Problem 2

Question 1

Signal detection theory

Answer 1

Is a method that measures the ability to differentiate between actual information and random patterns (noise) which distracts from the information

–> a number of factors affect how a detecting system will detect a signal

Question 2

Psychophysical methods

Answer 2

Are used to determine an observers absolute threshold

BUT: however the absolute threshold may be specified differently among participants

Question 3

SDT provides a precise language and graphic notation for analyzing decision making in the presence of uncertainty.

Elaborate

Answer 3

A 2x2 Matrix is provided, generated by 4 events that might happen when the participant responds

1. Hit
2. Miss
   - -> not hitting
3. False alarm
   - -> identifying when not presented
4. Correct rejection

Question 4

Signal

Answer 4

Is the stimulus presented to a subject

Question 5

Noise

Answer 5

Refers to all the other stimuli in the environment why may be mistaken for the signal

Question 6

Why is noise always involved in experiments ?

Answer 6

Because it is always present

–> thus they either present S+N or just N

Question 7

Which noise factors may affect a subjects performance ?

Answer 7

External or internal noise, defined by noisy neural responses

Question 8

How do neurons generate a specific response in the participants?

Answer 8

External stimuli generate neural activity in the brain

–> there will be a higher rate of neural firing when a signal is present than when its absent

THUS: when a critical threshold is exceeded, the operator will decide yes

Question 9

How do errors in responding occur on a neuronal level?

Answer 9

The firing rate of neurons varies due to

1. random variations in the environment
2. the operators brain level of neural firing

THUS: the smaller the difference in intensity between signals and noise, the greater these error probabilities become

Question 10

Probability distribution

Answer 10

Tell us what the chances are that a given single occurs due to

1. Noise (N)
2. Signal and noise ( S+N)

–> an overlab in these distributions means it is difficult to know

Question 11

There are 2 main components to the decision-making process of participants.

Name them.

Answer 11

1. Subjects sensitivity to the signal

2. Subjects response criterion

Question 12

Response criterion

Answer 12

Is determined by the rule or strategy that a subject uses

ex.: whether they focus on getting more hits or avoiding false alarms

Question 13

Liberal responder

to liberal criterion

Answer 13

1. High amount of hits
2. High amount of false alarms

–> probability of both hits and false alarms is high

Question 14

Neutral responder

to neutral criterion

Answer 14

1. High amount of hits
2. Average amount of false alarms

–> will rarely indicate “yes” in response to noise but very likely to signal

Question 15

Conservative responder

to conservative criterion

Answer 15

1. Average amount of hits
2. Low amount of false alarms

–> never indicate “yes” to noise and rarely “yes” to signal

Question 16

Beta

Answer 16

Refers to the ratio of activity produced by signal and noise at Xc (threshold)

–> it defines the response bias/response criterion

Question 17

Sometimes circumstances dictate which strategy is best to use in responding.

Why ?

Answer 17

Your behavior may be determined by placing a decision criterion

ex.: when examining an ill patient it is better to be biased towards “yes” than when examining a healthy patient

Question 18

How do beta and Xc interact ?

Answer 18

If Xc is shifted to the right, beta value will be higher than one

–> thus fewer “yes responses, hits and false alarms and vice versa

Question 19

Optimal performance

Answer 19

Occurs when Xc is placed at the intersection of 2 curves

–> when beta=1

Question 20

Payoffs

Answer 20

May cause the participants to change their strategy/response criterion

–> does not change the sensitivity of a subject

Question 21

A subjects Sensitivity to a stimulus is determined by … ?

Answer 21

… the distance between the peaks of noise (N) and signal + noise (S+N) distributions along the X-axis

–> this distance affects the shape of the ROC curve

Question 22

Discriminatory index (d’)

Answer 22

Refers to the distance between the peaks of Noise and Singal + Noise

–> Characterizes the detectability of the signal if we make the IID assumption

–> doesn’t depend on the subjects response criterion but is a true measure of internal response

AND: d means distance or separation/spread

Question 23

IID Assumption

Answer 23

Assumes that noise follows a normal distribution with fixed variance, independent of signal strength

Question 24

How can d prime be determined?

Answer 24

By comparing the experimentally determined ROC curve to standard ROC curves

or

from calculating the proportions of hits and false alarms in the experiment

Question 25

ROC curve

Answer 25

1. Is used to predict how each criterion will affect the subject’s hits and false alarms.
2. Captures the various alternatives that are available to the subject as they move their criterion to higher + lower levels

–> false alarm rate= X; hit rate = Y

Question 26

Optimal beta

Answer 26

Depends on the subject’s decision criterion Xc which can be influenced by payoffs

–> “optimal” = maximizing gains or minimizing losses

Question 27

Signal strength

Answer 27

Affects the probability density functions

–> when the signal is stronger, there is less overlap between the two probability density curves. Then, the subject’s choices are not so difficult as before.