2. Categorization  How do we organize our knowledge?  How do we retrieve knowledge when we need it?

3. Do We Use Categories? ß Visual agnosias (Warrington & Shallice, 1984) ß Double-dissociation for living and non-living ß Damage to Inferotemporal lobe ß Category-specific neurons in temporal lobe (Kreiman et al., 2000)

4. Levels of Categorization ß Superordinate, Basic, Subordinate ß More features named on Basic level (Rosch et al., 1976) ß Objects tend to be named at the Basic level (Rosch et al., 1976) ß Basic level can depend on knowledge – cultural differences

6. Definitional Approach ß Definitions determine category membership ß But most natural categories do not have defining features ß Elements of a category instead show a “family resemblance”

7. Spreading Activation Model (Collins & Loftus, 1975) ß Concepts are organized in a hierarchy and linked together ß Cognitive Economy ß Spreading Activation

8. Example Of Network ANIMAL eats has skin can move FISH has scales swims has gills BIRD has wings flies has feathers CANARY sings is yellow Tweety is one

9. Spreading Activation Model ß Takes longer to verify statements that require travel over more nodes ß “A canary can fly “ - one node ß “A canary has skin” - two nodes up, takes about 90 ms longer to verify (Collins & Quillian, 1969) ß Faster RT’s to related words in Lexical Decision Task (Meyer & Schvaneveldt, 1975)

10. Hedged Statements ß Statements that are qualified, like: ß Technically, a chicken is a bird. ß A penguin is sort of a bird. ß Loosely speaking, a bat is a bird. ß How do we evaluate these?

11. Prototype Approach (Rosch, 1973) ß Compare object to the prototype of a category ß Prototype is a “typical” example ß Average of examples (Rosch) OR ß Common exemplars (Medin et al., 1982)

12. Prototype Approach ß Typicality Effect in sentence verification (Smith et al., 1974) ß Typicality Effect in priming (Rosch, 1975)

13. Parallel Distributed Processing (Rumelhart & McClelland, 1986) ß Also called Connectionist or PDP ß Memories are patterns of activation among a set of “units” ß Each unit has an activation value ß Connections between units are weighted ß Model can learn (change weights) based on feedback – back propagation

14. PDP Model input units output units hidden units

15. Evolutionary Psychology ß How is categorization adaptive? ß What do fire, women, and dangerous things have in common?