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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

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Knowledge

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Knowledge l.jpg

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


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Face

recognition

Inferences

If x and y then z

If 4 legs and barks=dog


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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?


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hierarchy

rule based

automatic

Abstract,

verbal statements

Literal,

spatial relations

15.00

gills+scales+tail+fin=


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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


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ambiguous


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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


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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


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Predictions of DFT

reptiles,

Crawling animals

fish

gills+scales+tail+fin

amphibious creatures


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Typicality effects

More typical fish


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Fuzzy boundaries

A fish?

Fruit or vegetable?


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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


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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


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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


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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.


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defining features

nodes

This is a type of distributed network


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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 birdcan fly1

    A canary is an animalhas flesh2

    A canary is a fishhas gillsfalse


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Main effect of

number of levels =

concept structure


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Neuropsychological evidence

Temporal lobe


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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.


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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


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Thompson-Schill, et al (1999)

Living things

Non-living things


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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.


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