Appendix: Noise and Signal Detection Theory Flashcards
Noise
random variation in number of action potentials produced by neurons in response to fixed sensory stimulus
What can psychophysics be used for?
- Sensory system neurophysiology/ neuropsychology
- Sensory limits of vision, hearing, touch…
- Interspecies comparison
- Inferring neuronal mechanisms - Experimental psychology
- Visuomotor interactions
- Perception of speed, motion
- Attention - Quantitative measurement of perceptual states
- Diagnostic tool
- Assessment tool
Decision Criterion
threshold used when deciding whether stimulus was presented or not
Psychometric Function
plot of proportion of stimuli detected or discriminated vs stimulus intensity
- Ideal psychometric function: step function (fixed threshold)
- Real psychometric function: S- shaped (sigmoid or logistic) function
Method of Limits
either ascending or descending direction
- doesn’t change direction when stimulus is detected
- continue in many trials but vary the starting point
- similar to method of adjustment
Effect of noise on psychometric function
Detection or discrimination of stimulus is always subject to noise:
- Neural
- Stimulus (physical)
- Participant Distraction:
- Attention
- (Response)
Signal Detection Theory
framework for measuring how many people make decisions in presence of noisy perceptual evidence
- disregards decision- making style
- how stimuli are detected/ discriminated against background noise
- how to make decisions in the presence of uncertainty
- how to make optimal decisions from ambiguous data
- how to make good decisions from bad information
- allows measurement of sensitivity
SDT Outcome
SIGNAL. DECISION. CONSEQUENCE
yes. yes hit
yes no. miss
no. yes. false alarm
no. no. correct rejection
Receiver Operating Characteristics
quality of participants performance (hit/ false alarm)
Decision- Making Bias
participant’s tendency to be liberal or conservative when deciding if stimulus is present
Low Criterion
- decision for any kind of noise
- alert for every blob: make sure you never miss- but many false alarms
High Criterion
- make very strict decision for what to respond to
- only alert for really big blobs: no false alarms- but many misses
Utility
satisfaction from results of decision
Discriminatory d’
distance between means of noise curve and stimulus+noise curve
Difference between the hit rate and false alarm rate
High d’- very little overlap between options
Low d’- lots of overlap
- low sensitivity
- more misses and false alarms