1. Chapter 8: Representation and Organization of Knowledge in Memory: Concepts, Categories, Networks and Schemas

2. Using Our Minds Knowing that… Knowing how… Declarative knowledge
Procedural knowledge

3. Declarative Knowledge
Stored in Concepts
A mental representation of an item and associated knowledge and beliefs (cat, tools, furniture)
Cat
long tail
calico
furry
meows

4. When Do We Use Concepts? Create categories Make inferences
Combine to form complex thoughts
For communication

5. Organizing Structures of Declarative Knowledge
Concept
Unit of symbolic knowledge
Category
Rule used to organize concepts
Schemas
Framework used to organize concepts

6. Different Types of Concepts
Natural Concept
Occur naturally (e.g. plants, trees, cats)
Artifact Concept
Created by humans (e.g., hammers, computers)
Ad Hoc Concepts
Created individually to suit a need (things you need to be happy, things you do to please parents)

7. Different Theories on Concept Organization
Defining Features (Classical View)
Prototypes
Exemplars
Hierarchically semantic networks

8. Defining Features A defining feature
Must have this to be considered a member
What are the defining features of a mime?
Image taken from Microsoft, no copyright needed

9. Problem with Defining Features Theory
Difficult to specify necessary features of some concepts
What is the defining feature of a monster?
A widow?
A family?
Problem with theory is that it is not always easy to come up with defining features.
So for monsters, if they say scary, bring up the cookie monster, or Monsters Inc.; for weddings, not all need priests, not all need churches, etc…
Images taken from Microsoft.

10. Additional Defining Features Problem
Typicality Effects
Some things are better examples of a concept than others
Robin is a more typical bird than a ostrich
Clip art from microsoft office

11. Prototype Theory
Abstracted representation of a category containing salient features that are true of most instances
Characteristic features which describe what members of that concept are like
Monster prototype has these characteristics: Scary, pale, has sharp teeth, is evil, lives in odd place (coffins, closets, or graveyards)
Vampires, Zombies, and Bogeymen all fit that prototype well,
Can a green, grumpy, lives in a garbage can monster also fit? Yes, but less well.

12. Prototype Theory Deals well with fuzzy concepts
Fuzzy concepts are categories that cannot be easily defined (Monster, Games)
To categorize, simply compare to prototype

13. Exemplar View
No single prototype but rather multiple examples convey idea what the concept represents
Vegetable Concept = Peas, Carrots, or Beans
Is a green pepper a vegetable?
The more similar a specific exemplar is to a known category member, the faster it will be categorized

14. Exemplar View Similar to Prototype View
Representation is not a definition
Different: Representation is not abstract
Descriptions of specific examples
To categorize, compare to stored examples

15. Synthesis: Combine Prototype & Defining Feature
Evidence for both, so combine
Introduce the idea of the “core”
Defining features that item must have
Prototype
Characteristics typical of examples

16. Understanding of Defining Features
Keil & Batterman (1984)
5-10 year olds exposed to category
Smelly mean old man with a gun that took TV because parents told him he could have it
Friendly and cheerful woman who took toilet without permission and no intention to return it
Which is a robber?
Not until close to age 10, did children see the cheerful woman as a robber

17. Theory Based View
Knowledge of the world informs and shapes our predictions about concepts
Features in a complex network of explanatory links indicate
Relative importance of features
Relations among features
Objects classified into concept that best explains the pattern of attributes
Category Use and Category Learning Author(s): Arthur B. Markman Department of Psychology, University of Texas at Austin Brian H. Ross Department of Psychology, University of Illinois at Urbana-Champaign. Source: Psychological Bulletin. Vol. 129 (4)
July 2003, pp American Psychological Association.

18. Rips (1989) Sorp/Doon Story Participants were then asked
Manipulated if the change was caused by an accident, a change in nature, or a control group reading about sorps
Participants were then asked
Is it more similar to a bird or an insect?
Is it more likely to be a bird or an insect?

19. More Support for Theory Based View
Gelmen (2004)
“Dog” and “Gold” categories
Give a third item and ask child to draw an inference based on perceptual similarity or category membership
Children often used category membership, not just color or superficial features of item
Thus, the abstract essential meaning of items was used by children

20. Semantic Network Model
Nodes represent concepts in memory
Relations represented links among sets of nodes
Robin
Property
Wings

21. Collins & Quillian’s Model (1969)
Structure is hierarchical
Time to retrieve information based on number of links
Cognitive economy
Properties stored only at highest possible level
Inheritance
Lower-level items also share properties of higher level items

22. Collins & Quillian’s Model (1969)
Has skin
Animal
Breathes
Eats
Has fur
Has fins
Fish
Dog
barks
swim
Explain cognitive economy, inheritance with model.
4 legs
Has gills
Is pink
Has spots
Dalmatian
Salmon
Is edible
Skinny tail
Black &
white
Lays eggs upstream

23. Support for Collins & Quillian Model
Sentence verification task
Indicate if the following sentences are true or false: Measure reaction time
Salmon are pink.
Animals breathe.
A dog has four legs.
A dalmatian has skin.
The more links traveled according to model, the longer the reaction time of truth verification

24. Collins & Loftus (1975) Semantic Model
Got rid of hierarchy
Got rid of cognitive economy
Allowed links to vary in length to account for typicality effects
Spreading activation
Activation is the arousal level of a node
Spreads down links
Used to extract information from network

25. swims
fish
4 legs
fur
Goldie
dog
pet
Lucy
mutt
poodle

26. Basic Level Largest number of features Used most often Superordinate
Furniture, Animal
Largest number of
features
Used most often
Basic Level
Chair, Bird
Subordinate
Bean Bag, Robin

27. Evidence Basic-Level is Special
People almost exclusively use basic-level names in free-naming tasks
Children learn basic-level concepts sooner than other levels
Basic-level is much more common in adult discourse than names for superordinate categories
Different cultures tend to use the same basic-level categories, at least for living things

28. Schemas
Schemas are models of the external world based on past experience
Schemas for concepts underlying situations, events, or sequences of actions
Abstraction that allows particular objects or events to be assigned to general categories

29. Schemas Organize our knowledge May include other schemas
Help in encoding, storage, and recall
Allows us to make inferences

30. Schema Research Tuckey & Brewer (2003)
Examined the impact of schemas on eyewitness memory
One factor manipulated was the ambiguity or schema consistency of film crime watched
Created a film that activated bank robbery schema
Tuckey, M.R. & Brewer, N. (2003). The effect of schemas, stimulus ambiguity, and interview schedule, on eyewitness memory over time. Journal of Experimental Psychology: Applied, 9,

31. Tuckey & Brewer (2003) Participants saw one of two short films of a bank robbery
Just click on the black square for the movie to play.
Film of bank robbery provide by Michelle Tuckey.
Tuckey, M.R. & Brewer, N. (2003). The effect of schemas, stimulus ambiguity, and interview schedule, on eyewitness memory over time. Journal of Experimental Psychology: Applied, 9,

32. Tuckey & Brewer (2003) Ambiguous schema film Schema inconsistent film
Enter bank
“Hurry up”
Possible guns
Take money
Leave bank
Running escape
Schema inconsistent film
Partner chubby
One wore a suit
Another wore bright clothing
Was apologetic
One escaped on bus
One a female
Tuckey, M.R. & Brewer, N. (2003). The effect of schemas, stimulus ambiguity, and interview schedule, on eyewitness memory over time. Journal of Experimental Psychology: Applied, 9,

33. Tuckey & Brewer (2003) Ambiguity/Schema manipulation
Half of the participants saw a film that contained ambiguous scenes like
Criminals may have guns
Verbal demands of the tellers were made (but no explicit demands for money)
Other half of participants viewed a film that did not have ambiguous scenes
The bag the robber was holding was limp and could not have hidden a gun
Apologetic speech occurred in the film
Tuckey, M.R. & Brewer, N. (2003). The effect of schemas, stimulus ambiguity, and interview schedule, on eyewitness memory over time. Journal of Experimental Psychology: Applied, 9,

34. Tuckey & Brewer (2003) Ambiguous Schema Schema Inconsistent
Ambiguous Schema
Schema Inconsistent
Correct information
1.5
2.84
Intrusions
2.3
1.11
Results taken from Table 6, closed questionnaire items in Tuckey, M.R. & Brewer, N. (2003). The effect of schemas, stimulus ambiguity, and interview schedule,
on eyewitness memory over time. Journal of Experimental Psychology: Applied, 9,
Results indicated lower recall and more schema
consistent intrusions occurring in the
ambiguous condition

35. Bower, Black, & Turner (1979) Participants read 18 stories
1, 2, or 3 stories read about each schema
1 story about going to the doctor
1 story about going to the dentist
Health care schema activated for both
Bower, Gordon H.; Black, John B.; Turner, Terrence J.(1979) Scripts in memory for text.; Cognitive Psychology, 11,

36. Bower, Black, & Turner (1979)
Participants then asked if 3 particular types of events happened in the stories
Events actually in stories
Events consistent with schemas, but not actually in stories
Novel, unrelated events
Participants also rated their level of confidence about each of their answers
Bower, Gordon H.; Black, John B.; Turner, Terrence J.(1979) Scripts in memory for text.; Cognitive Psychology, 11,

37. Bower, Black, & Turner (1979) Results
Participants were confident
About the actual events that they did read
About schema-consistent events not actually in story
The more stories read about a certain schema, the more confidence that the schema-consistent event was in a story
Implications of the results
Ideas contained in the schema become a part of the memory with items and events actually experienced
Bower, Gordon H.; Black, John B.; Turner, Terrence J.(1979) Scripts in memory for text.; Cognitive Psychology, 11,

38. Brewer and Treyens (1981) Memory for graduate student's office
88 objects mentioned in recall
19 were inferred (not present)
9 people recalled books
8 people recalled skull
1 person recalled umbrella
Participants recalled expected objects or highly unexpected objects
Office Picture; Brewer & Treyens (1981); Fig.1; p. 211.
Brewer, William F.; Treyens, James C.(1981) The role of schemata in memory for places. Cognitive Psychology, 13,

39. Scripts Type of schema about events
Structure captures general information about routine events
Eating in a restaurant, attending a movie, a visiting a doctor’s office
Scripts have typical roles
(Customers, waiter, cook), (ticket vendor, patrons, refreshments), (doctor, nurse, patient)

40. Scripts
When we hear or read about a scripted event, our knowledge of the entire script is activated
We can fill in or infer the scenes and actions that are not explicitly mentioned

41. Schank and Abelman (1977) Visit a restaurant script
Sit down
Look at menu
Order food
Eat
Pay
Leave
73% of subjects produce the above actions 48% agreed on a further 9 actions
Schank, R. C. & R. P. Abelson. (1977). Scripts, Plans, Goals and Understanding, Chapters 1-3:1-68, Hillsdale, NJ: Erlbaum.

42. Representing Procedural Knowledge
Serial Processing
Linear sequence of operations
Create using production rules
If – then rules
If sliding on ice then pump the brakes
Tasks may take multiple rules
Organized into routines and subroutines

43. ACT-R Model Theory for simulating and understanding human cognition
Goal is to create model that can simulate how knowledge is organized and used to produce behavior
J. Anderson is a prominent researcher in this area
ACT-R Home Page:
is the office webpage of ACT-R theory. Webpage provides tutorials and publications to help interested students and researchers better understand the theory.

44. ACT-R Model Combines declarative and procedural knowledge in a model
Declarative knowledge is represented in structures called chunks defined by its type and slots
Type represents concepts or categories (e.g., dogs) and slots as category attributes (e.g., color or size)
is the office webpage of ACT-R theory. Webpage provides tutorials and publications to help interested students and researchers better understand the theory.

45. ACT-R Chunk Diagram The dog chased the cat
Chunk diagram for this proposition
Isa = chase
Agent = dog
Object = cat
is the office webpage of ACT-R theory. Webpage provides tutorials and publications to help interested students and researchers better understand the theory.
Example taken from:

46. ACT-R Production Diagram
Procedural knowledge is represented in productions
IF the goal is to classify a person
And he is unmarried
THEN classify him as a bachelor
Examples taken from:

47. Activation & ACT-R Spreading Activation Measures of Prior Learning
Activation spreads via links across chunks
Measures of Prior Learning
The recency and frequency of practice of the chunk as described in the previous unit affects speed of activation

48. Activation & ACT-R Sources of Activation Weighting
The number of links connecting elements of the chunks
Weighting
How much activation from source
Strengths of Association
The strength of association from source to chunk

49. ACT-R Has Simulated…
Myriad of successful models for a variety of phenomena
Visual search tasks
Driving behavior
RT to do paper, rock, scissors game under differing circumstances
Tower of Hanoi problem
Category learning
List memory
Group decision making
Visit link for paper references and pdf versions of papers relating to ACT-R.

50. Acquisition of Procedural Knowledge
Anderson (1980)
Cognitive Stage
Consciously think about steps to complete task
Associative Stage
Practice the procedure
Autonomous Stage
Skill has become automatic
Examples to get students to think about these stages: Remembering learning to tie your shoe—Do you have to think about it now? Riding a bike, shifting gears in a car, etc. Any procedural skill will do. Ask them what happens when you try to teach someone else a skill that is automatic for them. Usually generates stories of how it throws their own ability off.

51. Squire’s Non-declarative Knowledge
Procedural knowledge
Associative conditioning
Classical and operant conditioning
Simple nonassociative knowledge
Habituation
Sensitization
Priming

52. Squire’s Non-declarative Knowledge
Non-declarative (Implicit)
Procedural Priming Simple Nonassociative
(Skills &
Habits)
Recreation of chart based on Squire’s taxonomy in "Neuropsychological Investigations of Memory and Amnesia: Findings From Humans and Nonhuman Primates," p. 437, by S. Zola-Morgan and L. R. Squire, 1990, in A. Diamond, The Development and Neural Bases of Higher Cognitive Functions, New York: New York Academy of Sciences.
Emotional Skeletal
Responses Musculature
Striatum Neocortex Amygdala Cerebellum Reflexes
Pathways

53. Support for Squire’s Taxonomy
Basil Ganglia damage
Examine Parkinson’s and early Huntington disease patients
No apparent amnesia (declarative memory intact)
Problems with procedural memory
Perceptual motor learning
Habits & skills
Just one example of variety of studies with humans and animals have supported Squire’s taxonomy
Knowlton, B. J., Mangels, J. A., & Squire, L. R. (1996). A neostriatal habit learning system in humans. Science, 273,

54. Two Types of Priming Semantic priming Repetition priming
Meaning is primed
Remember Nurse-Doctor study?
Repetition priming
Prior exposure primes same items seen later

55. Connectionist Model Parallel processing
Multiple operations occur simultaneously
Parallel Distributed Processing (PDP) models
Goal is to model information as it is represented in the brain

56. The PDP Model The representation of information is distributed
Knowledge for specific things are not stored explicitly, but stored in the activations of patterns among units
Learning occurs with changes in connection strength by experience
Units send excitatory and inhibitory signals to other unit
Rumelhart, D.E., Hinton, G.E., & McClelland, J.L. (1986). A general framework for parallel distributed processing. In D. E. Rumelhart, J. L. McClelland, and the PDP Research Group (Eds.). Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 1: Foundations. Cambridge, MA: MIT Press.