human auditory cortex
• Auditory perception in speech technology (dealing with unwanted information) (Part 1)
• Auditory perception in speech technology (dealing with unwanted information) (Part 2)
• Similarities and differences between hearing and vision, with Alex Kell (moderator), Josh Tenenbaum, Hynek Hermansky, Josh McDermott, Gabriel Kreiman, Dan Yamins
• MIT’s entry in the DARPA robotics challenge
• Mapping, localization, and self-driving vehicles
• Layered control architecture in mammals and robots
• Human-robot collaboration
• iCub: An open source platform for research in robotics & AI
• Future research directions in robotics and motor control in biological systems, with Patrick Winston (moderator), John Leonard, Giorgio Metta, Stefanie Tellex, Tony Prescott, Russ Tedrake
• iTheory: Visual cortex and deep networks
• The statistical physics of deep learning
• Sensory representations in cortex-like deep architectures
• Basic neuroscience
• MATLAB ® programming (* with additional content development by Ellen Hildreth)
• Machine learning
• Neural decoding
• Church programming
• Amazon Mechanical Turk