Cognition 7e, Margaret MatlinChapter 8 Cognition General Knowledge How do we know what properties...

Cognition 7e, Margaret Matlin Chapter 8

CognitionCognition

General KnowledgeGeneral KnowledgeHow do we know what How do we know what

properties something has, and properties something has, and which of its properties should be which of its properties should be

generalized to other objects?generalized to other objects?How is the knowledge underlying How is the knowledge underlying these abilities acquired, and how these abilities acquired, and how is it affected by brain disorders? is it affected by brain disorders?

Chapter 8Chapter 8

IntroductionIntroduction

semantic memorysemantic memoryschemasschemas

We have an enormous amount of information at our disposal, and we use this information efficiently and accurately.


The Structure of Semantic MemoryThe Structure of Semantic Memory

Background on Semantic MemoryBackground on Semantic Memorysemantic memory - encyclopedic knowledge, lexical or

language knowledge, conceptual knowledgecategoryconceptsemantic memory allows us to:

• code objects• make inferences• decide which objects are similar



The Feature Comparison ModelThe Feature Comparison ModelConcepts are stored in memory according to a list

of necessary features or characteristics.

Description of the Feature Comparison Modeldefining features - necessarycharacteristics features



The Feature Comparison ModelThe Feature Comparison Model



Research on the Feature Comparison ModelResearch on the Feature Comparison Modelsentence verification techniquereaction times to answer true/false

typicality effect—people reach decisions faster when an item is a typical member of a category, rather than an unusual member

problem—very few of the concepts we use in everyday life can be captured by a specific list of necessary, defining features



The Feature Comparison ModelThe Feature Comparison ModelConclusions about the Feature Comparison Model

• can account for typicality effect, but research does not support the idea that category membership is based on a list of necessary features

• feature comparison model assumes that individual features are independent of one another, however many features are correlated

• feature comparison model does not explain how the members of categories are related to one another



The Prototype ApproachThe Prototype ApproachEleanor Rosch—we organize each category on the basis of a prototype, which is the item that is most typical and representative of the category•prototype approach—you decide whether an item belongs to a category by comparing that item with a prototype – personal experience•a prototype is an abstract, idealized example; may not exist•members of a category differ in prototypicality•graded structure—all members of categories are not created equal



Characteristics of PrototypesCharacteristics of Prototypes1. Prototypes are supplied as examples of a category

Mervis and colleagues (1976)prototype ratings for examples of categoriesitems rated most prototypical were the same items that

other people had supplied most often in the category norms

accounts for typicality effect—when judging whether an item belongs to a particular category, typical items judged faster than atypical items



Characteristics of PrototypesCharacteristics of Prototypes2. Prototypes are judged more quickly after

semantic primingsemantic priming effect—people respond faster to an

item if it was preceded by an item with similar meaning

priming facilitates the responses to prototypes more than it facilitates the responses to nonprototypes

priming inhibits judgments for nonprototypes (Rosch color studies)



Priming examplesPriming examples


Orthographic Morphological Semantic

Prime Target Prime Target Prime Target

corner CORN friendly FRIEND idea NOTION

turnip TURN punishment PUNISH crazy INSANE

tinsel TIN wonderful WONDER admire LIKE

bulletin BULLET active ACT pick CHOOSE

topple TOP greatness GREAT touch FEEL


Characteristics of PrototypesCharacteristics of Prototypes3. Prototypes share attributes in a family

resemblance categoryfamily resemblance

no single attribute shared by all examples of a concept

each example has at least one attribute in common with some other example of the concept

no single attribute serves as the necessary and sufficient criterion for membership in the category



3. Prototypes share attributes in a family resemblance category (continued)

Rosch and Mervis (1975)prototypicality judgments about members of

several categorieslist attributes possessed by each itemthe most prototypical item also had the largest

number of attributes in common with the other items in the category



The Prototype ApproachThe Prototype ApproachLevels of Categorization

super-ordinate-level categoriesbasic-level categoriessubordinate-level categories




2. Basic-level names are more likely to produce the semantic priming effect

priming with basic-level names is helpfulpriming with superordinate names is not helpful




3. Different levels of categorization activate different regions of the brain.

superordinate terms are more likely than basic-level terms to activate part of the prefrontal cortex

subordinate terms are more likely than basic-level terms to activate part of the parietal region

Example: AnimalHorseRace Horse



Conclusions About the Prototype ApproachConclusions About the Prototype Approachcan account for our ability to form concepts for groups that

are loosely structuredcan be applied to social relationships, inanimate objects,

nonsocial categoriesProblems

concepts can be unstable and variable (e.g., prototype ratings can shift based on experience)

we often do store specific information about individual examples of a category

better for general population than for experts



Individual Differences: Expertise and Individual Differences: Expertise and PrototypesPrototypes

expertisepracticeexperts construct prototypes in a different fashion




Lynch, Coley, and Medin (2000)tree expertsexperts' best examples were very tall, well-behaved

trees . . . rather than typical, average treesfor novices the ratings were based on familiarity rather than

typicality




Johnson and Mervis (1997)experts and novices prefer different levels of categorizationbird-watching experts provide very specific names for birds,

rather than basic-level term


Individual Differences: Individual Differences: Expertise and PrototypesExpertise and Prototypes

Example of Expert PrototypesExample of Expert Prototypes



The Exemplar ApproachThe Exemplar Approachfirst learn some specific examples of a concept

(exemplars)then classify each new stimulus by deciding how closely it

resembles those specific examples



A Representative Study on the Exemplar A Representative Study on the Exemplar ApproachApproach

Heit and Barsalou (1996)provide first example that comes to mind of seven

basic-level categoriesdifferent group rates the typicality of each category and

of each example with respect to "animal"researchers try to create equation to predict typicality of

the categories based on the exemplars in terms of frequency and typicality ratings



Heit and Barsalou (1996) (continued)

exemplar frequency and exemplar typicality did accurately predict which of the seven categories were most typical for the superordinate category "animal"

less typical exemplars increase the correlationwhen asked a question about a category, people don't

just consider prototypes, they also include information about less typical examples of the category



Comparing the Exemplar Approach with Other Comparing the Exemplar Approach with Other ApproachesApproaches

• exemplar approach proposes that we do not need any list of features (as in feature comparison approach), because all the necessary information is stored in the specific exemplars

• make decisions about category membership by comparing to a stored representation (like prototype approach), but the stored representation is a collection of numerous specific members of the category, not a typical member



Comparing the Exemplar Approach with Other Comparing the Exemplar Approach with Other Approaches (continued)Approaches (continued)

• do not need to perform any kind of abstraction process (don't need to devise list of features or a prototype) which would force you to discard useful, specific data about individual cases



Problems with the Exemplar ApproachProblems with the Exemplar Approach• exemplar approach may be more suitable for

categories with relatively few members (so as not to overwhelm semantic memory) • Requires too much memory• prototype approach may be more suitable for

categories with numerous members

• individual differences in representations may be substantial



ConclusionsConclusions• both approaches may coexist

• different hemispheres • left—prototypes• right—exemplars)

• different categories may require different strategies for category formation



Network ModelsNetwork Modelsnetwork models of semantic memory propose a

netlike organization of concepts in memory, with many interconnections;

the meaning of a concept depends on the concepts to which it is connected



The Collins and Loftus Network ModelThe Collins and Loftus Network Modelsemantic memory is organized in terms of netlike

structures, with numerous interconnections

when we retrieve information , activation spreads to related concepts

Node = conceptlinkspreading activation



The Collins and Loftus Network ModelThe Collins and Loftus Network Modelsentence verification tasks—activations spreads from the

concept nodes until an intersection is located (or not)

frequently used links have greater strengths; activation travels faster between those nodes

explains typicality effect, but has been superceded by more complex theories



Network ModelsNetwork ModelsAnderson's ACT Theories

ACT-R—Automatic Components of Thought-Rational; attempts to account for all of cognition

propositional networkproposition—smallest unit of knowledge that can be

judged either true or false; abstract representation



ACT* distinguishes among three types of ACT* distinguishes among three types of memory structuresmemory structures

• Declarative memory (LTM) takes the form of a semantic net linking propositions, images, and sequences by associations.

• Procedural memory (LTM) represents information in the form of productions

• Working memory is that part of long-term memory that is most highly activated.



A propositional networkA propositional network



Productions in Procedural memoryProductions in Procedural memory• Productions represent knowledge about how we do

things• Example: knowledge about how to type the letter "Q" on a

keyboard, about how to drive, or about how to perform addition.

• "IF” a sensory precondition• "THEN” action



Anderson's ACT Theories Anderson's ACT Theories (continued)(continued)activation can spreadlimited capacity of working memory can restrict the

spreadingif many links are activated simultaneously, then each link

receives relatively little activation



Network ModelsNetwork ModelsThe Parallel Distributed Processing Approach

McClelland and colleagues

parallel distributed processing (PDP) approach— cognitive processes can be represented by a model in which activation flows through networks that link together a large number of simple, neuron-like units

Artificial Neural Network (ANN) - an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information


Compare PDP with SemanticCompare PDP with Semantic



Why use neural networks?Why use neural networks?Neural networks is to learn to associate patterns in input data to an output on their own

involves modifying the connection weights

Gives them the ability to •Derive meaning from complicated or imprecise data•Recognize input that has not seen before



How Do Neural Networks Work?How Do Neural Networks Work?The output of a neuron is a function of the weighted sum

of the inputs plus a bias



How Do Neural Networks Learn (to associate How Do Neural Networks Learn (to associate output with an input pattern)?output with an input pattern)?

• If the output is not correct, the weights are adjusted according to a formula• Uses the difference between input and output

• Goal - Minimizing the error in the network• Most common measure of error is the mean square

error: E = (target – output)2


Neural Network ExampleNeural Network Example

Handwriting Recognition


Neural Network ExampleNeural Network ExampleBank LoansBank Loans

• Imagine a highly experienced bank manager who must decide which customers will qualify for a loan. Her decision is based on a completed application form that contains ten questions.

• The bank manager's experience allows her to use "Intuition” that will enable her to recognize certain patterns that her brain has become attuned to.

• If we had a large number of loan applications as input, along with the manager's decisions as output, a neural network could be "trained" on these patterns.

• The inner workings of the neural network have enough mathematical sophistication to reasonably simulate the expert's intuition.



Parallel Distributed Processing AssumptionsParallel Distributed Processing Assumptions

Cognitive processes arise from the interactions of neurons through synaptic connections.

The knowledge in such interactive and distributed processing systems is stored in the strengths of the connections and is acquired gradually through experience



Three Central Characteristics of PDPThree Central Characteristics of PDP1. Cognitive processes are based on parallel operations,

rather than serial operations. Therefore, many patterns of activation may be proceeding simultaneously.



Three Central Characteristics of PDPThree Central Characteristics of PDP2. A network contains basic neuron-like units or nodes,

which are connected together so that a specific node has many links to other nodes (hence the alternate name for the theory: connectionism).

PDP theorists argue that most cognitive processes can be explained by the activation of these networks.



Three Central Characteristics of PDPThree Central Characteristics of PDP3. A concept is represented by the pattern of activity

distributed throughout a set of nodes.

Notice that this view is very different from the commonsense idea that all the information you know about a particular person or object is stored in one specific location in the brain.



Features & Concepts of PDPFeatures & Concepts of PDPserial search vs. parallel searchmemory can cope with partial and/or partly incorrect

informationcharacteristics connected in a mutually stimulating

networkspontaneous generalization—draw a conclusion

about a general categorydefault assignment—draw a conclusion about a

specific member of a category



Other important characteristics of PDPOther important characteristics of PDP3. Every new piece of information you learn will change

the strength of connections among relevant units by adjusting the connection weights.

4. Sometimes we have only partial memory for some information, rather than complete, perfect memory. The brain’s ability to provide partial memory is called graceful degradation (e.g., tip-of-the-tongue phenomenon, brain function after accident or stroke)



Current Status of PDP TheoryCurrent Status of PDP Theory generally consistent with the neurological design or

neurons and the brain works better for tasks in which several processes

typically operate simultaneously; tasks requiring serial processing may be accounted for by other models

PDP explains: word superiority effect, retroactive interference, category formation, complex decision making



Current Status of Theory (continued)Current Status of Theory (continued) used to study social psychology, developmental

psychology, cognitive disorders can explain situations where learning accumulates

gradually across trials

The parallel distributed processing approach to semantic cognitionJames L. McClelland & Timothy T. RogersNature Reviews Neuroscience 4, 310-322 (April 2003)



Parallel Distributed Processing ApproachParallel Distributed Processing ApproachProblems

• not currently structured enough to handle the subtleties and complexities of semantic memory

• has trouble explaining why we sometimes forget extremely well-learned information when we learn additional information

• cannot explain why we sometimes can recall earlier material when it has been replaced by more current material


Schemas and ScriptsSchemas and Scripts

schema—generalized knowledge about a situation, an event, or a person

schema theories especially helpful when psychologists try to explain how people process complex situations and events

Scripts

What Your Favorite Porn Says About Who You Arehttp://www.psychologytoday.com/blog/intelligent-lust/

201201/what-your-favorite-porn-says-about-who-you-are



Background on Schemas and ScriptsBackground on Schemas and ScriptsPeople encode "generic" information about a situation or

event, then use this information when in that situation or a similar situation

This “package” of information is called a schema

heuristics—general rules that are typically accurate

schemas can lead to errors



Background on Schemas and ScriptsBackground on Schemas and ScriptsPiagetBartlettsocial psychologyschema therapyscript—simple, well-structured sequence of eventsscripts recalled more accurately if identified in advance



Enhanced Memory for Schema-Consistent Enhanced Memory for Schema-Consistent MaterialMaterial

Brewer and Treyens (1981)recall objects from waiting room;highly likely to recall objects consistent with "office

schema""remembered" items that were not in the room, but were

consistent with "office schema"Neuschatz and coauthors (2002)

"lecture schema"



Enhanced Memory for Schema-Inconsistent Enhanced Memory for Schema-Inconsistent MaterialMaterial

people are more likely to recall schema-inconsistent material when that material is vivid or surprising

Davidson (1994)—read stories describing well-known schemas; people especially likely to recall schema-inconsistent events that interrupted the normal, expected story



The Status of Schemas and Memory SelectionThe Status of Schemas and Memory SelectionRojahn and Pettigrew (1992)—meta-analysis; schema-

inconsistent material was somewhat more memorable

However, when people "remember" events that never actually happened, they are likely to construct a schema-consistent event



Schemas and Boundary ExtensionSchemas and Boundary ExtensionBoundary extension—our tendency to remember having

viewed a greater portion of a scene than was actually shown

Intraub and colleagues—see photo then draw replica of photo; participants consistently produced a sketch that extended the boundaries beyond the view presented in the original photo – p. 270

relevance in eyewitness testimony situations



Schemas and Memory AbstractionSchemas and Memory Abstractionabstraction—a memory process that stores the meaning

of a message but not the exact words

verbatim memory—word-for-word recall



Schemas and Memory AbstractionSchemas and Memory AbstractionThe Constructive Approach

Bransford and Franks (1971)listen to sentences from several different storiesrecognition test including new itemspeople convinced that they had seen these new items

before (false alarm)false alarms particularly likely for complex sentences

consistent with the original schemafalse alarms unlikely for sentences violating the meaning

of the earlier sentences



Schemas and Memory AbstractionSchemas and Memory AbstractionThe Constructive Approach

constructive model of memory—people integrate information from individual sentences in order to construct larger ideas; later cannot untangle the constructed information from the verbatim sentences



Schemas and Memory AbstractionSchemas and Memory AbstractionThe Pragmatic Approach

pragmatic view of memory—people pay attention to the aspect of a message that is most relevant to their current goals




Murphy and Shapiro (1994)read letters from "Samantha" to cousin or boyfriendbland vs. sarcastic commentsrecognition test on original, paraphrased, or irrelevant

sentences


Pragmatic ApproachPragmatic Approach




Murphy and Shapiro (1994) (continued)

correct recognition was higher for sentences from the sarcastic condition than for sentences in the bland condition

more false alarms for paraphrases of bland sentences than sarcastic sentences

more accurate in their verbatim memory for the sarcastic version than for the bland version



Schemas and Memory AbstractionSchemas and Memory AbstractionThe Current Status of Schemas and Memory Abstraction

two approaches (Constructive and Pragmatic) quite compatible

in many cases we integrate information into large schemasin some cases we know that specific words matter and pay

close attention to precise wording



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in Memoryinferences—logical interpretations and

conclusions that were not part of the original stimulus material



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in MemoryThe Classic Research on Inferences

Bartlett (1932)—memory as the complex interaction between the participants' prior knowledge and the material presented; individual's unique interests and personal background often shape the contents of memory

"The War of the Ghosts" study—Native American story read and recalled by British students



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in MemoryThe Classic Research on Inferences

"The War of the Ghosts" study (continued)

Participants tended: • to omit material that didn't make sense from their own

viewpoint• to shape the story into a more familiar framework• to add extra material to the story, making inferences so

that the story made more sense from their perspective• to borrow more heavily from their previous knowledge

as time passed before additional recall



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in MemoryResearch on Inferences Based on Gender Stereotypes

gender stereotypes—widely shared sets of beliefs about the characteristics of females and males




Explicit Memory TaskDunning and Sherman (1997)

read sentences followed by recognition-memory test"new" sentences consistent or inconsistent with

gender stereotypesmore likely to mistakenly "remember" a new sentence

as "old" when it was consistent with a gender stereotype




Implicit Memory Tasks1. Using neuroscience techniques to assess gender

stereotypesOsterhout, Bersick and McLaughlin (1997)—ERP

techniquestereotype-consistent sentences vs. stereotype-

inconsistent sentenceschange in ERPs for stereotype-inconsistent words but

not for stereotype-consistent words




Implicit Memory Tasks2. Using the Implicit Association Test to assess

gender stereotypesNosek, Banaji, and Greenwald (2002)Implicit Association Test (IAT)—based on the

principle that people can mentally pair related words together much more easily than they can pair unrelated words

https://implicit.harvard.edu/implicit





gender stereotypes (continued)

Stereotype-Consistent pairings (male/math vs. female/arts)

Stereotype-Inconsistent pairings (female/math vs. male/arts)





gender stereotypes (continued)

participants responded significantly faster to the stereotype-consistent parings than to the stereotype-inconsistent pairings

technique can be used to examine attitudes, as well as stereotypes



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in MemoryImplications of Inferences for Persuasion

AdvertisingHarris and colleagues (1989)

read stories containing advertising slogansdirect claim vs. implied claimpeople who had seen the implied-claim version often

believed they had seen the direct-claim versionConsumers be careful



In Depth: Schemas and Inferences in MemoryIn Depth: Schemas and Inferences in MemoryImplications of Inferences for Persuasion

Politicsstatements can be technically accurate but still misleadinglisteners make incorrect inference

people make inferences only in certain situations; often recall material in its original form



Schemas and Integration in MemorySchemas and Integration in MemoryIntegration and Delayed Recall

background knowledge may not encourage schema-consistent integration if people are tested immediately after the material is learned

Harris and colleagues (1989)story consistent with U.S. or traditional Mexican cultureno chaperone/chaperonerecall after 30 minutes—no tendency for the Mexican-schema

stores to shift in the direction consistent with U.S. schemasafter two days—the students had shifted a significant number

of story details



Schemas and Integration in MemorySchemas and Integration in MemoryIntegration and Limited Memory Capacity

schemas are more likely to influence memory integration when memory capacity is strained during recall, but not on a relatively simple task



Conclusions About SchemasConclusions About Schemas1. We often select material for memory that is inconsistent

with our schemas.2. We may indeed remember that we saw only a portion of

an object, rather than the complete object.3. We frequently recall the exact words of a passage as it

was originally presented.



Conclusions About SchemasConclusions About Schemas4. We often avoid making inappropriate inferences.5. We may keep the elements in memory isolated from

each other, rather than integrated together.6. When we are recalling information from our real-life

experiences—rather than information created by researchers—we may be more accurate.


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