semantic memory memory for meaning permanent memory store of general world knowledge mental...

Semantic Memory

Memory for meaning

Permanent memory store of general world knowledge

Mental thesaurus, dictionary, or encyclopedia

Language, concepts, decisions, etc.

Whereas episodic memory differs widely from individual to individual, semantic memory is similar across individuals

Two Models of Semantic Memory

Collins and Quillian Network Model

Smith Feature Comparison Model

Each makes two assumptions of semantic memory:

1) Structure

2) Process of retrieval

Collins and Quillian Network Model

Two fundamental assumptions of semantic memory:

Structure: Nodes in a network

Process of retrieval: Spreading activation

Collins and Quillian Network Model

Structure: Nodes in a network

Each concept in semantic memory is represented by a node, a point or location in semantic space

Collins and Quillian Network Model

Structure: Nodes in a network

Each concept in semantic memory is represented by a node, a point or location in semantic space.

Collins and Quillian Network Model

Structure: Nodes in a network

Nodes are linked together by pathways, directional associations between concepts. Every concept is related to every other concept.

Collins and Quillian Network Model

Structure: Nodes in a network

Each pathway has a label defining the relationship between the concepts: Isa statements and property statements form propositions

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

An individual concept becomes activated

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

This activation spreads to adjacent nodes, activating them as well

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

Activation continues to spread through the network, but the level of activation decreases with each “step”

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

Consider the activation caused by “Can a robin can breathe?”

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

The nodes ROBIN and BREATHE spread activation through the network.

Collins and Quillian Network Model

Process of Retrieval: Spreading Activation

The intersection of two spreads of activation is found indicating critical concepts; a decision stage operates to determine validity of intersection

Smith’s Feature Comparison Model

Two fundamental assumptions of semantic memory:

Structure: Feature lists

Process of retrieval: Feature comparison

Smith’s Feature Comparison Model

Structure: Feature Lists

Semantic memory is a collection of Feature Lists

Each concept represented as a list of semantic features: simple, one-element characteristics of the concept

Features are ordered in a list in terms of definingness: The most defining features for a concept are at the top of the list

Smith’s Feature Comparison Model

Structure: Feature Lists

Defining features: Features absolutely essential to the concept (e.g. Birds are living objects)

Characteristic features: Features common to, but not essential to, a concept’s meaning (e.g. Birds fly)

Smith’s Feature Comparison Model

Process of Retrieval: Feature Comparison

General example: True or false: “An A is a B”?

Stage 1: Global Feature Comparison

Access required concepts and randomly select features about each concept

Features compared and similarity score determined

High: “Yes”, Low: “No”, or Intermediate: Go to Stage 2

Smith’s Feature Comparison Model

Process of Retrieval: Feature Comparison

General example: True or false: “An A is a B”?

Stage 2: Comparison of Defining Features

Access defining features of each concept

Determine if defining features match

Features match: “Yes”

Features mismatch: “No”

Smith’s Feature Comparison Model

Process of Retrieval: Feature Comparison

Clashing Evidence for the Models

General Task: Sentence Verification

Key issues:

Cognitive Economy

Property Statements

Typicality Effects

Clashing Evidence for the Models

Cognitive Economy (Bad for: C & Q; Good for: S)

Bird

Robin

Wings

Feathers

Red Breast

Blue Eggs

Bird

Robin

Wings

Feathers

Wings

Feathers

Clashing Evidence for the Models

Property Statements (Bad for: S; Good for: C & Q)

E.g.: A canary is a small bird with yellow wings

According to Smith: Look up feature lists for five concepts CANARY, BIRD, SMALL, YELLOW, and WINGS

This requires a list of “Things that are small”; “Things that are yellow”; “Things with wings”

Collins & Quillian incorporate property statements into their network so it doesn’t face this problem

Clashing Evidence for the Models

Typicality Effects (Bad for: C & Q; Good for: S)

Not all members of a category are equal

Typical members of a category can be judged faster

This is captured with Smith’s similarity score but not explained by Collins & Quillian:

Bird Chicken

Penguin

Robin

Sparrow

A Hybrid Model

No strict cognitive economy

Property statements available

Typical members of a category stored more closely

Properties more important to concept stored more closely

A Final Wrinkle

Recent ERP research is now suggesting that RT effects (e.g. typicality effects) in semantic memory may be associated with decision processes rather than retrieval processes

What’s the problem? Such effects have lead to model revisions that add semantic distance between nodes (e.g. the hybrid model just described.) Such revisions may not be appropriate.

Current models of semantic memory have yet to adequately address this finding

Categorization

Concept Formation

Traditional Research:

Show subjects a series of arbitrary patterns and have them judge whether each is an example of the concept being tested.

Limitations are that they are not related to the real world

Categorization

Natural Categories

Concepts and categories that occur in the real world

Members do not belong to their categories in simple yes/no fashion

Categories have fuzzy boundaries with ill-defined membership for many category instances

No single feature is absolutely necessary as a criterion of category membership

Membership in a category is a matter of degree

Back to Spreading Activation

Four important principles associated with this idea:

1) Activation spreads

2) Spreading takes time

3) Activation becomes diffuse as it spreads

4) Activation decays over time

If semantic relatedness is the organizing principle of semantic memory, then relatedness should play a big role in these principles

The test: Priming

Priming in Semantic Memory

In essence: How does the processing of a prime affect the processing of a target?

Does thinking about one concept “bring to mind” other concepts? If so, they are “connected” in semantic memory

Priming in Semantic Memory

How can we use this to test the association between semantic relatedness and spreading activation?

- Distance of spread

- Speed of spread

Priming in Semantic Memory

Distance of Spread: Vary “steps” between prime and target

STIMULUS 1: ROBIN

Activation added to Robin

Priming in Semantic Memory

Distance of Spread: Vary “steps” between prime and target

STIMULUS 1: ROBIN

Activation spreads through

network

Priming in Semantic Memory

Distance of Spread: Vary “steps” between prime and target

STIMULUS 2: BIRD

Does activation get this far?

Priming in Semantic Memory

Distance of Spread: Vary “steps” between prime and target

STIMULUS 2: FEATHERS

Does activation get this far?

Priming in Semantic Memory

Distance of Spread: Vary “steps” between prime and target

STIMULUS 2: BREATHES

Does activation get this far?

Priming in Semantic Memory

Speed of Spread: Vary time between prime and target

How long does it take activation to go from Robin to

Bird?

Priming in Semantic Memory

There are two major ways to set up these experiments:

Empirical Demonstrations of Priming

Freedman and Loftus (1971)

Name a member of a category defined by a prime and a target

Conclusion: Category faster than letter or color

Prime Target Result

P Fruit No Priming

Red Fruit No Priming

Fruit P Priming

Fruit Red Priming

Empirical Demonstrations of Priming

Loftus and Loftus (1974)

Same methodology as Freedman & Loftus

Difference: Trials have various SOAs (within trials) and sometimes repeated the category of a previous trial (across trials)

TRIAL 1 TRIAL 2 TRIAL 3 TRIAL 4

Lag 0: Fruit-P Fruit-B Animal-D Building-L

Lag 2: Fruit-P Animal-D Building-L Fruit-B

Empirical Demonstrations of Priming

Loftus and Loftus (1974)

Empirical Demonstrations of Priming

Loftus and Loftus (1974)

Within trials: Category more facilitation than letter or color

Across trials: Facilitation less at longer lags

SOAs: Facilitation better at longer SOAs

Empirical Demonstrations of Priming

Rosch (1975)

Are two things members of the same category?

Prime: Category name (related) or “Blank” (neutral)

Targets: Typical or atypical category members

RobinSparrow

PenguinOstrich

BIRD

BIRD

TroutSparrow

BLANK No priming

Less priming

Lots of priming

Empirical Demonstrations of Priming

Meyer and Schvaneveldt (1971)

Lexical Decision Task

Empirical Demonstrations of Priming

Neely (1977)

Insert figure 7-13

Empirical Demonstrations of Priming

Neely (1977)

At small SOAs, there is facilitation between related words even tough it is unexpected.

At larger SOAs, this facilitation disappears.

Empirical Demonstrations of Priming

Marcel (1980)

Immediately after prime, present a mask

Prevents conscious awareness of seeing prime

Even without conscious awareness, prime affects target

Child Infant

Summary of Priming

Related primes speed processing: Activation spreads from one concept to another

Reduced relatedness or typicality of concepts decreases priming: Activation spreads to most related concepts

Longer SOAs increase priming: Spreading activation takes time

Summary of Priming

Longer lags decrease priming: Activation decays

Priming at very short SOAs and despite conscious expectations: Priming is automatic

Priming occurs without awareness: Priming is implicit

Context and Priming

Work in context is interested in large-scale semantic representations that involve episodic and semantic knowledge

- Comprehension of sentences and paragraphs

- Comprehension of spoken conversations

Contextual Ambiguity and Priming

What does the word bank mean?

1. We had trouble finding the bank.

2. We were swimming at the bank.

3. We were making a deposit at the bank.

Sentence 2 primes RIVER; Sentence 3 primes MONEY

Context primes a particular concept of bank