the influence of motivation on human categorization and decision making

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The Influence of Motivation on Human The Influence of Motivation on Human Categorization and Decision Making Categorization and Decision Making W. Todd Maddox and Arthur B. Markman W. Todd Maddox and Arthur B. Markman University of Texas University of Texas Presented at the Gazzaniga Summer Institute in Cognitive Neuroscience, UCSB, July 4, 2007

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The Influence of Motivation on Human Categorization and Decision Making. W. Todd Maddox and Arthur B. Markman University of Texas. Presented at the Gazzaniga Summer Institute in Cognitive Neuroscience, UCSB, July 4, 2007. Setting the Stage. All human behavior is motivated - PowerPoint PPT Presentation

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Page 1: The Influence of Motivation on Human Categorization and Decision Making

The Influence of Motivation on Human The Influence of Motivation on Human Categorization and Decision MakingCategorization and Decision Making

W. Todd Maddox and Arthur B. MarkmanW. Todd Maddox and Arthur B. MarkmanUniversity of TexasUniversity of Texas

Presented at the Gazzaniga Summer Institute in Cognitive Neuroscience, UCSB, July 4, 2007

Page 2: The Influence of Motivation on Human Categorization and Decision Making

Setting the StageSetting the Stage All human behavior is motivatedAll human behavior is motivated Motivation influences behaviorMotivation influences behavior

Approach positive states and avoid Approach positive states and avoid negative states.negative states.

Cognition influences behaviorCognition influences behavior Motivation and Cognition need to be Motivation and Cognition need to be

studied togetherstudied together Until recently studied in different Until recently studied in different

branches of Psychologybranches of Psychology

Page 3: The Influence of Motivation on Human Categorization and Decision Making

Overview of TalkOverview of Talk Why we should care about motivationWhy we should care about motivation A framework for thinking about A framework for thinking about

motivation and its influence on motivation and its influence on cognition and learningcognition and learning

Application to:Application to: Perceptual classification learningPerceptual classification learning Stereotype threatStereotype threat Choking/PressureChoking/Pressure ChoiceChoice Signal DetectionSignal Detection

Page 4: The Influence of Motivation on Human Categorization and Decision Making

Why we should careWhy we should care Motivation affects decision making Motivation affects decision making

Preferences (Brendl, Markman, & Messner; Ferguson & Bargh)Preferences (Brendl, Markman, & Messner; Ferguson & Bargh) Need to smoke increases preference for smoking related items and Need to smoke increases preference for smoking related items and

reduces preference for not smoking related items reduces preference for not smoking related items Goal-adoption (Aarts et al, Fishbach & Shah)Goal-adoption (Aarts et al, Fishbach & Shah)

People adopt goals of people around them. People adopt goals of people around them. Selection of optimal behavior (Bechara et al., Busemeyer & Selection of optimal behavior (Bechara et al., Busemeyer &

Townsend)Townsend)

All cognitive research has an (uncontrolled) motivational All cognitive research has an (uncontrolled) motivational componentcomponent ““motivate” to “try harder”motivate” to “try harder”

““Motivation” brain regions reciprocally connected with Motivation” brain regions reciprocally connected with “cognitive” brain regions“cognitive” brain regions

Page 5: The Influence of Motivation on Human Categorization and Decision Making

Motivational FrameworkMotivational FrameworkRegulatory Fit Regulatory Fit

Extends concept developed by Extends concept developed by HigginsHiggins

HypothesisHypothesis: When there is a “fit” : When there is a “fit” between the regulatory focus between the regulatory focus (global task goal) and task reward (global task goal) and task reward structure (local task goal) more structure (local task goal) more flexible cognitive processing flexible cognitive processing (exploration) results.(exploration) results.

Page 6: The Influence of Motivation on Human Categorization and Decision Making

Regulatory Fit = Flexibility: Regulatory Fit = Flexibility: Why?Why?

Empirical support in several Empirical support in several domainsdomains

Connection to NeuroscienceConnection to Neuroscience Positive affect-frontal dopamine-Positive affect-frontal dopamine-

flexibility hypothesis (Isen, Ashby, flexibility hypothesis (Isen, Ashby, etc)etc)

Regulatory focus-frontal activation Regulatory focus-frontal activation findings (Amodio, Cunningham, etc)findings (Amodio, Cunningham, etc)

LC-NE-exploration/exploitation LC-NE-exploration/exploitation relation (Ashton-Jones, Cohen, Daw)relation (Ashton-Jones, Cohen, Daw)

Page 7: The Influence of Motivation on Human Categorization and Decision Making

Regulatory FocusRegulatory Focus(Global Task Goal)(Global Task Goal)

Promotion Promotion Focus Focus (Approach)(Approach)

Achieve Global Task Achieve Global Task Performance Criterion Performance Criterion Raffle ticket for $50Raffle ticket for $50

Prevention Prevention Focus Focus (Avoidance)(Avoidance)

Achieve Global Task Achieve Global Task Performance Criterion Performance Criterion Keep $50 raffle ticket given Keep $50 raffle ticket given initiallyinitially

Page 8: The Influence of Motivation on Human Categorization and Decision Making

Task Reward StructureTask Reward Structure(Local Trial-by-trial Task (Local Trial-by-trial Task

Goal)Goal)

GainsGains Correct Response = 3 pointsCorrect Response = 3 pointsIncorrect Response = 1 pointIncorrect Response = 1 point

LossesLosses Correct Response = -1 pointCorrect Response = -1 pointIncorrect Response = -3 pointIncorrect Response = -3 point

Page 9: The Influence of Motivation on Human Categorization and Decision Making

Consider the bigger Consider the bigger picturepicture

Reward Structure of Task

Gains LossesPromotion Focus Fit MismatchPrevention Focus Mismatch Fit

Page 10: The Influence of Motivation on Human Categorization and Decision Making

Consider the bigger Consider the bigger picturepicture

Almost all cognitive research involves a Almost all cognitive research involves a promotion focus and a gains reward structurepromotion focus and a gains reward structure Promotion focusPromotion focus: small monetary reward or social : small monetary reward or social

contract with experimenter.contract with experimenter. Gains: reward for correct response, no reward for Gains: reward for correct response, no reward for

errorerror

Reward Structure of Task

Gains LossesPromotion Focus Fit MismatchPrevention Focus Mismatch Fit

Fit

Page 11: The Influence of Motivation on Human Categorization and Decision Making

Regulatory Fit vs. Loss Regulatory Fit vs. Loss AversionAversion

Fit differs from loss-aversionFit differs from loss-aversion Loss aversion is a main effect. Loss aversion is a main effect.

““Losses loom larger than gains.”Losses loom larger than gains.” Regulatory fit is an interactionRegulatory fit is an interaction

The influence of losses depends on regulatory The influence of losses depends on regulatory focusfocus

Losses lead to Losses lead to flexibleflexible behavior under prevention behavior under prevention Losses lead to Losses lead to inflexibleinflexible behavior under behavior under

promotion promotion Whether this leads to good or bad overall Whether this leads to good or bad overall

performance depends on whether the task calls performance depends on whether the task calls for flexibilityfor flexibility

Page 12: The Influence of Motivation on Human Categorization and Decision Making

Studying Regulatory Fit Studying Regulatory Fit EffectsEffects

How can we study this systematically?How can we study this systematically? Need task for which we can manipulate Need task for which we can manipulate

the advantageousness of flexibility, while the advantageousness of flexibility, while holding other task characteristics fixedholding other task characteristics fixed

Need a good manipulation of regulatory Need a good manipulation of regulatory focusfocus

Need to be able to manipulate reward Need to be able to manipulate reward structurestructure

Page 13: The Influence of Motivation on Human Categorization and Decision Making

ApplicatioApplication 1:n 1:

Perceptual Perceptual ClassificatiClassificati

ononMaddox, Baldwin & Markman (2006; Memory Maddox, Baldwin & Markman (2006; Memory & Cognition)& Cognition)

Page 14: The Influence of Motivation on Human Categorization and Decision Making

Perceptual Perceptual Classification TaskClassification Task

Stimuli with small number of Stimuli with small number of underlying dimensionsunderlying dimensions Lines that vary in length, orientation and Lines that vary in length, orientation and

positionposition Experimenter control of category Experimenter control of category

structurestructure Extensive set of tools for modeling Extensive set of tools for modeling

performance of individual participantsperformance of individual participants Can assess the strategies participants use Can assess the strategies participants use

in the taskin the task

Page 15: The Influence of Motivation on Human Categorization and Decision Making

0

18

YesBonus

No

Page 16: The Influence of Motivation on Human Categorization and Decision Making

0

18

Correct

21

YesBonus

No

Page 17: The Influence of Motivation on Human Categorization and Decision Making

0

21

YesBonus

No

Page 18: The Influence of Motivation on Human Categorization and Decision Making

0

22

YesBonus

No

Wrong, that was an A

Page 19: The Influence of Motivation on Human Categorization and Decision Making

Experiment Set 1Experiment Set 1Flexibility is AdvantageousFlexibility is Advantageous

Gains Losses

Promotion (try to earn ticket) Fit: Good Mismatch :

PoorPrevention (try

not to lose ticket)

Mismatch: Poor Fit: Good

Conjunctive Rule-Based TaskConjunctive Rule-Based Task Exploration of verbal rule space requiredExploration of verbal rule space required

Page 20: The Influence of Motivation on Human Categorization and Decision Making

Scatterplot of StimuliScatterplot of Stimuli

o = category A = long, steep lineso = category A = long, steep lines+ = category B = all others+ = category B = all others

Page 21: The Influence of Motivation on Human Categorization and Decision Making

Possible Rule-based Possible Rule-based StrategiesStrategies

83% accuracy100% accuracy

Page 22: The Influence of Motivation on Human Categorization and Decision Making

Motivation Motivation ManipulationsManipulations

Regulatory FocusRegulatory Focus Promotion: Promotion: Entry into a cash Entry into a cash

drawing if performance criterion drawing if performance criterion (86%) exceeded.(86%) exceeded.

Prevention: Prevention: Drawing entry at start, Drawing entry at start, must exceed performance criterion must exceed performance criterion (86%) to keep entry.(86%) to keep entry.

Reward StructureReward Structure Gains conditionGains condition: Gains on each trial: Gains on each trial Loss conditionLoss condition: Losses on each trial: Losses on each trial

Page 23: The Influence of Motivation on Human Categorization and Decision Making

Experiment Screen Experiment Screen SampleSample

Gains

Losses

Page 24: The Influence of Motivation on Human Categorization and Decision Making

PredictionPrediction

Exceeding bonus requires Exceeding bonus requires exploration to find conjunctive exploration to find conjunctive strategystrategy

If a regulatory fit leads to increased If a regulatory fit leads to increased flexible cognitive processing flexible cognitive processing (exploration of the verbal rule (exploration of the verbal rule space), space),

Then performance should be best Then performance should be best when there is a regulatory fitwhen there is a regulatory fit

Page 25: The Influence of Motivation on Human Categorization and Decision Making

Performance ResultsPerformance Results

0.7

0.75

0.8

0.85

0.9

0.95

1

Gains Losses

Reward Structure

Prop

ortio

n Co

rrec

t

PromotionPrevention

Plots averaged over blocks. Effects generally larger early in learning

Page 26: The Influence of Motivation on Human Categorization and Decision Making

Model-based AnalysesModel-based Analyses Decision-bound models (Ashby & Decision-bound models (Ashby &

Maddox) fit to each participant Maddox) fit to each participant block-by-blockblock-by-block

Page 27: The Influence of Motivation on Human Categorization and Decision Making

Possible Rule-based Possible Rule-based StrategiesStrategies

83% accuracy100% accuracy

Page 28: The Influence of Motivation on Human Categorization and Decision Making

Model Fit PredictionsModel Fit Predictions Regulatory Fit Conditions should be more Regulatory Fit Conditions should be more

“flexible” and find the more complex “flexible” and find the more complex conjunctive rule faster than the conjunctive rule faster than the Regulatory Mismatch ConditionsRegulatory Mismatch Conditions

Page 29: The Influence of Motivation on Human Categorization and Decision Making

Modeling ResultsModeling Results

00.1

0.20.3

0.40.50.6

0.70.8

0.91

Gains Losses

Reward Structure

Prop

ortio

n C

onju

nctiv

e R

ule Promotion

Prevention

Prop

ortio

n C

onju

nctiv

e R

ule

Use

Page 30: The Influence of Motivation on Human Categorization and Decision Making

ConclusionsConclusions

In a classification task where exploration of the verbal rule space is advantageous, a regulatory fit led to better performance.

Page 31: The Influence of Motivation on Human Categorization and Decision Making

Experiment Set 2Experiment Set 2Flexibility is Flexibility is

DisadvantageousDisadvantageous

Gains Losses

Promotion (try to earn ticket) Fit: Poor Mismatch :

GoodPrevention (try

not to lose ticket)

Mismatch: Good Fit: Poor

Information-Integration TaskInformation-Integration Task

Page 32: The Influence of Motivation on Human Categorization and Decision Making

Experimental Method identical to Experiment Set 1

Page 33: The Influence of Motivation on Human Categorization and Decision Making

PredictionPrediction If regulatory fit = more flexibility,

then rule-based strategies should persist leading to poorer performance

COVIS assumes that rule-based strategies dominate early..

Rule-based strategies must be abandoned in information-integration tasks

Exceeding the bonus requires abandoning rule-based strategies

Page 34: The Influence of Motivation on Human Categorization and Decision Making

Performance ResultsPerformance Results

0.7

0.75

0.8

0.85

Gains Losses

Reward Structure

Prop

ortio

n Co

rrec

t

PromotionPrevention

Page 35: The Influence of Motivation on Human Categorization and Decision Making

Modeling ResultsModeling Results

00.1

0.20.3

0.40.50.6

0.70.8

0.91

Gains Losses

Reward Structure

Prop

ortio

n II

Use

PromotionPrevention

Prop

ortio

n II

Use

Page 36: The Influence of Motivation on Human Categorization and Decision Making

ConclusionsConclusions

We observe a 3-way interaction between regulatory focus, task reward structure, and nature of the task.

Flexibility advantageous: Fit is good

Flexibility disadvantageous: Fit is bad

Page 37: The Influence of Motivation on Human Categorization and Decision Making

ApplicatioApplication 2:n 2:

Stereotype Stereotype ThreatThreat

Grimm, Markman, Maddox & Baldwin (under Grimm, Markman, Maddox & Baldwin (under review)review)

Page 38: The Influence of Motivation on Human Categorization and Decision Making

Stereotype ThreatStereotype Threat Stereotype threat is the risk of Stereotype threat is the risk of

confirming a negative stereotype confirming a negative stereotype about one’s group (Steele & Aronson, about one’s group (Steele & Aronson, 1995). 1995).

Task-relevant stereotype causes task-Task-relevant stereotype causes task-specific decrements in performancespecific decrements in performance How?How?

Page 39: The Influence of Motivation on Human Categorization and Decision Making

Proposed stereotype threat Proposed stereotype threat mechanismsmechanisms

Self-handicapping (Stone et al., 1999; Brown & Josephs, Self-handicapping (Stone et al., 1999; Brown & Josephs, 1999)1999) Blacks better when framed as diagnostic of “natural athletic Blacks better when framed as diagnostic of “natural athletic

ability”ability” Whites better when framed as diagnostic of “sports intelligence”Whites better when framed as diagnostic of “sports intelligence”

Low performance confidence (Cadinu et al., 2003)Low performance confidence (Cadinu et al., 2003) Lower expected level of performance, lower actual performanceLower expected level of performance, lower actual performance

Task-specific concerns (Brown & Josephs, 1999)Task-specific concerns (Brown & Josephs, 1999) Ideomotor priming (Bargh et al., 1996)Ideomotor priming (Bargh et al., 1996)

People primed with elderly stereotype by unscrambling sentences People primed with elderly stereotype by unscrambling sentences relevant to stereotype. Those primed walked more slowly down hallrelevant to stereotype. Those primed walked more slowly down hall

Arousal (O’Brien & Crandall, 2003)Arousal (O’Brien & Crandall, 2003) Reduced working memory load (Beilock et al., 2007)Reduced working memory load (Beilock et al., 2007) Regulatory focus (Seibt & Förster, 2004)Regulatory focus (Seibt & Förster, 2004)

Page 40: The Influence of Motivation on Human Categorization and Decision Making

Connecting Stereotype Connecting Stereotype Threat and Regulatory FitThreat and Regulatory Fit

Seibt and Förster (2004)Seibt and Förster (2004) Positive stereotype induces promotion; Positive stereotype induces promotion;

negative stereotype induces preventionnegative stereotype induces prevention Promotion induces more elaborative Promotion induces more elaborative

processing while prevention induces more processing while prevention induces more vigilant processingvigilant processing

Others…Others…

Page 41: The Influence of Motivation on Human Categorization and Decision Making

FrameworkFrameworkGainsGains LossesLosses

Positive Positive stereotype stereotype (“Promotion”)(“Promotion”)

FitFit MismatchMismatch

Negative Negative Stereotype Stereotype (“Prevention”)(“Prevention”)

MismatchMismatch FitFit

Regulatory fit allow for more flexible cognitive processing

Stereotype Threat Stereotype “Threat”?

Page 42: The Influence of Motivation on Human Categorization and Decision Making

Flexibility PredictionsFlexibility PredictionsGainsGains LossesLosses

Positive Positive stereotype stereotype (“Promotion”)(“Promotion”)

BetterBetter WorseWorse

Negative Negative Stereotype Stereotype (“Prevention”)(“Prevention”)

WorseWorse BetterBetter

GainsGains LossesLossesPositive Positive stereotype stereotype (“Promotion”(“Promotion”))

WorseWorse BetterBetter

Negative Negative Stereotype Stereotype (“Prevention(“Prevention”)”)

BetterBetter WorseWorse

Flexibility advantageous (rule-based)

Flexibility disadvantageous (information-integration)

Page 43: The Influence of Motivation on Human Categorization and Decision Making

Experiments 1 and 2: Experiments 1 and 2: Flexibility AdvantageousFlexibility Advantageous

Page 44: The Influence of Motivation on Human Categorization and Decision Making

Experiment StructureExperiment StructureGainsGains LossesLosses

ExperimeExperiment 1nt 1

Positive Positive stereotypstereotyp

eeWomenWomen FitFit MismatcMismatc

hh

Negative Negative StereotypStereotyp

eeMenMen MismatcMismatc

hh FitFit

ExperimeExperiment 2nt 2

Positive Positive stereotypstereotyp

eeMenMen FitFit MismatcMismatc

hh

Negative Negative StereotypStereotyp

eeWomenWomen MismatcMismatc

hh FitFit

Page 45: The Influence of Motivation on Human Categorization and Decision Making

Stereotype Prime Example: Stereotype Prime Example: Women are better in gains Women are better in gains

tasktaskThis is an experiment testing sex differences in spatial This is an experiment testing sex differences in spatial abilities. Previous research has shown that women abilities. Previous research has shown that women perform better than men on tests of spatial ability.perform better than men on tests of spatial ability.

In this experiment, you will earn some points for In this experiment, you will earn some points for correct responses and no points for incorrect correct responses and no points for incorrect responses. In this task, women tend to earn more than responses. In this task, women tend to earn more than 86 points per block of trials and men tend to earn 86 points per block of trials and men tend to earn fewer than 86 points per block of trials. fewer than 86 points per block of trials.

Please try your best in this task. Before continuing, Please try your best in this task. Before continuing, please indicate whether you are male or female. If you please indicate whether you are male or female. If you are male, press the "M" key. If you are female, press are male, press the "M" key. If you are female, press the "F" key.the "F" key.

Page 46: The Influence of Motivation on Human Categorization and Decision Making

Task AccuracyTask Accuracy

0.7

0.75

0.8

0.85

0.9

0.95

1

Gains Losses

Reward Structure

Prop

ortio

n C

orre

ct

WomenMen

Experiment 1: Women Positive Stereotype

Experiment 2: Men Positive Stereotype

0.7

0.75

0.8

0.85

0.9

0.95

1

Gains Losses

Reward Structure

Prop

ortio

n C

orre

ctWomenMen

Prop

ortio

n C

orre

ct

Prop

ortio

n C

orre

ct

Page 47: The Influence of Motivation on Human Categorization and Decision Making

Model ResultsModel Results

00.10.20.30.40.50.60.70.80.9

1

Gains Losses

Reward Structure

Prop

ortio

n C

J U

se

WomenMen

Experiment 1: Women Positive Stereotype

Experiment 2: Men Positive Stereotype 0

0.10.20.30.40.50.60.70.80.9

1

Gains Losses

Reward Structure

Prop

ortio

n C

J U

seWomenMen

Prop

ortio

n C

J Use

Prop

ortio

n C

J Use

Page 48: The Influence of Motivation on Human Categorization and Decision Making

ConclusionsConclusions

Stereotype threat manipulations led to behavior also observed under a prevention focus. When flexible strategy use is advantageous:

a negative stereotype is disadvantageous in a gains condition. a negative stereotype is ADVANTAGEOUS in a losses condition.

Page 49: The Influence of Motivation on Human Categorization and Decision Making

Flexibility PredictionsFlexibility PredictionsGainsGains LossesLosses

Positive Positive stereotype stereotype (“Promotion”)(“Promotion”)

BetterBetter WorseWorse

Negative Negative Stereotype Stereotype (“Prevention”)(“Prevention”)

WorseWorse BetterBetter

GainsGains LossesLossesPositive Positive stereotype stereotype (“Promotion”(“Promotion”))

WorseWorse BetterBetter

Negative Negative Stereotype Stereotype (“Prevention(“Prevention”)”)

BetterBetter WorseWorse

Flexibility advantageous(rule-based)

Flexibility disadvantageous

(information-integration)

Page 50: The Influence of Motivation on Human Categorization and Decision Making

Information-integration Information-integration ClassificationClassification

Page 51: The Influence of Motivation on Human Categorization and Decision Making

Experiment StructureExperiment StructureGainsGains LossesLosses

ExperimeExperiment 3nt 3

Positive Positive stereotypstereotyp

eeMenMen FitFit MismatcMismatc

hh

Negative Negative StereotypStereotyp

eeWomenWomen MismatcMismatc

hh FitFit

ExperimeExperiment 4nt 4

Positive Positive stereotypstereotyp

eeWomenWomen FitFit MismatcMismatc

hh

Negative Negative StereotypStereotyp

eeMenMen MismatcMismatc

hh FitFit

Page 52: The Influence of Motivation on Human Categorization and Decision Making

Task AccuracyTask Accuracy(Preliminary data)(Preliminary data)

0.7

0.75

0.8

0.85

0.9

0.95

1

Gains Losses

Task

Prop

ortio

n C

orre

ct

WomenMen Experiment 3:

Men Positive Stereotype

Experiment 4: Women Positive Stereotype

0.7

0.75

0.8

0.85

0.9

0.95

1

Gains Losses

Task

Prop

ortio

n C

orre

ct

Women

Men

Positive Stereotype = worse performanceHypothesis supported for gains, but not losses

Page 53: The Influence of Motivation on Human Categorization and Decision Making

Preliminary Preliminary ConclusionsConclusions

When flexible strategy use is disadvantageous:

a negative stereotype is ADVANTAGEOUS in gains and losses conditions.

Data collection and modeling is ongoing.

Page 54: The Influence of Motivation on Human Categorization and Decision Making

Application Application 3:3:

Choking Choking Under Under

PressurePressureMarkman, Maddox & Worthy (2006; Markman, Maddox & Worthy (2006; Psychological Science)Psychological Science)

Page 55: The Influence of Motivation on Human Categorization and Decision Making

Choking Under PressureChoking Under Pressure Anecdotal phenomenon (e.g. sports, Anecdotal phenomenon (e.g. sports,

test-taking, etc.)test-taking, etc.)

Much like stereotype threat, people Much like stereotype threat, people perform worse than normal when perform worse than normal when under pressureunder pressure

Might pressure be similar to a Might pressure be similar to a prevention focus?prevention focus?

Page 56: The Influence of Motivation on Human Categorization and Decision Making

Choking Under PressureChoking Under Pressure Basketball dataBasketball data Free throw during last minute of gameFree throw during last minute of game

Proportion of Free-Throws Made Relative Career Averages

-0.10

-0.08

-0.06

-0.04-0.02

0.00

0.02

0.04

0.06

-5 -4 -3 -2 -1 0 1 2 3 4 5

Point Margin

Dis

tanc

e fro

m B

asel

ine

Page 57: The Influence of Motivation on Human Categorization and Decision Making

Categorization TasksCategorization TasksRule-Based Information-Integration

Page 58: The Influence of Motivation on Human Categorization and Decision Making

MethodMethod Gains onlyGains only Low pressure – “do your best”Low pressure – “do your best” High pressure:High pressure:

-Paired with a ‘partner’-Paired with a ‘partner’-If both of you reach criterion, both get $6-If both of you reach criterion, both get $6-If one of you fails neither get $6 bonus-If one of you fails neither get $6 bonus-Partner reached criterion-Partner reached criterion

Low-Low-Pressure Pressure Rule-basedRule-based

High-High-Pressure Pressure Rule-BasedRule-Based

Low-Low-PressurePressureInformationInformation--IntegrationIntegration

High-High-PressurePressureInformationInformation--IntegrationIntegration

Page 59: The Influence of Motivation on Human Categorization and Decision Making

PredictionsPredictions

Low Pressure High Pressure

Rule-Based Fit: Good Mismatch : Poor

Information-integration Fit: Poor Mismatch:

Good

Rule-based: Rule-based: Low pressure = Fit = flexible = good performanceLow pressure = Fit = flexible = good performance

Information-integration:Information-integration: Low pressure = Fit = flexible = poor performanceLow pressure = Fit = flexible = poor performance

Page 60: The Influence of Motivation on Human Categorization and Decision Making

Results Results Accuracy

0.54

0.56

0.58

0.6

0.62

0.64

0.66

0.68

0.7

0.72

Information-Integration Rule-Based

Prop

ortio

n C

orre

ct

High PressureLow Pressure

Page 61: The Influence of Motivation on Human Categorization and Decision Making

Rule-Based ModelingRule-Based Modeling

More low pressure (fit) subjects were best fit by the More low pressure (fit) subjects were best fit by the rule-based models.rule-based models.

More high pressure (mismatch) subjects are More high pressure (mismatch) subjects are random.random.

Rule-Based

0%

20%

40%

60%

80%

100%

Low Pressure High Pressure

Perc

ent B

est F

it

RandomInfo-IntRule-Based

Page 62: The Influence of Motivation on Human Categorization and Decision Making

Information integration Information integration modelingmodeling

More high pressure subjects best fit by an More high pressure subjects best fit by an information integration model.information integration model.

More low pressure subjects random.More low pressure subjects random.

Information-Integration

0%

20%

40%

60%

80%

100%

Low Pressure High Pressure

Perc

ent B

est F

it

RandomRule-BasedInfo-Int

Page 63: The Influence of Motivation on Human Categorization and Decision Making

SummarySummary Pressure does appear to operate like a prevention focus during classification learning (at least with gains).

Pressure (a mismatch with gains) hurts rule-based learning, but helps information-integration learning.

Extensions to highly learned categories are ongoing.

Page 64: The Influence of Motivation on Human Categorization and Decision Making

Application Application 4:4:

Choice-Choice-Gambling Gambling

TaskTaskWorthy, Maddox & Markman (in press; Worthy, Maddox & Markman (in press; Psychonomic Bulletin and Review)Psychonomic Bulletin and Review)

Page 65: The Influence of Motivation on Human Categorization and Decision Making

0

PICK A CARD! YesBonus No

450

174

Page 66: The Influence of Motivation on Human Categorization and Decision Making

0

174181

YesBonus No

450

7

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0

PICK A CARD! YesBonus No

450

181

Page 68: The Influence of Motivation on Human Categorization and Decision Making

0PICK A CARD!

YesBonus No

-450

-311

Page 69: The Influence of Motivation on Human Categorization and Decision Making

0

-311-315

YesBonus No

-450

-4

Page 70: The Influence of Motivation on Human Categorization and Decision Making

0PICK A CARD!

YesBonus No

-450

-315

Page 71: The Influence of Motivation on Human Categorization and Decision Making

Deck CharacteristicsDeck Characteristics Experiment 1: Flexibility (exploration) is good

Disadvantageous deck early becomes advantageous as more samples are taken

Experiment 2: Flexibility (exploration) is bad One deck advantageous

Page 72: The Influence of Motivation on Human Categorization and Decision Making

Flexibility PredictionsFlexibility PredictionsGainsGains LossesLosses

PromotionPromotion BetterBetter WorseWorse

PreventionPrevention WorseWorse BetterBetter

BetterBetterPreventionPrevention

WorseWorsePromotionPromotion

GainsGains

Flexibility advantageous

Flexibility disadvantageous

Page 73: The Influence of Motivation on Human Categorization and Decision Making

Flexibility is Advantageous Flexibility is Advantageous Results Results

Average Distance from Criterion

-40

-35

-30

-25

-20

-15

-10

-5

0GAIN LOSS

Poin

ts B

elow

Crit

erio

n

Promotion Prevention

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Flexibility is Flexibility is Disadvantageous Results Disadvantageous Results

Average Distance from Criterion

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Poin

t Bel

ow C

riter

ion

Promotion Prevention

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Model-based AnalysesModel-based Analyses Applied a version of the softmax action selection model to individual subject data (Sutton, Barto, Daw, etc)

Model estimates probability of selecting each deck based on estimated value.

Includes an exploration/exploitation parameter

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Modeling ResultsModeling ResultsExploration/Exploitation parameter values

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Gains Losses

Expl

orat

ion-

Expl

oita

tion

Promotion Prevention

Exploration-Exploitation Parameter Values

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Expl

orat

ion-

Expl

oita

tion

Promotion Prevention

Flexibility is Good

Flexibility is Bad

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SummarySummary Regulatory Fit hypothesis applies to choice.

Fit leads to greater exploration.

Extensions to decks that require numerous switches are ongoing.

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Application Application 5:5:

Signal Signal DetectionDetection

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OverviewOverview Two-stimulus identification (line length)

100ms exposure durations, 2 pixel length difference Promotion/Prevention x Gains/Losses Payoffs biased toward “short” mouth

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Results: Sensitivity (d’)Results: Sensitivity (d’)B

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1 2 3 Overall

Block (100-trials per block)

d'

Promotion-GainPromotion-LossPrevention-GainPrevention-Loss

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Results: Sensitivity (Results: Sensitivity ())C

0.6

0.8

1.0

1.2

1.4

1.6

1.8

1 2 3 Overall

Block (100-trials per block)

Beta

Promotion-GainPromotion-LossPrevention-GainPrevention-Loss

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SummarySummary Predicted fit to lead to better decision criterion learning.

Prediction unsupported.

Fit increased sensitivity.

Studies with more extensive training are ongoing.

Applications to depressed patients ongoing.

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Overall SummaryOverall Summary We outline a framework for understanding the We outline a framework for understanding the

motivation-learning interface.motivation-learning interface. Global: promotion/prevention focusGlobal: promotion/prevention focus Local: gains/lossesLocal: gains/losses Most research involves a promotion focus and Most research involves a promotion focus and

gains.gains. We propose that a fit leads to more flexible We propose that a fit leads to more flexible

(exploratory) processing(exploratory) processing This may or may not be advantageousThis may or may not be advantageous We apply this to several domainsWe apply this to several domains

Classification, choice, signal detectionClassification, choice, signal detection

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Open QuestionsOpen Questions Does a fit imply:Does a fit imply:

More efficient exploration of the strategy space, More efficient exploration of the strategy space, oror

Less evidence to abandon a rule?Less evidence to abandon a rule?

Is flexibility always from simple to complex Is flexibility always from simple to complex rules?rules? Bias toward complex rule initially, then gradually Bias toward complex rule initially, then gradually

introduce simple rule that yields bonus.introduce simple rule that yields bonus.

What is the relationship between exploration What is the relationship between exploration in the verbal rule-space and in the card task?in the verbal rule-space and in the card task?

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Future DirectionsFuture Directions Understand mental disordersUnderstand mental disorders Many disorders lead to cognitive deficitsMany disorders lead to cognitive deficits

Do these reflect disruptions of information Do these reflect disruptions of information processing?processing?

Perhaps they reflect motivational issuesPerhaps they reflect motivational issues Anxiety disorders may lead to chronic Anxiety disorders may lead to chronic

prevention focusprevention focus Could lead to regulatory mismatchesCould lead to regulatory mismatches

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Collaborators/Collaborators/FundingFunding

Darrell WorthyDarrell WorthyLisa GrimmLisa GrimmBrian GlassBrian GlassGrant BaldwinGrant Baldwin

Supported by NIMH R01 MH77708 and AFOSR grant FA9550-06-1-0204