1. Knowledge information that is gained and retained what someone has acquired and learned organized in some way into our memory

2. 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

3. Semantic Memory: Cognitive Models Set-theoretical model semantic feature-comparison model network models propositional networks

4. 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 ________

5. 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

6. 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

7. 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.

8. 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…

9. Set-theoretical model Retrieval is a function of verification –must search through 2 or more “sets” to find overlapping information –more overlap = quicker decisions

10. 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

11. Feature Comparison Model

12. 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

13. Two stage decision model of sentence verification:

14. 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

15. 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

16. Network Models Hierarchical Network Model -Collins and Quillian - early work Spreading Activation Theory - Collins and Loftus

17. 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

18. Hierarchical-Network Model

19. 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.

20. Hierarchical-Network Model

21. 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

22. 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.

23. Spreading Activation

24. 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

25. Propositional Network Models HAM and the representation of Knowledge (Human Associatve Memory) ACT (Adaptive Control of Thought