Knowledge

• information that is gained and retained

• what someone has acquired and learned

• organized in some way into our memory

Semantic Organization

• put items that are related in some way into a cluster or a group.

• Cognitive Models - assume that detailed congitive structures represent the way semantic info is organized in memory

Semantic Memory: Cognitive Models

• Set-theoretical model

• semantic feature-comparison model

• network models

• propositional networks

How to study semantic memory

• Association Tasks:– Free association: Used by Freud to study

personality, but may tell us more about the structure of knowledge.

– Category association: People are asked to give associates to a category name.

• fruit: _________

• fruit: a ________

How to study semantic memory• Tip of the tongue (TOT):

– A sensation we have when we are confident we know a word we are searching for, but we are unable to recall it

– Brown & McNeill (1966) research 1.read definitions of infrequent words

2.subjects asked to raise hands when they had a TOT

3.subjects then asked:

What is a similar word? What does the word sound like?

How many syllables? What is the word’s first letter? 4.Results: subjects often could supply partial information

How to study semantic memory• Sentence verification task:

Present sentence: "Is a robin a bird?"

Measure RT to correctly respond

• Category verification task:

bird-robin ("yes")

bird-tree ("no")

Measure RT to correctly respond

How to study semantic memory• Lexical Decision (word/non word) Task:

Present a word (brain) or a non-word (shup).

Ask subjects to decide, as quickly as possible, if the item is a word.

RT tells us how long it takes subjects to search their mental dictionary.

Set-theoretical model

• Concepts in memory are collections (sets) of info.

• Sets include:– instances of a category

• category car has instances of Volkswagon, Saab, Mercedes,…

– attributes or properties of a category • category car has properties of tires, engine, trunk,

metal, windshield…

Set-theoretical model

• Retrieval is a function of verification– must search through 2 or more “sets” to find

overlapping information– more overlap = quicker decisions

Feature Comparison Model

• Basic Assumptions– Concepts are represented as a set of features,

similar to Set-Theoretical model– unlike previous model, differentiates between:

1. Defining features (essential components)

2. Characteristic features (accidental, not always present)

– verification is based more on defining features

Feature Comparison Model

Feature Comparison Model

• Features are ordered according to "definingness"

characteristic features defining features

birds fly birds have wings

birds sing birds have feathers

• Relations between concepts computed based on shared features

Two stage decision model of sentence verification:

Feature Comparison Model

Predictions:

1. Category size effect: A robin is a bird. vs. A robin is an animal.A dog is mammal. vs. A dog is an animal.

2. Typicality effects A robin is a bird. vs. A penguin is a bird.

3. Quick rejection of false sentences: A bat is a bird vs. A pencil is a bird

Feature Comparison Model

• Problems:

1.Defining Features?

2.Semantic Priming?

3.Quick rejection of false sentences?

people are trees

a bat is a bird

a dog is a cat

Network Models

• Hierarchical Network Model -Collins and Quillian - early work

• Spreading Activation Theory - Collins and Loftus

Hierarchical-Network Model

• Representational Assumptions– hierarchically organization of concepts– cognitive economy: properties are stored at the

most general, or highest level possible.

• Processing Assumptions:– intersection search: enter the network at two

concepts, and search for a connection. – type of connection determines yes/no response

Hierarchical-Network Model

Hierarchical-Network Model

• Tests of the model:– Category-Size Effect:

compare: A robin is a bird.

to: A robin is an animal.

– Cognitive Economy: compare: A bird has feathers

to: A bird has skin.

Hierarchical-Network Model

Hierarchical-Network Model

• Challenges to the Hierarchical Assumption: 1) reversals of the category size effect

A dog is a mammal vs. A dog is an animal.

2) typicality effects: A robin is a bird. vs. An ostrich is a bird.

• Challenges to Cognitive Economy

• Negative sentence RT’s not predicted by the model

Spreading Activation

• New assumptions: 1.Not hierarchical: length of links represent

degree of relatedness. Search time depends on link length

2.Spreading Activation: retrieval (activation) of one of the links lead to partial activation of connected nodes. Degree of activation decreases with the distance.

3.Activation decreases with time.

Spreading Activation

Spreading Activation

• New predictions:– Typicality effects:

• A robin is a bird. vs. A chicken is a bird.

– Semantic Priming:

type of trial prime target RT

related prime bread butter 600

unrelated prime nurse butter 670

Propositional Network Models

• HAM and the representation of Knowledge (Human Associatve Memory)

• ACT (Adaptive Control of Thought