1
Q
conceptual knowledge
A
- helps with recognition and generating inferences
- enables people to recognize objects and events and to make inferences about their properties
2
Q
concepts
A
- mental representation of an object, event, or abstract ideas
- e.g. how someone mentally represents a “cat” or “house”
3
Q
category
A
- examples of a concept that are grouped together
- e.g. category of “cats” includes tabbies, Siamese cats, Persian cats, leopards, etc
4
Q
categorization
A
- process of building and placing things in a category
- categorization not only helps understand what is happening in the environment, it also plays an essential role in enabling us to take action
5
Q
approaches to categorization
A
- definitional approach
- family resemblance
- prototype approach
- exemplar approach
6
Q
definitional approach
A
- categorization based on definition of the category
- each member of a category needs to meet the same/set criteria
- e.g. “a square is a plane figure having four equal sides, with all internal angles the same”
- the problem is that not all of the members of everyday categories have the same features
7
Q
familial resemblance
A
- categorization based on ways they resemble each other
- each feature of objects within a category do no need to match
- allows for some variation within a category
8
Q
prototype approach
A
- strategy of category selection based on similarity with a prototype
- an “average” representation of the category
- individuals generate their own prototype for a category but people often have similar prototypes
- variations within categories as representing differences in typicality
9
Q
prototype
A
a “typical” member of the category
10
Q
high typicality
A
a category member closely resembles the category prototype
11
Q
low typicality
A
the category member does not closely resemble a typical member of the category
12
Q
typicality effect
A
faster to verify prototypical/typical members as belonging to a category than non prototypical/less typical members
13
Q
sentence verification technique
A
- participant is asked to indicate whether a particular sentence is true or false
- determine how rapidly people could answer questions about na objects category
- used by Edward Smith at al. (1974)
14
Q
prototypical members and priming
A
- prototypical members of a category are more affected by a priming stimulus than are non prototypical members
- priming results in faster “same” judgments for the prototypical objects
15
Q
exemplar approach
A
- strategy of category selection based on the greatest similarity between an item in category and the novel item
- members of a category are judged against examples
- examples of members of the category that the person has encountered in the past
- selecting the category with an exemplar that is the closest match the the item that is to be categorized
- can deal with more variable categories
16
Q
exemplars
A
- actual members of the category that a person has encountered in the past
- e.g. if a person has encountered sparrows, robins, and blue jays in the past, each of these would be an exemplar for the category “birds.”
17
Q
hierarchal organization
A
- organization of categories in which larger, more general categories are divided into smaller, more specific categories
- these smaller categories can, in turn, be divided into even more specific categories to create a number of levels
18
Q
categories of Roschs hierarchal organization
A
- superordinate/global category
- basic-level category
- subordinate category
19
Q
superordinate global category
A
- top of the hierarchy
- contain many category members
- broad and varied, meaning one can’t generate a prototype at the superordinate level
- most general category level
- lack similarity
- e.g. fridge and a desk = both furniture but not similar
20
Q
basic-level category
A
- in the middle of the hierarchy
- often the first words learned and the type of words used daily belong at the basic-level category
- categories are the most differentiated at this level
- items within the basic-level category are similar (guitar and harp)
- items in different basic-level categories are dissimilar (guitar vs. apple)
- categorization is fastest at this level
21
Q
subordinate category
A
- bottom of the hierarchy
- fewest amount of category members/items
- most specific category level
- e.g. rocking chair, bean bag chair, dining chair → there’s only so many type of rocking chairs or dining chairs
22
Q
exceptions to Roschs hierarchal organization/categorization
A
- exceptions are the experts in a field
- e.g. if there’s a birdwatcher thy would be able to categories items at the subordinate level very quickly, like categorizing a type of sparrow
23
Q
semantic network approach
A
an approach to understanding how concepts are organized in the mind that proposes that concepts are arranged in networks
24
Q
hierarchal model
A
as applied to knowledge representation, a model that consists of levels arranged so that more specific concepts
25
collins and quillians semantic network model (1969)
- semantic network model is a type of hierarchical model that explains organization of semantic knowledge in LTM via a diagram
- concepts represented as nodes and arranged hierarchically
- concepts that are semantically associated are connected through links
- movement through the network takes time
- retrieval of concepts involves spreading activation
- the model indicates how concepts and their properties are associated in the mind, and to make predictions about how we retrieve properties associated with a concept
26
cognitive economy
- feature of some semantic network models in which properties of a category that are shared by many members of a category are stored at a higher-level node in the network
- e.g. the property “can fly” would be stored at the node for “bird” rather than at the node for “canary”
- makes the network more efficient, it does create a problem because not all birds fly
- quillian added exceptions at lower nodes to solve this problem
27
semantic facilitation
- semantic facilitation occurs when the semantic path was just used
- if the path is used before the activation dissipates then our travel down that path is facilitated
- e.g. if you need to verify a canary is a bird you activated that pathway, but if you have to verify that a canary is a bird a second time, before the activation of that path has completely dissipated you can travel it quicker
28
characteristics of the semantic network models
- direction of movement is bottom to the top
- semantic facilitation occurs when the semantic path was just used
- accounts for the category-size effect
29
category size effect
- faster to classify items that are part of a small category rather than a large category
- e.g. bottom of the hierarchy
30
spreading activation
- activity that spreads out along any link in a semantic network that is connected to an activated node
- spreading activation can influence priming
31
lexical decision task
a procedure in which a person is asked to decide as quickly as possible whether a particular stimulus is a word or a nonword
32
limitations of the semantic network
1. can't explain the typicality effect
2. classification speed does not always depends on level changes/distance traveled in the network
33
the semantic network can't explain the typicality effect example
- verify “a penguin is a bird” → slow RT
- penguins are atypical members because they don't fly, in comparison to canaries which are typical
- verify “a canary is a bird” → faster RT
34
classification speed is not always dependent on level changes/distance traveled in the semantic network example
- verify “a Chimpanzee is a primate” → 1 level change → slow RT
- verify “a chimpanzee is an animal” → 2 level changes → faster RT
- however research has shown that verifying chimpanzees as an animal is much quicker than verifying it as a primate
35
connections model
explains how knowledge is represented in the mind and can explain findings such as how concepts are learned and how damage to the brain affects people's knowledge about concepts
36
connectionism
- a network model of mental operation that proposes that concepts are represented in networks that are modeled after neural networks
- an approach to creating computer models for representing cognitive processes
- aka parallel distributed processing models
- concepts are represented as units
37
connection weight
- determines the degree to which signals sent from one unit either increase or decrease the activity of the next unit
- connection weight of each unit determines activation or inhibition of a signal
38
3 types of connection weights
1. high connection weights
2. low connection weights
3. negative connection weights
39
high connection weights
result in a strong tendency to excite the next unit
40
lower connection weights
cause less excitation
41
negative connection weights
can decrease excitation or inhibit activation of the receiving unit
42
activation units in a network depend on: (2)
1. the signal that originates in the input units
2. the connection weights throughout the network
43
input units
units activated by stimuli from the environment
44
hidden units
- located between input units and output units
- receive signals from input units and send them to output units
45
output units
contain the final output of the network
46
error signal
during learning in a connectionist network, the difference between the output signal generated by a particular stimulus and the output that actually represents that stimulus
47
back propagation
- an error signal is transmitted backward through the network
- this provides the information needed to adjust the weights in the network to achieve the correct output signal for a stimulus
48
graceful degradation
disruption of performance due to damage to a system that occurs only gradually
49
4 representations of concepts in the brain
1. sensory-functional hypothesis
2. multiple-factor approach
3. semantic category approach
4. embodied approach
50
sensory-functional hypothesis
we identify living things based on sensory features and nonliving things based on their function
51
multiple-factor approach
- identify living and nonliving things based on sensory features, function, motion, color
- how concepts are divided up within a category
52
semantic category approach
specific neural circuits associated with specific categories
53
embodied approach
reactivation of sensory and motor processes when interacting with objects
54
semantic dementia
- condition in which there is a general loss of knowledge for all concepts
- patients with semantic dementia tend to be equally deficient in identifying living things and artifacts
- damage to the anterior temporal lobe (ATL) has been connected with semantic deficits in dementia patients and with the savant syndrome
55
hub and spoke model of semantic knowledge
- a model of semantic knowledge that proposes that areas of the brain that are associated with different functions are connected to the anterior temporal lobe, which integrates information from these areas
- functions indicated include: valence, speech, auditory, praxis, functionality and visual
56
transcranial magnetic stimulation (TMS)
a procedure in which magnetic pulses are applied to the skull in order to temporarily disrupt the functioning of part of the brain
Cognitive Psychology
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