lectrue 5

Question 1

obj recnition

Question 2

agnosia

Answer 2

difficulty percieving obj features/drawing but can see simple features and meaning

can assog meaning to names

Question 3

associative agnosia

Answer 3

can percieve simple features but cant assign meaning

describe apple but cant say this is an apple

Question 4

recog obj
top down aka comcept/goal driven

Answer 4

relying on previous knowledge to id a stimuli

Question 5

bottom up aka

Answer 5

recognisixing obj base on pattern
data driven/stimulus driven

Question 6

recognition is linked to recognizing individual oarts

Answer 6

features are building blocks
proved through singe cell recording

Question 6

maks role are to

Answer 6

stop a stimulus from being pricessed completly

Question 7

words that are mroe common are mroe recognized

Answer 7

frequency effect

Question 8

in rep primining uncommon words rpeform

Answer 8

poorly

Question 8

first exposeure prin=mes for subsequent exposure

Answer 8

repititon priming

Question 9

in rep priming, high requency words preform

Answer 9

not that much effect bc frequency priming takes over

Question 10

word syperiority effecr

Answer 10

easier to recognize letters in words versus bythemselves

Question 10

well formingness

Answer 10

easier it represents the languange, the mroe likely to recognize the word

Question 11

feature net

Question 12

fearure detecror–letterdect=== triggers higher level responce— word dector

Question 13

frequent firit=ng results in

Answer 13

higher activation

Question 14

why does reptition priming happen?

Answer 14

because recent firing results in a hiher activation

Question 15

network includes a layer of
and do not need a higher level of input

Answer 15

bigram dectors

Question 16

over recognization cmes from

Question 17

feature net recovering from confusion

Answer 17

send feak activation to the bigram dectors

Question 18

feature nrets contain

Answer 18

distrubuted knowledge

Question 19

the mechien model emphasizes the role of

Answer 19

inhibitor measures

Question 20

rbc model applies to recognition of

Answer 20

3d objects

Question 21

what are gions

Answer 21

shapes for all 3d forms

Question 22

this is the feature net for 3s obj, explain their fx feature dectors geon dectors geon asseblies obj model

Answer 22

feature dectors: curves edges geon dectors: basic 3d shape dector geon asseblies: relationship between geons like top vs side obj model: complete picture

Question 23

mukltiple vies model, rnb

Answer 23

mental rotation is required, recognition is viewing angle is dependant

Question 24

hiarchy of rmv movel vs others, what is the difference? whole obj corners/notches lines/orientations

Answer 24

this rebrens a particualr viewpoint and obj specific vs a part of the obj,

Question 25

prosopagnosia

Answer 25

face blindness, knoes i is a face doesnt know whose face it is

Question 26

it is the relationships but not the features alone that guide facialr ecognition

Answer 26

composite effect

Question 27

activation in the back of the brain indicates