1
Q
Category
A
- set of objects that can be treated as equivalent in some way.
- they share many properties and are informative
2
Q
Concepts
A
- mental representations formed of categories
- core of intelligent behavior
- allows to extend what you have learned about a limited number of objects to a potentially infinite set of entities.
3
Q
Nature of categories
A
- well defined = definitions about what is in and out of the category.
- provides necessary feature for category membership
- the features must be jointly sufficient for membership
- limitation: clear cut boundaries while the world is not.
4
Q
Fuzzy categories
A
- categories have unclear boundaries that can shift over time.
5
Q
Fuzzy categories: borderline members
A
- outliers to categories or items
6
Q
Fuzzy categories: typicality
A
- some items are more typical than others.
- most important variable in predicting how people interact with categories.
- category prototype: most typical category member. Other items are compared to this.
- influences of typicality on cognition: judgement, speed, memory, accessibility, understanding and repeatability.
- source: family resemblance theory (features frequent in other categories enhances typicality) and frequency.
7
Q
Category hierarchies:
A
- most concrete categories are nested inside larger, abstract categories.
- the basic level: not too small, not too big but just right and from a neutral situation = easy to learn. Experitise, quality of life and upbringing influences this.
- explanation: category members are similar to one another but they are different from members of other categories.
8
Q
Prototype theory
A
- general description learned that applies to the category as a whole.
- weighted features by frequency
- typical members have high weight = easier to match
9
Q
Exemplar theory
A
- theory denies the general description of a category
- claims that concepts are remembered examples.
- classification happens through comparison of previously seen items.
- close similarity has a large effect on classification.
10
Q
Modern ideology
A
- concepts are represented through multiple cognitive systems: both general descriptions and exemplars.
11
Q
Semantic networks
A
- knowledge is stored in the form of associative networks = concepts are represented by nearby nodes corresponds to related concepts.
12
Q
Semantic networks: category verification task
A
- used to determine how we access categorical knowledge.
- participants as to verify or deny simple statements
- accuracy not important
- speed is important = connections and proximity of the features.
- the process where the activation of one nodes spreads to other, related nodes
13
Q
Semantic networks: feature verification tasks
A
- used to asses how the features of categories are stored and accessed.
- participants asked to verify or deny simple statements
- accuracy not important
- speed is important = connections and proximity of the features.
- the process where the activation of one nodes spreads to other, related nodes
14
Q
Semantic networks: spreading activation model (collins and loftus)
A
- Assumptions about representation of knowledge and aout nodes being lined in an associative network.
- the strength of activation decreases as a function of time, distance and number of concepts activated (more concepts, the less activation any once concepts receives).
- the activation taht reaches any concept node is summed up = after threshold, concept is activated
- semantic priming: tendency for the processing of one stimulus to enhance/speed up the processing of another related stimulus.
15
Q
Functions of concepts
A
- building blocks of thought
- sever as mental shorthand that allows for quick and efficient understanding.
- going beyond the present and making predictions.
- infer knowledge not explicitly related
- support new learning
- important for communication
16
Q
Categories as a concept:
A
- Natural kind: they define themselves. They share characteristics and are labeled after discovery.
- Artifacts: includes objects/conventions designed by humans to serve particular function. They dont share the same basic features.
- Ad hoc: formed in the service of the same goal. They do not share any characteristics.
17
Q
Similarity based categorization: classical view
A
- items are classified into category if they have certain feature = both necessary and sufficient
- limitations: difficult to specify, cannot explain typicality, boundaries are too clear cut.
18
Q
Similarity based categorization: prototype approach
A
- specific features of the category that members are likely to have.
- evaluated and classified based on ressemblance to other members
- high family ressemblance = typical member
- abstract through repeated experience = most representative, quickly and easily accessed, distance between labels and prototype is short.
- solves the rigidity, typicality and fuzzy boundary problems.
- limitations: categories are more complex and sensitive to context.
19
Q
Similarity based categorization: exemplar approach
A
- represent categories in terms of examples
- extreme version: no abstraction or generalization process = every single encounter
- typicality effect: no problem here (more likely to retrieve items that been encoded frequently).
- biasing effect: context is no problem (content activates certain examples due to priming retrieval).
- sensitive to correlations: typical = high correlation, less typical = low correlation.
- limitation: abstract representations, economy (not every example is stored).
20
Q
Similarity based categorization: knowledge approach
A
- connecting concept to existing knowledge
- psychological essentialism: believe categories have underlying properties that are found only in that category.
- decisions made through assumptions
- signs of essentialism: in or out of the category, resistance to change, essence is passed on to progeny.
- limitation: no statement about typicality, too difficult/broad, boundaries too clear-cut.
21
Q
Conceptual knowledge using picture drawing in semantic dementia: abstract
A
- 6 patients with semantic dementia asked to produce drawings of concrete concepts from dictation
- drawing were characterized by a loss of distinctive features
- artifact domain = feature loss resulted in box-like representations.
- living domain = distinctive features lost and tendency to include incorrect features that resulted in more familiar and prototypical representations of bigger concept.
22
Q
Conceptual knowledge using picture drawing in semantic dementia: introduction
A
- semantic memory = knowledge about concepts, facts and words/meanings
- semantic demantia happens late in life
- aim: investigate the structure and internal representation of visual conceptual knowledge
23
Q
Conceptual knowledge using picture drawing in semantic dementia: methods
A
24
Q
Conceptual knowledge using picture drawing in semantic dementia: results
A
- less target features drawn
- either less features or included more features that were typical in neighboring categories
25
Conceptual knowledge using picture drawing in semantic dementia: discussion
- supports prototype theory: hierarchy of things
- against exemplar approach: it should be more likely that the distinctive features will be kept.
Cognitive Psychology
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