TWiki> CogsciTeach Web>PlanningTop (revision 4)EditAttach


  • Tu/Th 1400 (Lecture Theatre 2, Appleton Tower) F 1500 (Room 2.12, Appleton Tower)
    • 30 lectures
    • First lecture 21 September
    • Last lecture 2 December
  • 9 Tutorials
  • 9 Lab

Open Questions

Teaching Assistant


Guest Lecture(rs)

  • Lucky to get
  • 1 person for a run of 3, maybe (from PPLS)

Assessed coursework topics x 3

  • essay vs. practical
    • Collaboration?
    • Mixture in each assignment?
  • topics

Exam Planning

  • content
  • format
  • dummy example


  • topics
    • One (?) continuing topic -- design, execute, assess, model a phenom.
      • Perception? (BW)
      • Collective intelligence
      • Pictionary game (Jon O -- please send me pointers!!!!)
        • Bilateral development of pictures, then into a group
      • Segmentation (Saffran et al.)
      • Use some of the lectures for this too?
  • software

See SyllabusPlanning for topics, lecturer and timetable details


  1. Language -- U-shaped curve -- learning-- synthetic perception D' vs beta -- see LanguageTopic
  2. Memory and attention-- vision--see MemoryTopic
    1. synthesised line boundaries -- Dennett at TED, maybe
    2. Google's PageRank algorithm as a model of human memory
  3. Intro to the brain/ relevant neurology stuff [added by Alyssa]
    1. What are neurons and how do they "work" (trasmit information)
    2. Major brain structures, mostly those relating to our themes (language areas, prefrontal cortex, hippocampus-memory, amygdala if we do emotion, visual cortex)
    3. How this biological stuff relates to models of the brain and neural processes, and how it inspires connectionist models of language learning, memory, etc.
  4. Levels of analysis in cognition
    1. Three levels of analysis/ problem decomposition as described in David Marr's 'Vision." Implementation vs algorithmic level vs conceptual level of a problem. ** This might be a good thing to work through in a tutorial. The original section in Vision is only a few pages long, and very readable. It's a good piece to assign, and there are multiple copies of this book in the library.
    2. Type 1 vs Type 2 problems-- David Marr again, from his 1977 paper "Artificial Intelligence--A Personal View." Also very readbale.

First lecture

  1. McGurk , Gorilla, starting at 14:40
  2. Real brains -- NMR film?
    1. Search -- chess, humans vs. machines
    2. Garden paths
  3. What is cogsci?

This is a test by Mark.

-- HenrySThompson - 25 Aug 2010

Edit | Attach | Print version | History: r8 | r6 < r5 < r4 < r3 | Backlinks | Raw View | Raw edit | More topic actions...
Topic revision: r4 - 01 Sep 2010 - 22:17:39 - AlyssaAlcorn
This site is powered by the TWiki collaboration platformCopyright © by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding TWiki? Send feedback
This Wiki uses Cookies