Schiffman Chapter 2

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Schiffman Chapter 2
2
Thresholds

• Absolute threshold minimum stimulus that can be
  detected
• Detection varies over time threshold is level
  detected 50 of time

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Method of Limits

• Start low go higher until S detects start high
  and go lower until S no longer detects
• Bias problemsome Ss want to be very sure dont
  give false positives others more concerned about
  false negatives
• If constant rate of change, Ss may anticipate too
  much

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Modified Method of Limits

• Staircase methodstart low, go up until detect,
  then go lower from there until dont detect, then
  go back up, etc.

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Method of Constant Stimuli

• Random order of stimulus intensities
• Give signal to respond (in different modality)
  yes or no whether perceive stimulus
• Plot detections for each intensity level

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Method of Adjustment

• Subject controls stimulus intensity
• Similar to method of limits, but with subject
  turning the knob
• Least accurate method

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Subliminal Perception

• Tachistoscope
• Stimulus can be too weak or too brief to be
  perceived subliminal
• Can stimulus still affect subject??

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Evidence on Subliminal Perception

• Priming studies can prime and emotions,
  which can affect judgments of neutral stimuli
  (e.g., faces)
• Priming studies can prime semantically with
  subliminal cues
• Neurological awareness in different brain area
  than direct perception
• But no evidence can control people

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Difference Threshold

• JNDjust noticeable differencesmallest change
  that can be detected
• Webers fraction change in intensity/intensity
  K
• Ex. need to add more weight to notice change in
  a heavy weight (compared to light initial weight)
• 2 point touch threshold distance apart required
  to perceive as 2 stimuli

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Fechners Law

• Relates magnitude of sensation to magnitude of
  stimulus
• Based on JND (JND as a standard unit)
• Graph bottom page 39 shows relation between
  stimulus and perception

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Stevens Power Law

• Disagreed with FechnerStevens did NOT think
  stimulus sensory magnitude were
  logarithmically related
• Better captured as a power function
  (exponential sensory magnitude physical
  intensity to a power
• Better about Stevens? Shape of curve depends on
  modality fits data better

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Examples of Power Functions

• Brightnessexponent is such that function is
  negatively accelerated increasing function

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Example of Power Function

• Electric shock function is positively
  accelerated increasing function