Knowledge

1. AIMS & OBJECTIVES: The aim of this lecture is to review current approaches to understanding knowledge At the end of the lecture you will have learned What is meant by the term propositional knowledge The difference between a category and a prototype Typicality effects Taxonomic categories CORE READING: Parkin, A. (2000). Essential Cognitive Psychology. Psychology Press, Chapter 8. SUPPLEMENTARY READING: Larochelle S, et al., (2000). What some effects might not be: The time to verify membership in "well-defined'' categories. Quarterly Journal of Experimental Psychology-A, 53(4), 929-961. Knowledge

2. Face recognition Inferences If x and y then z If 4 legs and barks=dog

3. External representations Turtle Oldest living creature Buries eggs etc.. Internal representations Store of facts (LTM). Allows language etc.. Also, allows us to make inferences about the external environment. This enables us to solve novel problems (1+4=5) Adaptive and productive. What is knowledge?

4. hierarchy rule based automatic Abstract, verbal statements Literal, spatial relations 15.00 gills+scales+tail+fin=

5. We do not encode all objects encountered in everyday events. We categorise each object as an exemplar of a “type” on the basis that it shares featurese.g. a turtle an amphibious creature long living slower than a hare. Abstract common features form a category. A category is a class or description of objects or events with common attributes and the members of categories are called instances. People tend to think in taxonomiccategories Furniture, vegetable.. Exemplars and categories

6. ambiguous

7. Categories and concepts Literal= perceptual boundaries • Concepts are categories of mental representations stored in LTM memory. • Concepts are used to perceive, store, act on and communicate about objects and events -> false memories. • How are conceptual categories represented in the human mind? Abstract= independent of form

8. Concepts defined by necessary and sufficient attributes. An instance is a member of a conceptual category only if it meets minimal properties e.g., a triangle a two dimensional geometric figure with three straight sides joined at their ends with angles adding up to 180o Prediction: DFT assumes clear boundaries between members and non-members of a category. All members of category should be equallyrepresentative of the conceptual category. All people should represent categories in the same way. BUT category boundaries are not clearly defined or discrete. Typicality effects. Defining feature theory

9. Predictions of DFT reptiles, Crawling animals fish gills+scales+tail+fin amphibious creatures

10. Typicality effects More typical fish

11. Fuzzy boundaries A fish? Fruit or vegetable?

12. Typicality effects (1975, JEP, 104, 192-233). People tend to decide that some instances are better members than others. Most typical furniture chair vase drapes Instances are not literally defined as members of a category on basis of logic. Instances have an internal abstract relative structure. This structure needs an organising principle. Eleanor Rosch

13. Conceptual categories are represented by a prototype. A prototype is a composite or abstraction of features. This combines all of the characteristics of the most typical members of a category (fruit - seeds, edible). Categorisation tasks Is this a fish? This is based on overall similarity of an exemplar to the abstract prototype rather than on the features of the items themselves. This theory explains the typicality effect because not all instances precisely resemble the prototype. Rosch’s prototype theory

14. How are representations of knowledge arranged in LTM Collins and Quillian (1969) taxonomies. Knowledge about biological forms is organised in a hierarchy. General concepts are at the apex and specific concepts are at the base. The superordinate level is the most inclusive category e.g., animal. The superordinate category subsumes more specific subordinate categories e.g., category “animals” birds, fish etc canary, ostrich, shark, salmon Network Theory

15. Network Theory • Individual concepts are called nodes and these are represented by definitions based on a set of properties. • Subordinate categories can ‘inherit’ the properties of a superordinate category. • This makes categories very economical and allows us to draw inferences.

16. defining features nodes This is a type of distributed network

17. Prediction • Sentence verification YES/NO for semantic category decisions should be a function of the number of levels that need to be passed to answer a question. • CategoryPropertyLevels A canary is a canary can sing 0 A canary is a bird can fly 1 A canary is an animal has flesh 2 A canary is a fish has gills false

18. Main effect of number of levels = concept structure

19. Neuropsychological evidence Temporal lobe

20. Category specific agnosia “animal” • Warrington and Shallice (1984) reported a patient JBR who had visual agnosia. • JBR had a selective deficit when asked to name pictures from the semantic category living things (e.g., animals) but no impairment with non-living things and patient YOT shows the reverse pattern.

22. Patients with dementia seem to lose subordinate information (e.g. canary) before superordinate name (e.g. animal) on tests of concept knowledge. Data consistent with idea of hierarchical knowledge in semantic memory that supports Collins model. Evidence from brain imaging suggests category specific regions in the brain (e.g. Thompson-Schill, 1999). Neuropsychological evidence

23. Thompson-Schill, et al (1999) Living things Non-living things

25. Summary • Prototype theory assumes categories are represented by exemplars and there is some evidence in support. • Neuropsychological data suggests knowledge about the world is represented in taxonomic categories in a distributed brain network.