outline of lecture i.intro to signal detection theory (words) ii.intro to signal detection theory...
DESCRIPTION
Signal Detection Theory S.D.T. is a procedure for measuring sensitivity to stimulation, independent of the subject’s response bias.TRANSCRIPT
Outline of Lecture
I. Intro to Signal Detection Theory (words)
II. Intro to Signal Detection Theory (pictures)
III. Applications of Signal Detection Theory
Part 1
Introduction to Signal Detection Theory
S.D.T. In Words
Signal Detection Theory
S.D.T. is a procedure for measuringsensitivity to stimulation, independent of the subject’s response bias.
Detection Experiment• We want to measure a subject’s ability to
detect very weak stimuli.
• Signal Detection Theory requires a “Type A” experiment.
• How do we know when the subject is objectively incorrect?
“Catch Trials”
The subject is asked to make a responsewhen no stimulus has been presented(also called “noise only” trials).
Not All Errors Are Equal
1. Reporting stimulus is present when it’s absent (“false alarm”).
Versus
2. Reporting stimulus is absentwhen it’s present (“miss”).
Correct Responses Differ, Too
1. Reporting stimulus is present when it’s present (“hit”).
Versus
2. Reporting stimulus is absentwhen it’s absent (“correct rejection”).
Stimulus-Response Matrix
Response
Stim
ulus
“No” “Yes”
Pres
ent
Abs
ent
Miss
CorrectRejection
Hit
FalseAlarm
Stimulus-Response Matrix
Response
Stim
ulus
“No” “Yes”
Pres
ent
Abs
ent
Miss
CorrectRejection
Hit
FalseAlarm
Type I error
Type II error
Signal Detection Theory
S.D.T. reduces the stimulus-responsematrix to two meaningful quantities.
1. Detectability (d’) - a subject’s sensitivity to stimulation.
2. Criterion () - a subject’s inclination to favor a particular response; bias.
Part 2
Introduction to Signal Detection Theory
S.D.T. In Pictures
Distributions of Sensory ResponsesPr
obab
ility
Level Of Neural Activity (Arbitrary Units)
Distributions of Sensory ResponsesPr
obab
ility
Level Of Neural Activity (Arbitrary Units)
Spontaneous Activity is Constant
Distributions of Sensory ResponsesPr
obab
ility
Level of Neural Activity (Arbitrary Units)
Spontaneous Activity is Normally Distributed
The “Noise”Distribution
Distributions of Sensory Responses
The “Noise”Distribution
The “Signal + Noise” Distribution
A Mild Stimulus is Presented (d’=1)
Prob
abili
ty
Level of Neural Activity (Arbitrary Units)
d'
Distributions of Sensory Responses
The “Noise”Distribution
The “Signal + Noise” Distribution
A Moderate Stimulus is Presented (d’=2)
Prob
abili
ty
Level of Neural Activity (Arbitrary Units)
d'
Distributions of Sensory ResponsesPr
obab
ility
Level of Neural Activity (Arbitrary Units)
d'
The “Noise”Distribution
The “Signal + Noise” Distribution
An Intense Stimulus is Presented (d’=3)
Distributions of Sensory Responses
Sub-Threshold Stimulus is Presented (d’=0)
Prob
abili
ty
Level of Neural Activity (Arbitrary Units)
The “Noise”Distribution
The “Signal + Noise” Distribution
About d’
So, d’ is a statistic for measuring perceptual sensitivity.
About d’
So, d’ is a statistic for measuring perceptual sensitivity.
Also, d’ often refers to “detectability”,and “discriminability” in perceptual experiments.
About d’
So, d’ is a statistic for measuring perceptual sensitivity.
Also, d’ often refers to “detectability”,and “discriminability” in perceptual experiments.
A high d’ value -----> good performance:
A low d’ value -----> poor performance.
About Bias
Now let’s consider THAT OTHERaspect of behavior… bias.
About Bias
Bias: The inclination to favor a particular response.
Example: The inclination to favor the “yes, I see it” response
over the “no, I don’t see it” response.
About Bias
Signal Detection Theory assumes that Bias can be measured according to a criterion.
Criterion: A rule for converting sensory activityinto an overt response.
Prob
abili
ty
Level of Neural Activity (Arbitrary Units)
"No, I don'tsee it"
"Yes,I see it"
Criterion
The “Noise”Distribution
The “Signal + Noise” Distribution
Neutral Criterion
The “Noise”Distribution
The “Signal + Noise” DistributionPr
Pr o
f S+N
Neural Activity"No" "Yes"
Hits Misses
Pr o
f N FalseAlarms
CorrectRejections
Stimulus-Response Matrix
Response
Stim
ulus
“No” “Yes”
Pres
ent
Abs
ent
Miss
CorrectRejection
Hit
FalseAlarm
Neutral Criterion
The “Noise”Distribution
The “Signal + Noise” DistributionPr
Pr o
f S+N
Neural Activity"No" "Yes"
Hits Misses
Pr o
f N FalseAlarms
CorrectRejections
Liberal (low) CriterionPr
Pr o
f S+N
Neural Activity"No" "Yes"
Hits Misses
Pr o
f N FalseAlarms
CorrectRejections
The “Noise”Distribution
The “Signal + Noise” Distribution
Conservative (high) Criterion
The “Noise”Distribution
The “Signal + Noise” Distribution
Pr o
f S+N
Neural Activity
Hits Misses
"No" "Yes"
PrPr
of N False
Alarms
CorrectRejections
About Bias
Just as d’ is the statistic for sensitivity,Beta () is the statistic for bias.
When… = 1, the criterion is neutral (no bias)
the criterion is low (liberal bias)
the criterion is high (conservative bias)
Part 3
Applications of Signal Detection Theory
S.D.T. Applications
S.D.T. can be used in perceptualdiscrimination experiments.
S.D.T. And DiscriminationPr
obab
ility
Perceived Speed
"No, 2nd Stimuluswas not faster"
"Yes,2nd stimuluswas faster"
The “slow”distribution
The “fast”distribution
S.D.T. Applications
S.D.T. can be used in non-perceptualresearch, including memory experiments.
S.D.T. And MemoryPr
obab
ility
Subjective Memory Strength
"No, I don'trecall it"
"Yes,I recall it"
The “new items”distribution
The “old items” distribution
Learning CheckI. Draw two bell-shaped curves (Gaussian distributions) with the same mean, but different standard deviations.
II. Draw two bell-shaped curves (Gaussian distributions) with the same standard deviations, but different means.
III. Draw one signal-detection-theory plot for a subject who hasPOOR discrimination, and another signal-detection-theory plot for a a different subject is has GOOD discrimination.
IV. Finally, on the SDT plots that you just completed, draw a liberalcriterion for one subject, and a conservative criterion for the other. Labeleach of these clearly.