Lindsay et al. (2004) Participants heard true and false stories about their childhood Group 1: saw a...

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Lindsay et al. (2004) ticipants heard true and false stories about their childhood Group 1: saw a classroom photo from 2 nd grade more likely to think false memories are true Group 2: no photo Cues enhance false memory!

Transcript of Lindsay et al. (2004) Participants heard true and false stories about their childhood Group 1: saw a...

Page 1: Lindsay et al. (2004) Participants heard true and false stories about their childhood Group 1: saw a classroom photo from 2 nd grade  more likely to think.

Lindsay et al. (2004)

Participants heard true and false stories about their childhood

Group 1: saw a classroom photo from 2nd grademore likely to think false memories are true

Group 2: no photo

Cues enhance false memory!

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Eyewitness testimony• Jury believes a confident witnessConfidence-accuracy correlation only 0.29200 people per day become accused based on eyewitness testimony

• Wells et al. (2000) - 40 cases where DNA evidence exonerated someone• 36 involved witness ID of innocent people• People served average of 8.5 years• 5 sentenced to death

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Pick the gunman (Wells & Bradfield, 1983):• Participants watched a videotape• Gunman in view for 8 seconds• Then picked gunman out of a lineup• Each participant picked someone• The gunman was not even IN the lineup

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Stanny & Johnson (2000)

ERRORS DUE TO ATTENTION

-during crime emotions are high-attention narrows as arousal increases (Easterbrook, 1959)

Fired weapon decreases memory for perpetrator, victim, etc.

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Ross el al. (1994)ERRORS DUE TO FAMILIARITY

Proxy: Go with the teacher who resembles robber

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Wells & Bradfield (1998):‘Good, you identified the suspect…’

[perpetratornot included]

ERRORS DUE TO SUGGESTION

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Con

fid

en

ce r

ati

ng

Items correctly identified

Asked questions

Not asked questions

Items not correctly identified

Shaw (1996)

CONFIDENCE (AND ERRORS) DUE TO POSTEVENT QUESTIONING

-saw items in room-recognition testGROUP#1: no follow-up questionsGROUP#2: follow-up questions refer to answers on recognition test

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What Is Being Done?

1. Don’t tell criminal is in this lineupthis caused 42% decrease in false ID (Malpass & Devine,

1981)

2. Increase similarity among lineup peoplemay decrease correct ID a bit, but will decrease errors as

well!

CH

OSE

IN

NO

CEN

T

CH

OSE

GU

ILTY

low highSIMILARITY

low highSIMILARITY

PERPETRATOR IN LINEUP

PERPETRATOR NOT IN LINEUP

Lindsay & Wells (1980)

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What Is Being Done?

3. In lineup, use sequential presentation, not simultanoeus-avoid making a relative judgment of comparing people

when suspect not in lineup: % of falsely identified is…

17%

43%

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10am

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concept : mental representation used for a variety ofcognitive functions

categorization is the process by which concepts areorganized in some systematic way

Concepts are building blocks of knowledge

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Why Categorize?understand new casesmake inferences about items in the categoryunderstand behaviorsnot to mention, organize our knowledge!

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Definitions

insufficient to place things in categoriesvariability within a categoryfunctional considerations

family resemblance : members of a category resemble one another in number of ways

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Prototypesaveraging the category members

prototypicality-high - member closely resembles prototype (sparrow)-low - member does not resemble typical (penguin)

“average” cat

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Demo 1 (Rosch & Mervis, 1975)

write as many characteristics or attributes that you feel are common to each object

chairsofamirrortelephone

prototypical objects have high family resemblancea lot of overlap with other items in the category

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Demo 2 (Smith et. al., 1974)

an apple is a fruita tomato is a fruita pomegranate is a fruita watermelon is a fruit

typicality effectstatements about prototypical items verified rapidly

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Demo 3list as many objects as you can for each category

office furnituretransportationcolors

prototypical objects named first

office furniture - desk, chair, lamp, couch... bookshelftransportation - car, bus, truck, train, bike... pogo stickcolors - red, blue, yellow, green, orange, purple, black, white, teal... tan

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prototypical objects affected more by priming

priming - presentation of one stimulus affects response to another

Rosch (1975)

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SUMMARY

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Exemplarscomparing to examples of members within a categoryatypical casesno ‘averaging’variable categories which are harder to form a prototype of

Exemplars & Prototypescomplementaryinitially try to form a prototypical member of categoryand later include exceptions (exemplars) that also fitcategory

smaller categories = exemplarslarger categories = prototypes

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11am

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Levelscategorization is organization of information

categories themselves are organized

hierarchical

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Basic Level Categories easiest to access and use

How many common features can you

name?

3

9

10.3

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Lose a lot of information

Gain just a little information

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Basic Level Categoriesname items at the basic level categoryfaster at deciding membership at the basic level

individual differences[experts don’t rely as much on this ‘basic-level’]

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Semantic Networksconcepts arranged in networks ~ the way concepts organized in the mind

model of knowledge representation

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Semantic Networks

Collins & Quillian (1969)

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Semantic Networks

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Predictionstime it takes a person to retrieve information is determined by distance traveled through network

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Spreading Activationactivity spreads out along any link connected to activated node

PRIMING!

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Priming EffectsMeyer & Schvaneveldt (1971)

lexical decision task - is it a word or not?

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Priming EffectsMeyer & Schvaneveldt (1971)

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Criticisms of Collins & Quillian

did not explain typicality effect (faster response for more typical members of a category):

“Canary is a bird.”“Ostrich is a bird.”

Collins et al. prediction: should be the same RT

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Collins & Loftus Modelnot hierarchical

link length is how ‘related’ the two items are

based on person’s experience

explains too much!

model that explains everything, explains nothing

adjusting length of connections fits any result!

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1pm

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knowledge = distributed activity of many unitsparallel distributed processing (PDP)

nodes

links (weights)

‘neuron-like’: excitation/inhibition

CONNECTIONISM

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McClelland & Rumelhart, 1986

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These patterns are learned, not hardwired

supervised learning

model makes mistakes and gets corrected

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TRIAL#1

TRIAL#2

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Contains knowledge of canary. Where?

In the pattern!

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graceful degradationdamage to part of the system does not disrupt all

generalizeabilitysimilar concepts have similar patterns of activation

computer models simulate it welllanguage processing

train on multiple conceptseach concept is ‘encoded’ in the network (weights)learns to respond to various inputsslow learning - so changes to weights don’t disrupt previous knowledge

Properties

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Criticisms

how many units?

how many levels?

how much training?

who trains?

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2pm

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VISUAL IMAGERY

How is the furniture arranged in your bedroom?Is the gas tank on the left or right side of your car?

No sensory input sensory impression

History of science:

Aristotle: “thought impossible without an image”Watson (behaviorism): images “unproven, mythological”

Paivio (1963): easier to remember concrete vs abstract nouns

Shepard & Metzler (1971):mental rotation

Same or different?

RT=f(angle)

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IMAGERY is like PERCEPTION

Mental scanning (Kosslyn, 1973):

Participants memorize image

• Move from one part of image to another

• Mental scan time is proportional to spatial distance

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IMAGERY is SPATIAL

Mental scanning (Kosslyn, 1978):

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IMAGERY is like LANGUAGE

Propositional, not spatial (Pylyshyn, 1973):

Spatial representation may be epiphenomenal

abstract&

symbolic

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IMAGERY is PROPOSITIONAL

RT=f (conceptual “distance”) : how many nodes away?

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…just like Semantic Networks

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Tacit Knowledge?

• Imagining = mental simulation• ...in the real world it takes longer to move from A to B• ...this fact is incorporated into imagining• what Kosslyn considers spatial is simply based on experiential knowledge about the world – not necessarily image-likeEvidence against Tacit knowledge:Finke & Pinker (1982)

[2 sec delay]

Distance (dot, arrow)

React

ion

tim

e

Was the arrow pointing at

the dot?

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3pm

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Does the bunny havewhiskers?

Kosslyn (1978)

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Interactions of imagery and perception

“Imagine a banana on the screen, and describe it.”Perky (1910)

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Priming again!

Farah (1985)

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Imagery and the brain

Krieman et al (2000): Neurons in the Temporal Lobe

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Imagery and the brainLeBihan et al (1993): Neurons in the Visual Cortex

fMR

I

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Transcranial Magnetic Stimulation (TMS): knock out parts of brain for few minutes

fMRI not causing imagery

Pylyshyn: fMRI may be epiphenomenon

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Transcranial Magnetic Stimulation (TMS): knock out parts of brain for few minutes

Perception & Imagery conditionswhich stripes are longer?RESULTS: TMS caused a slowdown in response timeslowdown for both perception and imagery

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4pm

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Removing part of the visual cortex decreases image size

Farah (1992)

NEUROPHYSIOLOGICAL EVIDENCE FOR VISUAL IMAGERY

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UNILATERAL NEGLECTBisiach & Luzzatti (1978)

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R.M.: Can visually identify objects in front of him, but can’t accuratelydescribe imagery from memory. “A grapefruit is larger than an orange.”

C.K.: Cannot visually identify, but can draw vivid andaccurate pictures based on imagery

NEUROPHYSIOLOGICAL EVIDENCE FOR VISUAL IMAGERY:DOUBLE DISSOCIATION

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Using imagery to improve memory

Visualizing interacting images enhances memory

Organizational effect of imagery enhances memory

Method of Loci

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Folk psychology & memory self-help books: bizarre imagery helps memory?

INTERACTING > NONINTERACTING BIZARRE == NONBIZARRE

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Mechanical problems: Hegarty (2004)

Schwarz & Black (1999)

Rule-based approach

Mental simulation

Which cup flows over earlier?0 delay: @ same angleAfter imagining: wide cup