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

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

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

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

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

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)

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

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

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.

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

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.

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

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

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

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

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

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. 592-613. American Psychological Association.

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?

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

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

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

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

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

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

swims fish 4 legs fur Goldie dog pet Lucy mutt poodle

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

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

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

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

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, 101-118.

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, 101-118.

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, 101-118.

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, 101-118.

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, 101-118. Results indicated lower recall and more schema consistent intrusions occurring in the ambiguous condition

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, 177-220.

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, 177-220.

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, 177-220.

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, 207-230.

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)

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

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.

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

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: http://act.psy.cmu.edu http://act-r.psy.cmu.edu/ is the office webpage of ACT-R theory. Webpage provides tutorials and publications to help interested students and researchers better understand the theory.

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) http://act-r.psy.cmu.edu/ is the office webpage of ACT-R theory. Webpage provides tutorials and publications to help interested students and researchers better understand the theory.

ACT-R Chunk Diagram The dog chased the cat Chunk diagram for this proposition Isa = chase Agent = dog Object = cat http://act-r.psy.cmu.edu/ 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: http://act-r.psy.cmu.edu/tutorials/unit1.doc.

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: http://act-r.psy.cmu.edu/tutorials/unit1.doc.

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

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

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 http://act.psy.cmu.edu/papers/ACT-R_Models.htm link for paper references and pdf versions of papers relating to ACT-R.

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.

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

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

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, 1399-1402.

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

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

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.