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Lecture 7 Semantic Memory
OBJECTIVES
Describe and evaluate key theories of semantic memory organisation – how information is stored and
represented in memory?
1
...
Scripts and Schemas (Going to a restaurant – enter – sit at a table – look at the menu etc
...
g
...
g
...
g
...
g
...

o

A chair must have these defining features (can also have additional features, e
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made of wood)

o

If it has these necessary features then together the features are sufficient for it to be classed as a chair

o

Defining features capture the meaning of a concept

o

Features are ‘primitives’, ie
...
= Feature of

SPREADING ACTIVATION
When a concept (node) is activated, this activation spreads to other related nodes in the semantic network…
...

How do we make semantic judgements, e
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do canaries breathe?
Activation spreads out from both ‘can breathe’ and ‘canary’ - travelling from one node to another via
connections
...

These two sources of activation intersect suggesting a possible relation between the two concepts - this
intersection triggers decision stage to verify the relation
We can predict how long it takes for different types of semantic judgements
...
If two nodes near to each other, quick time for
an answer

TESTING COLLINS AND QUILLIAN’S PREDICTIONS
1
...
g
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Canary is a canary - 0 Levels (just activate the canary node)
B
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Canary is an animal – 2 Levels (has to spread through two connections)
Supports connections
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Sentence verification tasks, e
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instance – feature
Which leads to the quickest answer?
-

Does a canary breathe?
Is a canary yellow?
Can a canary fly?

Processing:
A
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Canary can fly – 2 Levels
C
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g
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g
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g
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g
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g
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Not all features are equal (Conrad, 1972) - some features are more closely associated with a concept
than others, e
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robin has red breast vs
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Not all instances are equal (Rosch, 1973)
is a more typical bird than an ostrich

some are ‘better’ (more typical) than others, e
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a robin

TYPICALITY EFFECT (Smith et al
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Hard to establish defining features
hard to find a set of features that defines membership and
excludes nonmembers, e
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Wittgenstein (1953)
What are the defining features of ‘GAMES’? What links all games together (e
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football, chess, hide & seek,
etc
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Differences between categories should be clear-cut but aren’t - fuzzy categorical boundaries rather
than clearly defined ones (McClosky & Glucksberg, 1978)
People agree with others, and are consistent across sessions, about:



Category – Typical instances, e
...
FRUIT – apple
Category – Unrelated instances, e
...
FRUIT – dog

But, do not agree (with others or themselves) about:
 Category – Atypical instances, e
...
FRUIT – tomato
should not have these fuzzy boundaries if they are supposed to be clear-cut definitions and categories
5
...
1974)
People are faster to verify OSTRICH – ANIMAL than OSTRICH – BIRD
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FEATURE COMPARISON MODEL (SMITH ET AL
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Two types of features:
1
...
g
...
Characteristic Features – features that some instances have, but not all – not essential (e
...
bird – can
fly)
1- or 2-Stage Processing Mechanism for judging similarity between an instance and a category (e
...
Robin –
Bird)…

1- OR 2-STAGE PROCESSING MECHANISM
Stage 1 – rapid, general comparison of the features (defining characteristic) of both concepts
Robin – Bird

High Similarity

YES (rapid response) If there is a match

Chair – Bird

Low similarity

NO (rapid response)

Bat – Bird

Intermediate

?

Stage 2 – slow, careful comparison of defining features only (ignore characteristic features)
Bat – has teeth and fur
= NO MATCH
Bird – has beak and feathers

EVALUATION OF FEATURE COMPARISON
Strengths
1
...
e
...
g
...
g
...
g
...
Copes with some issues of hierarchical organisation
People are FASTER to verify OSTRICH – ANIMAL than OSTRICH – BIRD
Ostrich – Bird
Ostrich - Animal

Hierarchical Levels
1
2

Stages of Processing
2
1

Ostrich is more similar to an Animal (is alive, has skin, breathes) than a Bird (can fly)

Problems
1
...
Treats features in isolation - doesn’t explain how features relate to each other (e
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having wings &
flying go together)
...

3
...
G
...
g
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Proposes that instances of a category vary in closeness to the central prototype – i
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their typicality
Therefore accounts for typicality effects, e
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typical instances are classified faster than atypical (robin/bird
vs
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Allows for fuzzy category boundaries – not always a clear distinction between categories, e
...
Labov
(1973)

Ask whether a cup or a bowl
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Allows for family resemblance:
 Category membership depends on similarity rather than definition
 There is no (defining) feature that is shared by all instances of a concept
 But all instances have some features in common with the prototype
The Smith Brothers (Armstrong et al
...
269)
Middle brother is a composite of all of the brothers – there is not one defining feature of all of them

Prototype theory still has problems accommodating/explaining:
1
...
g
...
People know about relations between attributes, e
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wings and flying – not captured by the
representation of a single prototype
3
...
g
...
exemplars see Medin (1989) on the reading list

EVALUATION
Semantic categorisation may involve different approaches:
-

Prototype approach may be best for some categories, e
...
those with many members (e
...
animals)
Exemplar approach may be more appropriate for other categories, e
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smaller categories or
categories we have little experience of

Semantic memory is not just about simple concepts and categories
...
g
...
g
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General information about our own traits, attitudes, abilities, goals, etc…
2
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e
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we’re more likely to remember self-relevant information than info about other people (e
...

Kendzierski, 1980)
4
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g
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e
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g
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g
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g
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g
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g
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Instrument for measuring atmospheric pressure
2
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A tube with mirrors that allows the observer to see what is above their head
ToT experience often marked by a strong ‘Feeling of knowing’ – can recall some aspects (e
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1st letter, number
of syllables) but not the complete name
Numerous explanations of the ToT phenomenon, e
...
Semantic information is activated but activation hasn’t
spread to the phonological information needed to produce the word

SUMMARY
There are numerous explanations of how we represent and organize semantic knowledge:
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Defining feature Theory (strengths and weaknesses)
Feature comparison theory (strengths and weaknesses)
Prototype theory (strengths and weaknesses)

Scripts and schemas – organise knowledge about everyday events



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