September 1998HKU Propositional Representation In what language is information “written” in our heads? Is it in the same language we speak? Why is it that we sometimes have tip- of-the-tongue phenomenon? Why do we sometimes feel we cannot put our thoughts into words?

September 1998HKU Language of Thought Sachs (1967) found that people confuse different sentences with the same meaning more than similar sentences with different meaning. e.g., Galileo, the great Italian scientist, was sent a letter about it. A letter about it was sent to Galileo, the great Italian scientist. Galileo, the great Italian scientist, sent him a letter about it.

September 1998HKU Empirical Evidence The exact words of a representation are quickly lost while the meaning is maintained. Priming and fan-effect found, supporting the theory that we have propositional networks. (McKoon & Ratcliff, 1980)

September 1998HKU Propositional Networks If propositions are connected into networks through associative connections, then we would expect spreading of activation. Subjects read two stories. They were then given word lists and asked to indicate whether they belong to Story 1. They were faster if the words were preceded by another word from Story 1 than by a word from Story 2.

September 1998HKU Priming and Fan-effect Priming Fire-Engine Bread Fire-Engine Butter Butter Apple slower faster faster

September 1998HKU Fan-effect Increasing the number of propositions in which a particular component appears increases response time for that component. (Pirolli and Anderson, 1985) e.g., The doctor is in the bank The accountant is in the park The lawyer is in the park

September 1998HKU Difficulties with Propositions There is evidence for a propositional language of thought, but it is clearly not the whole picture: –How do propositional networks capture meaning? –How are causal sequences represented?

September 1998HKU Schematic Representation Schemas are an attempt to capture the interdependence of propositions. We have schemas for common objects and events that are inter- related clusters of properties and category relationships.

September 1998HKU Properties and Categories Dog: –Animal<-- CATEGORY –Mammal<-- CATEGORY –Four legs –Barks –Furry –Tail wags –Poodle <-- CATEGORY

September 1998HKU Schemas Schemas are general, abstracted representations that excluded details about specific instances of objects. Describe the general category instead. e.g., schema for a person, room...

September 1998HKU Scripts Shank and Abelson (1977) e.g. restaurant gas Station birthday party

September 1998HKU Evidence for Scripts Evidence: Bower, Black, and Turner (1979) had people read stories such as about going to the doctor. They then asked subjects questions about the story. Found that subjects infer events that were not in the story based on their own scripts.

September 1998HKU Evidence for Schemas Person Schemas: we use personality categories to classify people and these often lead us to infer properties that aren’t present. e.g., Cantor and Mischel,1979 gave subjects mild characteristics of personality types (like extrovert). Subjects later recalled the more strong, typical ones.

September 1998HKU Schema What objects are in this office? Brewer & Treyens, 1981

September 1998HKU Schemas and memory Subjects spent less than a minute in the room. Most recalled a chair and a desk. About 1/3 recalled books.

September 1998HKU Schemas, Scripts and Propositions Scripts and schemas are not easily represented as a bunch of associated propositions. Propositions aren’t very good at representing sequences, such as those in much of our episodic knowledge (in contrast to declarative knowledge).