1
Q
Conceptual Knowledge
A
knowledge that enables us to recognise objects and events and to make inferences about their properties
2
Q
-Concept:
A
mental representation used for a variety of cognitive functions
categories of objects, events and abstract ideas
3
Q
-Categorization:
A
is the process by which things are placed into groups called categories
-categories are all possible examples of a particular concept
4
Q
category
A
includes all possible examples of a concept
5
Q
Why categories are useful?
A
- help to understand cases not previously encountered
- “Pointers to knowledge”
- categories provide a wealth of general information about an item
- allow us to identify the special characteristics of a particular item
6
Q
Definitional approach to categorization
A
we can decide whether something is a member of a category by determining whether a particular object meets the definition of the category
- Does not work well
- Not all members of everyday categories have the same defining features
7
Q
Family resemblance
A
refers to the idea that things in a particular category resemble one another in a number of ways
8
Q
prototype approach to categorization
A
membership to category is determined by comparing the object to a prototype that represents a category
- characteristic features that describe what members of that concept are like
- An average of category member encounters in the past
9
Q
Prototype
A
a “typical” member of the category
10
Q
Typicality
A
high typicality means that a category member closely resembles the prototype, low means opposite
11
Q
Determining Categories by Similarity
A
- compare object to a “standard”
- prototype approach: the standard is determined by averaging category members
- exemplar approach: the standard is created by considering a number of typical members of a category
12
Q
Exemplar approach
A
the standard is created by considering a number of typical members of a category
13
Q
COGLAB: Prototype
A
- What methods did we employ in this experiment?
- On each trial you were shown a dot pattern and were asked to classify it as belonging to Category A or Category B. You were asked to respond as quickly and as accurately as you could.
- In the training phase (60 trials if all are finished correctly), each dot pattern was a variation of one of two fixed prototype random dot patterns. The variations are made by randomly taking ten of the twenty-five dots in a prototype and moving them to a new position.
- In the test phase, a new set of dot patterns was presented. The dot patterns in the testing phase were of four types. One was the prototype that corresponds to the A category. Another was the prototype that corresponds to the B category. The other two patterns were new variations of these prototypes (one variation for each prototype).
- Average reaction times for previously unseen prototypes and previously unseen variations of the prototypes.
- The expected effect is that the RT for the prototypes is smaller
14
Q
Posner & Keele (1968)
A
- Stimulus: Dot patterns (3 different prototypes that were constructed by placing dots in nine randomly selected positions in a 30X30 matrix)
- Participants see 4 distortions of each prototype and changed until they could discriminate them
- Learn to categorize patterns with feedback
Results
• Prototypes are categorized as well as old distortions
• Both are categorized better than new distortions
• The new, far-removed distortions are least well categorized
-Prototypes are explicitly extracted from examples and serve as representation for category
15
Q
strong positive relationships exisits between
A
prototypicality and family resemblance
16
Q
-When items have a l arge amount of overlap with characteristics of other items in the category
A
the family resemblances of these items is high
17
Q
Low overlap =
A
low family resemblance
18
Q
To measure the family resemblance (Rosch & Mervis, 1975)
A
- List the characters of the following items
- Chair Sofa Mirror Telephone
-Results
- Chair Sofa share a lot of common characteristics
- Mirror Telephone share few common characteristics
- High family resemblance corresponding to high prototypicality (chair)
- Low family resemblance corresponding to low prototypicality (Telephone)
19
Q
Sentence verification technique
A
used to determine how rapidly people could answer questions about something’s category - “an apple is a fruit”
faster for words with high typicality
20
Q
typicality effect
A
ability to judge highly prototypical objects more rapidly
21
Q
high prototypical objects are judged
A
more rapidly
22
Q
-Rosch (1975b)
A
- Hearing “green” primes a highly prototypical “green”
- Prototypical objects are named first (Mervis et al., 1976)
- Please list the birds you know as many as possible
23
Q
Priming
A
occurs when a presentation of one stimulus facilitates the response to another stimulus that usually follows closely in time
24
Q
Naming
A
people are more likely to list some objects than others when asked to name objects in a category
25
exemplar approach to categorization
involves determining an object is similar to other objects, does not include a single "average" but involves many examples called exemplars
26
Exemplars
are actual members of that category that a person has encountered in the past (standard)
27
Exemplar is similar to prototype in that
representing a category is not defining it
28
Exemplar is different to prototype in that
representation is not abstract
-descriptions of specific examples
29
-the more similar a specific exemplar is to a known category member
the faster it will be categorized (family resemblance effect)
30
Exemplar approach can
- Explains typicality effect
- easily considers atypical cases
- Easily deals with variable categories
31
Posner and Keele (1968)
-In their experiments:
- They had participants learned distortions from four prototypes (a triangle, M, F, or a random pattern). With 1bit/dot distortion, 5 bits/dot distortion. Then tested with 7.7bits/dot distortion.
- During test, those who got training with 5 bits/dot distortion better than 1bit/dot distortion.
32
Prototypes or Exemplars?
- May use both:
- Early in learning. People may be poor at considering “exception” but later, exemplars for the exceptions would be added to the category (Minda and Smith, 2001)
- Exemplars may work best for small categories, e.g., US presidents
- Prototypes may work best for larger categories, e.g., birds
33
Hierarchical organization
organization, in which larger, more general categories are divided into smaller, more specific categories, creating a number of levels of categories
34
Global (superordinate)
vehicle for example - broadest terms
35
basic level
car or truck - mid-specific terms
36
specific level (subordinate)
ford, chevy - specific
37
“Privileged” Level of Categories
- concept has a hierarchical organization
- Furniture can be divided into “chair, table, etc.”
- chairs can contain kitchen chairs and dining room chairs
- this kind of organization, in which larger, more general categories are divided into smaller, more specific categories to create several levels of categories is called a hierarchical organisation
38
which level is "special"
none is specific and it depends on what the person focuses on and where their expertise lies
39
Evidence that Basic-Level is Special
- going above basic level results in a large loss of information
- going below basic levels results in little gain of information
Timeline
Description automatically generated
- People almost exclusively use basic-level names in free-naming tasks
- Quicker to identify basic-level category member as a member of a category
- Children learn basic-level concepts sooner than other levels
- Basic-level is much more common in adult discourse than names for superordinate categories
- Different cultures tend to use the same basic-level categories, at least for living things
40
A Hierarchal Organization
- more common features given by participants for basic level category
- quicker to identify basic level category member as a member of a category
- to fully understand how people categorize objects, one must consider:
- properties of objects
- learning and experience of perceivers
41
semantic network appraoch
proposes that concepts are arranged networks
42
-Collins and Quillan (1969)
- Node = category / concept
- concepts are linked by nodes
- model for node concepts and properties are associated in the mind
- it is a hierarchical model
43
cognitive economy
shared properties are only stored at higher-level nodes
-exceptions are stored at lower nodes
44
-Inheritance
-lower-level items share properties of higher-level items
45
Spreading activation
is actively that spreads out along any link that is connected to an activated node
- when a node is activated, activity spreads out along all connected links
- concepts that receive activation are primed and more easily accessed from memory
46
Lexical decision task
-participants read stimuli and are asked to say as quickly as possible whether the item is a word or not
reaction time was faster when the two words were associated
believed to have occurred because retrieving one word form memory triggered a spread of activation to other nearby locations of the network, meaning when the words were related, the response was faster because of more activation
47
Coglab: Lexical Decision Task
What do we predict participants will do?
Why?
- Response times to the second word should be faster when the second item is a word that is semantically associated to the first item than when it is unrelated.
- How robust is this effect?
Are there limits to this effect? The effect is very robust, but it may not appear for every person on every experiment.
48
Criticism for the Collins and Quillan Model
- could not expect the typicality effect
- the concept of cognitive economy was questioned because of evidence that people may store specific properties of concepts right at the node for that concept
49
Connectionalism
an approach to creating computer models for representing cognitive processes
these are also called parallel distributed processing (PDP)
50
Unit (connectionist network)
unit are inspired by the neurons found in the brain
51
Input units
units activated by stimuli from the environment
52
hidden units
receive from input and sent to output units
53
output units
where signals are sent
54
connection weight
determines how signals sent from one unit either increase of decrease the activity of the next unit
55
high connection weight results in
a strong tendency to excite the next unit
56
what does the activation of units depend on
the signal originates in the input units
the connection weights throughout the network
57
Myer and Schvaneveldt (1971)
- “yes” if both strings are words; “no” if not
- some pairs were closely associated
- reaction time was faster for those pairs
- spreading activation
58
The Connectionist Approach
- creating computer models for representing cognitive processes
- parallel distributed processing
- knowledge represented in the distributed activity of many units
- weights determine at each connection how strongly an incoming signal will activate the next unit
59
Connectionist Approach cont’d
-how learning occurs
- network responds to stimulus
- provided with correct responses
- modifies responding to match correct response
- can explain generalization of learning
60
-Back propagation
error signal transmitted back through the circuit
- Indicates how weights should be changed to allow the output signal to map the correct signal
- the process repeats until the error signal is zero
61
Graceful degradation
disruption of performance occurs gradually as parts of the system are damaged
- slow learning process that creates a network capable of handling a wide range of inputs
- Learning can be generalized
- partial loss of functioning but not detrimental to the system (graceful)
62
Categories in the Brain
- different areas of the brain may be specialized to process information about different categories
- double dissociation for categories “living things” and “nonliving things”
- category-specific memory impairment
63
Sensory-Functional (S-F) Hypothesis
- states that our ability differentiate living things and artifacts depends on a memory system that distinguishes sensory attributes and a system that distinguishes functions
- distinguishing living things depend on perceiving their sensory features. For example, distinguishing between a tiger and a leopard depends on perceiving stripes and spots
- Artifacts, in contrast, are more likely to be distinguished by their function. For example, a screwdriver, chisel, and hammer are all tools but are used for different purposes
64
category-specific memory impairment
an impairment in which they had also the ability to identify one type of object but retained the ability to identify other types
65
sensory (relevant information)
living things
66
Functional (relevant information)
artifacts (a hammer hits nails)
67
multiple factor approach
-looks at how concepts are divided up within a category rather than identifying specific brain areas of networks for different concepts
68
Crowding:
when different concepts within a category share many properties
-animals all share eyes, legs, and the ability to move
69
semantic category approach
proposes that there are specific neural circuits in the brain for some specific categories
focuses on areas of the brain that are specialises to respond to specific types of stimuli, emphasizes that the brain's response to items from a particular category is distributed over a number of different cortical areas
70
The embodied approach
states that our knowledge of concepts is based on reactivation of sensory and motor processes that occur when we interact with the object
71
-Mirror neurons:
neurons that fire when we do a task or when we observe another doing that same task
72
-Semantic somatotopy:
correspondence between words related to specific body parts and the location of brain activation
73
Hub and Spoke Model
areas of the brain that are associated with specific functions are connected to the ATL, which serves as a hub that integrates the information from these areas
Cognitive Psycho - 258
flashcards
Decks in class (13)
# Cards
-
Chapter 6 - Long term memory (Midterm 2)55
-
Chapter 7 - ENCODING, Retrieval, and Consolidation55
-
Chapter 8 - Everyday Memory and Memory Errors59
-
Chapter 9 - Conceptual Knowledge73
-
Chapter 10 - Visual Imagery58
-
Chapter 11 -Language71
-
Chapter 12 - Problem Solving & Creativity44
-
Chapter 13 - Judgement, Decisions and Reasoning59
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Chapter 1 - Studying the Mind34
-
Chapter 2 - Cognitive Neuroscience38
-
Chapter 3 - Perception48
-
Chapter 4 - Attention66
-
Chapter 5 - Short-Term and Working Memory41
