Title: Cognitive%20Psychology
1Cognitive Psychology
2(No Transcript)
3What do these have in common?
- You are driving to a lunch date, and accidentally
take the route to your job. After you correct
your route, as you are driving by the theatre, a
red ball chased by a child suddenly appears on
the street, and you screech your brakes. You get
to the restaurant and try to find your friend,
who has flaming red hair. The restaurant is
packed, its hard to make-out faces, but you can
see peoples hair so you look for red hair. When
you get to your table your friend asks if you
noticed the Star Wars promotion with two costumed
people fighting with light sabers. As you talk
about important but dull business, your mind
keeps drifting to your exciting first date last
night. You force yourself not to think about it,
but it keeps coming back.
4- Innatentional Blindness (original experiment)
- http//www.youtube.com/watch?vvJG698U2Mvo
- Change Blindness (office) https//www.youtube.com/
watch?vdiGV83xZwhQ
5Change Blindness
- Counter experiment http//www.youtube.com/watch?v
mAnKvo-fPs0 - Campus Door Demo
- http//viscog.beckman.uiuc.edu/flashmovie/12.php
- Construction door http//viscog.beckman.uiuc.edu/f
lashmovie/10.php - Gradual Change http//viscog.beckman.uiuc.edu/fla
shmovie/1.php
6Aspects of Attention
- Detection.
- Filtering and selection.
- Search.
- Automatic processing.
- Concentration.
7Architecture
Sensory Store
LTM
STM
Filter
Pattern Recognition
Selection
Input (Environment)
Response
8Attention
- In this model, attention is
- The filter and selection boxes
- The arrows.
- The special job carried out by each of these
boxes according to different theories of
attention - (Yes, this is cheating)
- In this model attention
- Puts together information from various sources.
- Gets information into STM
- Works in imagery
9Detection
- Two kinds of thresholds
- Absolute Threshold Minimum amount of
stimulation required for detection. - Difference Threshold (Just Noticeable
Difference) Amount of change necessary for two
stimuli to be perceived as different.
10Detection
- Absolute Thresholds
- Vision One candle, on a mountain, perfectly
dark, 30 miles. - Hearing A watch ticking 20 feet away.
- Smell A single drop of perfume in a three room
apartment. - Touch The wing of a bee on your cheek.
- Taste One teaspoon of sugar in two gallons of
water.
11Determining Thresholds
- How to determine thresholds
- Method of limits
- Ascending Start with a value below the
threshold, increase, ask for detection, increase
At the point a person says detect, average
that stimulus value with the value from the
previous trial. Repeat to estimate threshold. - Descending Same, but start above threshold and
work down. - Combining results from both directions will give
you an estimate of the threshold.
12Determining Thresholds
- How to determine thresholds
- Method of constant stimuli
- Present a series of randomly selected stimulus
values, ask for yes/no response for each. The
value thats detected 50 of the time is the
threshold. - These methods can be adapted to determine
difference thresholds.
13Determining Thresholds
- We think thresholds work like a step function,
but they dont. They are sigmoid or ogive curves
This graph represents an ogive-curve and how
detection really changes it is a gradual slope.
The threshold is defined as a 50 detection rate.
This graph represents a step function. Below the
threshold there is 0 detection. Above the
threshold, there is 100 detection. This is the
way we normally believe our perception to work.
14Determining Thresholds
- Difference Threshold
- Webers Law K ?I / I
- K is the Konstant
- ? is the difference
- I is the stimulus intensity
- The formula states that the threshold for
noticing a difference (whether its the length of
a line or weight of a dumbell) is a constant
ration between the old / background stimulus
and the new / target stimulus.
15Determining Thresholds
- Early Researchers Noticed Thresholds Shift!
These are ogive curves for stimuli of the same
intensity but with different signal to noise
ratios or payoff matrix
- How to get around this problem A model that
accounts for signal to noise ratios and payoff
matrixes ? Signal Detection Theory
16Signal Detection
- Can estimate detection (sensitivity) independent
of bias. - Two kinds of trials
- Noise alone Background noise only.
- Signalnoise Background noise with signal.
- Two responses from observer
- Detect.
- Dont detect.
17Signal DetectionFour Situations
State of the world State of the world
Response Signal Noise
Yes (Present) Hit False Alarm
No (Absent) Miss Correct Rejection
18Hits(response yes on signal trial)
Criterion
N
SN
Probability density
Say yes
Say no
Internal response
19Correct rejects(response no on no-signal trial)
Criterion
N
SN
Probability density
Say yes
Say no
Internal response
20Misses(response no on signal trial)
Criterion
N
SN
Probability density
Say yes
Say no
Internal response
21False Alarms(response yes on no-signal trial)
Criterion
N
SN
Probability density
Say yes
Say no
Internal response
22Signal DetectionSensitivity and Bias
- We can estimate two parameters from performance
in this task - Sensitivity Ability to detect.
- Good sensitivity High hit rate low false
alarm rate. - Poor sensitivity About the same hit and false
alarm rates. - Response Bias Willingness to say you detect.
- Can be liberal (too willing) or conservative (not
willing enough). - For example, if the true signal to noise ratio is
50 and you have a 75 detection rate, then your
response bias is to be too liberal.
23Signal DetectionSensitivity and Bias
- Computing sensitivity or d (d-prime)
- Is a measure of performance (like percent
correct, or response time) - Typical values are from 0 to 4 (greater than 4 is
hard to measure because performance is so close
to perfect) - A d-prime value of 1.0 is often defined as
threshold.
24d-Prime
- d-prime is the distance between the N and SN
distributions - d-prime is measure in standard deviations
(Z-Scores) - In SDT, one usually assumes the two underlying
distributions are normal with equal variance
(i.e., both curves have the same standard
deviation)
25Signal DetectionSensitivity and Bias
- Computing bias
- The criterion is the point above which a person
says detect. It can be unbiased (the point
where the distributions cross 1.0), liberally
biased (lt 1.0), or conservatively biased (gt 1.0).
26Signal DetectionSensitivity and Bias
- Since sensitivity and bias are independent, you
can measure the effect of different biases on
responding to a particular value for
detectability. - Influences on bias
- Instructions (only say yes if youre absolutely
sure). - Payoffs (big reward for hits, no penalty for
false alarms). - Probability of signal (higher probability leads
to more liberal bias).
27Signal DetectionSensitivity and Bias
- Receiver operating characteristic (ROC) curves
- For a given detectability value, you can
manipulate the hit and false alarm rates. An ROC
curve shows the effect of changing bias for that
level of detectability.
28Sample ROC Curves
of Hits
29Optimal Performance
- Depending on the probability of a signal trial
and the payoff matrix, the optimal placement of
the criterion will vary. - p(N) value (CR) - cost (FA)
- ?opt X
- p(S) value (H) - cost (M)
- You can compare performance to the ideal observer
to assess the operator.
30Examples of Visual Search
Is there a threat?
Wheres Waldo?
31Search
- How do you use attention to locate items in a
complicated array? Two kinds of search Feature
Search and Conjunction Search. - Feature search A single feature allows you to
find the item you are searching for. - Find the blue S.
32Search
X T X T
X T S X
T X X X
T T X T
33Search
X T X T T T X T
X T X X T X T T
T X S T X X T X
X X T X T X T X
T X T T X T X T
34size Treisman Gelade 80 Healey Enns 98
Healey Enns 99x
length, width Sagi Julész 85b Treisman
Gormican 88
line (blob) orientation Julész Bergen 83 Sagi
Julész 85a, Wolfe et al. 92 Weigle et al. 2000
closureJulész Bergen 83
colour (hue) Nagy Sanchez 90 Healey 96 Bauer
et al. 98 Healey Enns 99
density, contrast Healey Enns 98 Healey Enns
99
curvature Treisman Gormican 88
35Search
- How do you use attention to locate items in a
complicated array? - Conjunction search You have to combine features
to find the item you are searching for. This
should take attention and be more difficult
(Treisman, 1988). - Find the green T.
36Search
X T X T
X T T X
T X X X
T T X T
37Search
X T X T T T X T
X T X X T X T T
T X T T X X T X
X X T X T X T X
T X T T X T X T
X T X T
X T T X
T X X X
T T X T
38Simple feature search Look for an O
39Simple feature search Look for something red
40Conjunctive feature search Look for something red
AND O
41Conjunctive Search
Response Time
Simple feature search
Number of Stimuli in Display
42Properties of searches
- Feature searches
- Dont require attention (pop-out).
- No help from location cueing (dont need it).
- Conjunction searches
- Require attention.
- Affected by the number of distracters.
- Helped by cueing the location.
43Pop-Outs in Advertisement
44Scan Paths
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46Feature Conjunction Attention as Glue
The significance between conjunctive and
disjunctive searches is that it means that
individual features like color and size are
loaded pre-attentively (attention is not
required), but a conjunctive search requires
attention to bind the two features to the object
to a location in space. You need attention to
know an object is both red and large and where it
is. The integration may happen in the visual
cortex as a result of synchrony, with attention
affecting the tuning properties of sensory
neurons, and preparing other cognitive processes
like working memory.
47Attention as GlueKeep your eye on the fixation
point below. A screen with colored letters will
be briefly flashed. Try to remember as many
letters with their colors as you can.
48L
S
O
P
Q
M
Q
H
U
X
B
T
K
V
Z
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50Attention as a Glue
- What color was the X?
- Do you distinctly recall a particular letter
being a different color? How did that happen? How
did a color in one location get associated with
an object in another location? - This is attention as a glue
51Treismans Feature Integration Theory
- A two-stage theory of visual attention.
- Stage 1. fast parallel for single features
- Stage 2. Slow serial for conjunctions of single
features. - Several primary visual features are processed and
represented with separate feature maps that are
later integrated in a saliency map that can be
accessed in order to direct attention to the most
conspicuous areas. - A parallel search, a red circle amidst green
circles, takes no time no matter how many green
circles (its cheap). A serial search, with
conjunction features, like red circles amidst
black circle and red triangles, requires you to
check each distractor serially.
52Automatic Processing
- After practice, some tasks no longer require
attention. Three criteria for automatic tasks - Occur without intention.
- When the load is low
- Required reaction times are short
- The tasks are over-learnt or well-practiced
- No conscious awareness/Cant be introspected.
- Dont interfere with other activities.
- Fast processes -- the brain does them
automatically, they are a basic feature - You can tell how the process of automatization is
going by doing dual task studies (primary and
secondary).
53Automatic Processing
- Read the Words.
- Say the colors
- Which is harder?
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55Automatic Processing
- You did the Stroop task.
- The interpretation is that you automatically read
the word. If thats the task, the color doesnt
interfere because you dont automatically
register that. If youre supposed to name the
color, automatic reading messes you up.
56Filtering
- So, thresholds shiftbut once set, then what?
What happens when something gets over the
threshold wherever it is? When does meaning
become involved? - How do we choose what to attend to? Is the choice
made early or late?
57Themes
- Early or Late? In other words, does something get
chosen before or after (respectively) the
stimulus gets stamped with meaning - What is attention?
- Some sort of bottleneck or filter?
- A capacity or resource (or several kinds)?
- Can we learn something by looking for it in
brains?
58Filtering
- Early Broadbent. Selection happens at the filter
and sensory store before pattern recognition. The
selection is made at the EARLY STAGE of crude
physical analysis.
59Filtering
- Early Evidence
- Dichotic listening. Two messages, one to each
ear, played simultaneously. - Shadowing Repeat out loud everything in one ear.
What do people (or what dont people) notice in
the unattended ear? - Miss change of speaker.
- Miss change of language.
- Miss change of direction.
60Filtering
7-4-1
3-2-5
- Early Evidence
- Filter flapping Two sets of numbers come in, one
set in each ear. - Report by ear Easy.
- Report in order Hard.
- The argument is that the filter lets in all of
one channel, then the other, no problem. To
switch back and forth takes a lot of effort.
61Filtering
- Problem for early models
- People detect their name on the unattended
channel (cocktail party phenomenon). - Treisman (1960) If a shadowed story switches
ears, people follow it, and then correct. They
have to be attending to meaning to follow the
story.
62Filtering
- Problem for early models
- Example 1
- I SAW THE GIRL/song was WISHING
- me that bird/JUMPING in the street
- Example 2
- AT A MAHOGANY/three POSSIBILITIES
- look at these/TABLE with her head
63Filtering
- Attenuation model
- Everything in memory is active at some resting
level. Some stuff thats important has a high
resting level, making it easier to respond to
(e.g., your name). - Other stuff has a low resting level, making it
harder to respond to. - As you think about something, you raise its
activity level.
64Filtering
- Attenuation model
- The unshadowed ear is attenuated (the volume is
low). This little bit of attention can reach
something with a high resting level (your name, a
story youre shadowing), but not some random bit
of information. - So, no filter, just attenuation.
65Filtering
- Capacity model
- You have a certain amount of attention, you can
spread it around as needed. If you spend a lot on
one task, then you have less for others. - Primary task Do well on this no matter what
(main focus of resources). - Secondary task Also do this.
- By manipulating the difficulty of the primary
task and measuring the secondary task, we can see
how attention allocation affects performance.
66Filtering
- Capacity model
- For example, Johnston and Heinz (1978) had two
tasks - Primary Shadow one ear for a change that is easy
(gender) or a change that is hard (category). - Secondary Detect a light.
67Filtering
- Capacity model Johnston and Heinz (1978)
Primary Secondary
Shadow one list (control) 1.4 error 310 ms
Easy (gender) 5.3 error 370 ms
Hard (category) 20.5 error 482 ms
68Filtering
- Capacity model
- What this implies is that the filter can be early
(gender) or late (category), the amount of your
resources that you allocate to it determines
where the filter is.
69Emotion Driving Attention
- Detecting a Snake in the Grass (Ohman, Flykt,
Esteves, 2001) - Stimuli snakes, spiders, mushrooms, flowers
- Presented in 2x2 or 3x3 displays
- Task Do all the pictures belong to the same
category?
70Emotion Drives Attention
- Reaction time to detect target in ms.
Fearful Neutral
2x2 950 1010
3x3 950 1010
71Emotion Drives Attention
- The Emotional Stroop Effect
- You are slower at naming a color of emotionally
charged words than neutral words - Taboo words vs neutral words
72Emotion Drives Attention
RED GREEN BLACK YELLOW BLUE RED BLACK
RED GREEN BLACK YELLOW BLUE RED BLACK
73 74 75 76 77 78 79 80 81 82 83 84 85Emotion Drives Attention
86Emotion Drives Attention
- Emotional Stroop effect occurs with
- Taboo words
- Alcohol words (beer) in alcoholics
- Smoking words (cigarettes) in smokers
- Spider words (web, crawl) in arachnophobics
- Food pictures in females with anorexia
- Threat words (disease) with people with anxiety
disorders
87The Dot Task Detection in PTSD
88Mood and Attention Levels of Focus (Gasper
Clore, 2002)
- Hypothesis Affective cues may be experienced as
task-relevant information, which then influences
global versus local attention. - Mood Manipulation Subjects randomly assigned to
write about a happy or sad event in their lives - Each participant randomly assigned to a drawing
chain, where the first person in each group saw a
drawing of an African shield with the title of
Portrait of a Man. In a later session, a 2nd
person saw the 1st persons reproduction from
memory, and so on.
89Local Global
- Lesions in LH produce deficits in local
perception - Lesions in RH produce deficits in Global
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91Mood and Attention Levels of Focus (Gasper
Clore, 2002)
- Happy Mood condition more likely than Sad Mood to
contain schema-relevant details like title and
facial features - Sad Mood drawings became less face-like down the
chain but not Happy Mood drawings - Sad Mood drawing looked less like original
92Mood and Attention Levels of Focus (Gasper
Clore, 2002)
- Experiment 2 employed a task in which the same
objects were sometimes the global and sometimes
the local stimulus (Kimchi Palmer, 1982).
Participants saw an overall shape (e.g., a
triangle) made up of smaller geometric figures
(e.g., triangles). Their task was to indicate
which of two other figures (e.g., a square made
of triangles or a triangle made of squares) was
more similar to this target figure.
Result Sadder people base their decisions on the
local features, and report doing so.
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98Posner Cueing Task
Peripheral Cue condition triggers exogenous
attention/ Reflexive attention Bottom-up
Central Cue condition triggers endogenous
attention / voluntary attention Top-down
99Inhibition of ReturnThe Been There, Done That
Reflex
- We are faster at unpredicted cues after a long
enough pause - IOR prevents going over the same ground, promotes
searches for novel stimuli
100- The findings from patients with brain damage led
Posner to construct a model for attention that
involves three separate mental operations - Disengaging of attention from the current
location - Moving attention to a new location
- Engaging attention in a new location to
facilitate processing in that location.
101Psychological Refractory Period (PRP)Timing the
Central Bottleneck
- A Multiple sensory input
- B Serial Decision maker
- C Multiple action output
A
B
C
Stimulus 1
A
B
C
PRP
Stimulus 2
SOA
Time
Slope 1
102Embodied cognition of attention is Cognition
Time-Pressured?
- If we were designed to perform under pressure, we
would be good at it. - But, the reality is that, under time pressure we
fall apart - We actively avoid operating under conditions
where we are time pressured - Most of daily behavior consists of mundane,
routine behavior
103Embodied Cognition is Time PressuredWilson, 2002
- Summary
- Perceptuomotor processes are time-pressured, but
that does not illuminate cognitive performance
under time pressure - Difficult to interpret whether cognition is time
pressured means we evolved to perform under
pressure or that our cognitive abilities must be
understood in the context of coping with
(unsuccessfully) or avoiding time pressures
104(No Transcript)
105- Line Bisection and flower drawing are examples of
spatial-based neglect. - The dumb-bells are an example of object based
neglect
106(No Transcript)
107IMPLICIT ASSOCIATION TEST
108CATEGORY SWITCH
?
?
Get Kristin's demo
?
?
?
?
109WORD CATEGORIZATION
?
?
?
?
?
?
?
110IMPLICIT ATTITUDES
111IMPLICIT BELIEFS
2000
Reaction Time
1500
1000
500
0
Insects Good
Insects
Bad
112Stereotype Threat(Beilock McConnell, 2004)
- People perform in compliance with stereotypes
- In one of the first studies on stereotype threat,
Steele and Aronson (1995) had high-achieving
African American and Caucasian students at
Stanford University complete a portion of the
graduate record exam (GRE). - Prior to doing so, some students were told that
the test was diagnostic of intellectual ability
whereas others were told that the test was a
laboratory problem-solving task not diagnostic of
intellectual ability.
113Stereotype Threat(Beilock McConnell, 2004)
- Results demonstrated that after controlling for
SAT scores (to equate past academic performance),
there was no difference in GRE performance
between White and Black students for whom the
test was not framed as diagnostic of intellectual
ability. - Of those students who were told that the test was
diagnostic of intellectual ability, however,
African Americans performed significantly worse
than Caucasians. - Steele and Aronson argued that informing students
about the diagnosticity of the test activated the
negative cultural stereotype that Blacks are not
as intelligent as Whites, which contributed to
the less-than-optimal performance of African
Americans on a test assumed to gauge intelligence.
114Stereotype Threat Memory or Attention(Beilock
McConnell, 2004)
- How does stereotype threat work?
- One proposal is that stereotype threat produces
reduces working memory capacity - But past research has shown that stereotype
threat effects are most pronounced for expert
athletes, for whose abilities are highly
proceduralized, relying little on working memory. - On the other hand, expert athletes choke when
they start to pay too much attention to the steps
of their automatized processes this increased
attention can backfire and disrupt what should
have been fluent, proceduralized execution. This
idea is often termed the explicit monitoring
hypothesis.
115Stereotype Threat Memory or Attention(Beilock
McConnell, 2004)
- Do stereotype threats reduce working memory
capacity, or do stereotype threats prompt
explicit monitoring of automated procedures - Expert male golfers perform a putt, before or
after hearing a stereotype (men are poorer
putters than women) or receiving control
information (putting performance differs as a
function of skill level). - Experts who received stereotype did worse
116Stereotype Threat Memory or Attention(Beilock
McConnell, 2004)
- Now how to determine it is attention? Introduce a
dual-task - Experiment 2 (Beiock et al, 2003)
- Two groups with stereotyped and non-stereotyped
- One group performs putting alone
- Second group putts while listening for target
word - Results. Performance was the same for putters in
the dual single task who had no stereotype
threat. For putters with stereotype threat,
performance was better in dual-task condition
(Stereo-type Threat affects attention, not
memory)
117The End
118Quizz
- You drove home and did not stopping at the store.
- This was due to a search failure because the sign
for the store did not pop-out. - You have a lot on your mind, and you are easily
distracted - Going to the store is a conscious decision, but
you were filtering based on perceptual features - Driving home is an automatic process
- Driving home is a conditioned response
119Quizz
- Youre walking to class and thinking about a quiz
thats coming up. Someone calls your name, but
you dont hear them. - a) Your ROC curve is high.
- b) This counts as a hit
- c) You are filtering for perceptual features
- d) You are filtering for categorical or semantic
information - e) You didnt study and you cant hear people
while throwing-up
120Concentration
- Our last topic has to do with the task of paying
attention. - Sometimes you have to concentrate on something in
which you have no interest. - Sometimes you have to not think about something
in which you have an interest.
121Concentration
- Wegner, Schneider, Carter, and White (1987).
- Try not to think of a white bear.
- Five minutes, measure the number of times people
do it. - Or, try to think of it.
- Both are hard, with less activity later on.
122Concentration
- Wegner, Schneider, Carter, and White (1987).
- After suppression, its easier to keep thinking
about a white bear. - After expression, its still hard not to think of
a white bear at first, but people adapt.
123Embodied cognition of attention is Cognition
Time-Pressured?
- Cognition happens in real-time or runtime
- Cognition must cope with predators, prey,
stationary objects and terrain as fast as the
situation dishes them out. - How do you get robots to think about walking on
uneven terrain, or to swing from branch to
branch, or looking around a crowded room looking
for a soda without bumping into something - Story of legalizing sightdogs.
124Embodied cognition of attention is Cognition
Time-Pressured?
- Examples for
- Skilled hand movements, or time-locked
perceptuomotor activity (catching, throwing,
tying, walking) - Inhibition Of Return
- Exogenously driven attention
- Examples Against
- PRP
- Task-switching
- Trade offs between speed and accuracy in attention
125Quizz
- You are looking for a friend at a party. This
person has brown hair and is very tall. - You are performing a serial search, that will be
affected by the number of people there - You are performing two serial searches, and the
person will pop-out - You are performing a conjunction search which
will be affected by the number of people there - You are performing a conjunction search and the
person will pop-out because there is nobody
else there with those two qualities.
126Quizz
- The Titanic hitting an iceberg would be a pretty
good example of a - hit
- miss
- false alarm
- correct rejection
127Quizz
- Bob, an electrician, is trying to see how faint
he can make a light. He starts by turning the
light ON to its maximum, then turning it down
until he cannot see it. - a) Difference detection methods of limits
ascending - b) Difference detection method of constant
stimuli random - c) Absolute thresholds method of limits
descending - d) Absolute thresholds constant stimuli random
128Quizz
- In Signal Detection Theory, which of the
following is not true - attention requires more hits than false alarms
- there is a normal distribution for signal and one
for noise with the distance apart measured in
Z-scores - d-prime measures the difference between signal
and noise - bias and sensitivity are independent