concepts and general knowledge

Question 1

define concept

Answer 1

mental representation used for a variety of cognitive functions

Question 2

how to study concepts

Answer 2

categorization

categorization is the process by which things are placed into groups called categories

Question 3

why are categories useful

Answer 3

help to understand individual cases not previously encountered
pointers to knowledge
provide wealth of general info about an item
-allows us to indentify the special characteristics of a particular item

Question 4

defining categories according to philosopher ludwig wittdenstein

Answer 4

simple concepts have no definition

eg games

Question 5

defintional approach to categorization

Answer 5

determine category membershup based on whether the object meets the definition of the category
doesnt work
not all members of everyday categories have the same defining features

Question 6

the moe characterstic features an object has,….

Answer 6

the more likely we are to believe it is part of the category

Question 7

family resemblance

Answer 7

category members may not be defined, but rather resemble one another
example category = games

Question 8

defintional models work?

instead

Answer 8

nope not well
prototype approach
exemplar approach

Question 9

prototype approach

Answer 9

prototype = typical
an abstract resemblance of the typical member of the cateogry
characteristic features that describe what members of that concept are like
an average of category members in the past
contains the most salient features
true of most instances of the category
differs individual to individual
graded membership = some members are closer to the prototype than others
fuzzy boundaries = no clear dividing line for membership
certain members are considered better than other (best red)

Question 10

high vs low prototypicality

Answer 10

high = category member closely resembles category phenotypes = a typical member
lo = category member does not closely resemble category prototype = unusual member

Question 11

typicality effect

Answer 11

prototypical objects are processed preferentially

high = judged more rapidly

Question 12

naming effect

Answer 12

prototypical objects are named first

depends on culure!`

Question 13

priming effect

Answer 13

prototypical category members are more affected by a priming stimulus
eg hearing the word green primes a highly prototypical green more than a less typical green

Question 14

prototypicality and attractiveness

Answer 14

affects judgements = most typical more attractive

Question 15

explain the exemplar approach

Answer 15

concept is represented by multiple exemplars (rather than a single prototype)
exemplars are actual category members (not abstract averages)
to categorize, compare the new item to each of the individually stored exemplars (one by one)
more similar to a specific exemplar is to a known category and the more instances of that category we have, the faster it will be categorized
explains typicality effect, easily takes into account how atypical cases and variable categories

Question 16

explain how both exemplar and prototype explains ….
typicality
graded memberships
illustration

Answer 16

typicality - average of a category vs encountered more often
graded membership - less similar to average vs how often it is encountered
illustration - ideal to less ideal member vs often to not as often encountered

Question 17

every concept is…

Answer 17

a mix of exemplar and prototype

• early learning involves exemplars
• experience involves averaging exemplars to get prototypes
• with more experienec, we can use both

Question 18

flexibility of exemplars vs prototypes

Answer 18

prototypes are economical but less flexible

exemplars are flexible but less economical

Question 19

so do we use exemplars or prototypes

Answer 19

probably both depending on the category
exemplars = best for small categories, also highly variable ones
prototypes = best for large fairly homogenous categories, highly bariable categories (like games) create strange, unrepresentative prototypes

Question 20

difficulties with categorizing via resemblance (typicality)

Answer 20

prototype and exemplar appraoch are based on typicality of membership - but cannot explain everything
so as number gets bigger we rate numbers as less typically odd or even
atypical features do no exclude category members (we still call red painted stripy squashed sweet lemon a lemon)
all the typical features but not category members (so perfect counterfeit bill = still not a bill)

Question 21

hierarchical organization of categories

Answer 21

just as certiain category members seem to be priviledged, so are certain types of category
global (superordinate) level = very general
basic level = somewhat specific category
specific (subordinate) level - very specific category
evidence = basic level is psychologically priviledged

Question 22

why do we use the basic level of categorization most

Answer 22

is the best / econonmical middle ground

Question 23

evidence to show basic level is “special”

Answer 23

people almost exclusively use basic-level names in free-naming tasks
quicker to identify basic-level category member as a category member
children learn basic names first ie doggie
basic level is much more common in adult discpurse than names for superordinate categories
different cultures tend to use the same basic-level categories at least for living things

Question 24

to understand how people categorize objects we must consider…

Answer 24

properties of objects

learning and experience of perceivers

Question 25

knowledge network

Answer 25

model of the representation of knowledge
suggests knowledge is represented via a vast network of connection and associations between all of the information you know
-early models = higherarchical structure (collins and quillian)

Question 26

sentence verification task

Answer 26

participants must quikcly decide whether sentences like robins are … birds, animals, have hearts etc are true
requires links along network tree
reaction time goes up for longer associative paths

Question 27

spreading activation in semantic networks

Answer 27

activation is the arousal level of a node
when a node is activated, activity spreads out along all connected lnks
concepts that receive activation are primed and more easily accessed from memory

Question 28

criticism of knowledge networks

Answer 28

cannot explain typicality effects
cognitive economy?
some sentence-verification results are problematic for the model (eg mammal vs animal)

Question 29

semantic networks modification by collins and loftus

Answer 29

shorter links to connect closely related concepts
longer links for less closely related concepts
no hierarchical structure based on individual persons experience

Question 30

assessment of semantic networks modification

Answer 30

is predictive and explanatory of some results but not all
generated multiple experiments
lack of falisifiability
-no rules for determining link length or how long activation will spread
-therefore there is no way to prove it wrong
-circular reasoning

Question 31

propositional knowledge networks

Answer 31

localist representations - each node is equivalent to one concept

Question 32

connectionist knowledge networks

Answer 32

distributed processing - information involves a pattern of activation
parallel processing of information occurs at the same time
-a netowrk of nodes and links but operates very differently from semantic networks
= neuron like units
knowledge represented in the distributed activity of many units
weights determines at each connection how strongly an incoming signal will activate the next unit

Question 33

3 neuron like units explained in connectionist approach

Answer 33

input units - activated by stimulation from environmant
hidden units - receive input from input units
output units - receive inputs from hidden units

Question 34

how learning occurs in the connectionist approach

Answer 34

network responds to stimulus
provided with correct response
modifies responding (based on correct response) to minimize error signal
learning can be generalized

Question 35

error signal in the connectionist approach

Answer 35

difference between actual activity of each output unit and the correct activity
difference between answer given by neural network and correct answer
error signals cause a node to decrease its connections to input nodes that led to the error = back propogation

Question 36

back propogation

Answer 36

error signal transmitted back through the circuit
indicates how weights should be changed to allow the output signal to match the correct signal
the process repeats until the error signal is zero

Question 37

graceful degradation

Answer 37

disruption of performance occurs gradually as part of the system are damaged

Question 38

case studies KC and EW

Answer 38

trouble with categories that represent living things but no trouble with non living things
different areas of the brain may be specialized to process information about different categories
other specific deficits eg recognizing the categories of persons, animals and tools

Question 39

how are categories represented in the brain

Answer 39

by distributed activity, but in similar areas across all people
more similar patterns of brain activity for categories with similar features
category specific neurons have been found in humans and aninals (stimuli made up of part dog and cat showed specific neurons fire for dog and specific for cat)

Question 40

are infants capable of categorization

Answer 40

familiarization/ novelty preference procedure
2 months can categorize global
3-4 months can categorise basic
6-7 months can categorize specific
categorization becomes fine-tuned with age