Chapter 8

Question 1

in a probabilistic framework, what is sensory information represented by

Answer 1

evidence (I)

Question 2

in a probabilistic framework, what are physical states represented by

Answer 2

possible interpretations (S)

Question 3

what is the question asked in a probabilistic framework,

Answer 3

what is the most likely interpretation given the available evidence P(S|I)

Question 4

what three aspects does bayes include

Answer 4

posterior, likelihood, prior

Question 5

what is the posterior in bayes

Answer 5

used to make perceptual judgment P(S|I)

Question 6

what is the likelihood in bayes

Answer 6

sensory information P(I|S)

Question 7

what is the prior in bayes

Answer 7

knowledge, experience P(S)

Question 8

what is the decision rule in byaes

Answer 8

maximum a posteriori (MAP) or the peak of the posterior

Question 9

prior is responsible for what

Answer 9

many illlusions like light from above

Question 10

how does the brain combine different sources of information

Answer 10

cue integration - rules of probability

Question 11

what is it called when there are multiple cues

Answer 11

cue combination

Question 12

if probabilities are independent/uncorrelated what does bayes theory look like

Answer 12

P(SI1, I2, I3) ~ P(I1,I2,I3|S)P(S)

Question 13

if posterior is product of all likelihoods and prios, gives brain most precise estimate

Answer 13

P(S|I1, I2,I3)~ P(I1|S)P(I2|S)P(I3|S)P(S)

Question 14

what are the three assumptions of the maximum likelihood estimates

Answer 14

gaussian noise (normal distributed), idependnece, uniform prior - bayes model of cue combo
P(S|I1, I2) ~ P(I1|S)P(I2|S)

Question 15

what is the maximum likelihood esitmation

Answer 15

optimal estimate weighted linear combo of contributing cues

Question 16

what are the maximum likelihood estimate weights determined by

Answer 16

relative cue reliabilities

Question 17

haptic vr equipemtn uses what device

Answer 17

phantom force feedback device