Sensation

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Sensation

• Perception gathering information from the
  environment
• 2 stages
• Sensation simple sensory experiences and
  translating physical energy from the environment
  into neural codes
• Perception organizing, identifying, and
  interpreting sensations to create mental
  representations of objects and events

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Top-down and Bottom-up Processes in Perception

• Bottom-up
• data driven
• stimulus driven
• Example different wavelengths of light produce
  different color sensations
• Top-down
• conceptually driven
• context driven
• Example reading an exit sign more quickly
  because you know what it is likely to be

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Topics in Sensation

• Thresholds
• Signal Detection Theory

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Thresholds

• Absolute threshold the lowest intensity of a
  stimulus that can be detected
• Subliminal stimuli
• Eat Popcorn (McConnell et al 1958)
• Backward messages
• Self-help tapes (Greenwald et al 1991)
• Priming
• So do subliminal stimuli have real effects?

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Thresholds Theoretical and Actual Functions

• Theoretical Threshold Functions (Step Threshold)
• Actual Threshold Functions (Threshold is a
  continuous function)
• Operational Definition of the Absolute Threshold
• The stimulus intensity at which it is correctly
  identified 50 of the time
• Is there anything else besides stimulus intensity
  that must be considered?

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Signal Detection Theory

• 2 Components of detection judgments
• Discriminability
• How much sensory evidence is there that a signal
  is present?
• Controlled by stimulus
• Bottom-up
• Bias
• How much evidence does the perceiver require
  before saying yes?
• Controlled by a pay-off matrix (among other
  things)
• Top-down

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Discriminability and Bias

• Signal and Noise distributions
• X axis Magnitude of internal sensory process
  (amount of neural excitation)
• Y axis frequency (probability density function)
• Noise effects of noise alone
• Signal effects of signal plus noise
• Criterion
• How much neural excitation does the perceiver
  require before saying yes?
• Tutorial http//psych.hanover.edu/Krantz/STD/

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Signal Detection Measures of Discriminability and
Bias

• Discriminability
• d (d prime)
• distance between signal and noise distributions
• 0 no discriminability higher values more
• Assumes that the signal and noise distributions
  are normal
• Log(alpha)
• another measure of discriminability that does not
  assume normality
• 0 no discriminability 4.6 perfect performance

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Signal Detection Measures of Discriminability and
Bias

• Bias
• Beta
• 1 neutral (when the criterion is through the
  point where the signal and noise distributions
  cross)
• lt 1 liberal (yes) bias
• gt 1 conservative (no) bias
• C
• 0 neutral
• lt 0 liberal
• gt 0 conservative

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Evidence for Signal Detection Theory

• Swets, Tannar, Birdsall, 1961
• 4 choice detection task (tones A, B, C, D)
• After an incorrect answer, answered again
• If the participants had no information about
  which tone it was when they were wrong, should be
  at chance on subsequent guesses
• Results after a missed guess, they were above
  chance on the next guess
• Therefore, the threshold is a continuous function
  (as Signal Detection Theory predicts), not a step
  function.

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The Problem of Bias

• How can researchers avoid mistakenly attributing
  changes in response bias to perceptual effects
  (discrimination)?
• Use Signal Detection Theory measures of
  discriminability and bias to distinguish the two
• Induce a strong conservative bias
• Use a forced-choice task

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Importance of SDT

• Stimulus detection is a function of not only how
  strong the signal is, but also the criterion that
  the perceiver chooses
• Even basic sensory processes involve both
  bottom-up and top-down processes
• Perception depends on contributions from both the
  stimulus and the perceiver
• Sub-threshold stimuli can still provide
  information (and thus influence cognitive
  processes)