Perceptual Responses to Weak Stimuli by 53401g

VIEWS: 7 PAGES: 45

									Perceptual Responses to Weak
           Stimuli
       Detection Thresholds
      Signal Detection Theory



            Responses to Weak Stimuli   1
       Objectives: Be able to
• Discuss the threshold, its shape and
  assumptions.
• Discuss assumptions, what’s
  measured, and errors for thresholds.
• Discuss assumptions, what’s
  measured, and errors for signal
  detection measurement.
• Discuss how criterion affects
  sensitivity and response bias
• Describe practical examples of the use
  of thresholds and signal detection.      2
               Responses to Weak Stimuli
        Detection Threshold
• If the stimulus is too weak, it is not
  detected
• Stimulus grows stronger, still not
  detected
• When stimulus reaches threshold
  strength, it is detected
• At all levels above threshold strength it
  is detected

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Threshold – Single Measurement




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Problems with Detection Thresholds

• Measured threshold can vary from trial
  to trial
• Variation in threshold fits a normal
  curve
• Measured threshold functions look like
  an S
• Threshold function is a cumulated
  normal curve
• Not a squared off function
               Responses to Weak Stimuli   6
Multiple Measurements of a Threshold




             Responses to Weak Stimuli   7
        Discussion Question 1

• If the threshold concept is correct, why
  does the “percent of seeing” curve in
  threshold experiments produce an S-
  shaped curve rather than a squared off,
  “threshold shape” function? Explain.




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     Threshold Assumptions
• A. Sensitivity Varies - thus threshold
  varies
• B. No Response Bias - else threshold
  may be lower or higher than measured




               Responses to Weak Stimuli   9
 What’s Measured with Thresholds?


• A stimulus intensity: The stimulus
  intensity needed for the stimulus to be
  detected half the time.




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    Three Kinds of Threshold
           Measures

• Method of Limits
• Staircase Method
• Method of Constant Stimuli




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          Method of Limits
• Present stimuli in an ascending order
  until observer detects it.
• Present stimuli in a descending order
  until observer fails to detect it.




               Responses to Weak Stimuli   12
 Problems with Method of Limits
• The observer knows whether the next
  stimulus will be larger or smaller than
  the previous one.
• Response Bias Errors: Anticipation
  and Habituation.




                Responses to Weak Stimuli   13
  Anticipation and Habituation
• Anticipation - response changes before
  percept does – jumps the gun
• Habituation - percept changes,
  response does not – fail to respond to
  change
• These errors eliminated in Method of
  constant stimuli
• Stimulus order randomized

               Responses to Weak Stimuli   14
           Staircase Method
• Begins like method of limits: ascending order
  until detected
• From there, tracks the threshold - Quick
  Threshold
• Stimulus detected, next stimulus weaker
• Stimulus not detected, next stimulus
  Stronger
• Are anticipation and habituation possible?


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     Method of Constant Stimuli


• Stimulus order randomized - no
  anticipation or habituation possible
• Other kinds of response bias possible
• Takes many trials - slow, but accurate
  measure



                Responses to Weak Stimuli   17
      Discussion Question 2
• Compare and contrast the detection
  threshold measures: Method of Limits
  (MOL), Method of Constant Stimuli
  (MCS), and Staircase Method (Stair).
  What are the assumptions, what is
  measured, and what kinds of errors of
  measurement are made using each
  method?
• What does compare and contrast
  mean?

               Responses to Weak Stimuli   18
      Discussion Question 3
• Give an example of a practical
  application in which threshold
  measures would be useful. Be sure
  to describe what is measured, give
  an example of a practical
  application, and show how the
  application fits what is measured.


              Responses to Weak Stimuli   19
                       Q3
• What is measured?
  – The stimulus intensity necessary for the
    stimulus to be detected half the time.
  Example.
  Fit.




                 Responses to Weak Stimuli     20
      These Two Thresholds Differ:
Is Laurie more sensitive or more willing to say yes?




                    Responses to Weak Stimuli    21
• Staircase thresholds can be measured
  quickly, but there can be problems.
• Because differences in thresholds
  could mean either differences in
  sensitivity or differences in response or
  decision making processes, we can’t
  be sure what differences in thresholds
  mean.
• When motivation cannot be controlled,
  we need another method.

                Responses to Weak Stimuli   22
 Signal Detection Theory (SDT)
• Assumes that variability in thresholds
  is due to variable sensory noise, not
  variable sensitivity.
• Assumes that response bias cannot be
  eliminated, as required by threshold
  measures.
• SDT attempts to measure response
  bias and sensitivity

               Responses to Weak Stimuli   23
       Sources of Sensation

• Sensory Noise - normally distributed.
• Sensory Noise Plus Stimulus - Noise
  plus a fixed amount of sensation added
  by the stimulus.
• Unlike Thresholds, where the stimulus
  is always presented, the observer does
  not know whether a stimulus was
  presented.


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              Sensitivity
• Sensitivity is the distance between the
  mean of the noise only distribution and
  the mean of the noise plus stimulus
  distribution in standard deviation units.
• Sensitivity is assumed to be fixed,
  unchanging.
• Sensitivity = d’ or d prime.


                Responses to Weak Stimuli   28
           Response Bias
• Response bias (for thresholds also) is
  the willingness to report the presence
  or absence of the stimulus, unrelated to
  sensation.
• Can be influenced by motivational
  aspects of the situation as well as the
  probabilities of a stimulus being
  present.

                Responses to Weak Stimuli   29
            Response Bias
• Response bias sets the criterion to
  decide whether there was a stimulus
• If the sensation level exceeds her
  criterion, the observer says, “I saw it.”
• If the sensation level does not exceed
  her criterion, the observer says, “I did
  not see it.”


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Assumptions of Signal Detection
• Sensitivity is fixed - thus it can be
  measured
• There is internal sensory noise that
  mimics the effect of the stimulus
• This noise causes variation in the level
  of sensation
• There is response bias and it can be
  measured

                Responses to Weak Stimuli    35
        What is Measured by SDT

•   Sensitivity
•   Response Bias
•   These are observer qualities
•   Thresholds measure stimulus intensity
    levels




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     Discussion Question 4
• Compare and contrast the constant
  stimuli method (MCS) of detection
  threshold measurement with signal
  detection (SDT) measurement. What
  are the assumptions, what is
  measured, and what kinds of errors
  of measurement are made using
  each method?


              Responses to Weak Stimuli   40
      Discussion Question 5

• Discuss the effect of changing one’s
  criterion from lax to strict on both
  sensitivity and response bias. Explain
  how those results occur. Drawing a
  diagram may be helpful.




               Responses to Weak Stimuli   41
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      Discussion Question 6
• Give an example of a practical
  application in which signal detection
  measures would be useful. Be sure to
  describe what is measured, give an
  example of a practical application, and
  show how the application fits what is
  measured.



                Responses to Weak Stimuli   43
                       Q6
• What is measured?
  – Sensitivity, d’
  – Response bias, β
• Example.
• Fit.




                Responses to Weak Stimuli   44
       Objectives: Be able to
• Discuss the threshold, its shape and
  assumptions.
• Discuss assumptions, what’s
  measured, and errors for thresholds.
• Discuss assumptions, what’s
  measured, and errors for signal
  detection measurement.
• Discuss how criterion affects
  sensitivity and response bias
• Describe practical examples of the use
  of thresholds and signal detection.       45
                Responses to Weak Stimuli

								
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