Ch. 9 Flashcards
Conceptual knowledge
Knowledge that enables us to recognize objects and events and to make inferences about their properties
- allows us to make inferences about their properties
Definitional approach to categorization
- determine category membership based on whether the object meets the definition of the category
- does not work well
- not all members of everyday categories have the same defining features
Family resemblance
-things in a category resemble one another in a number of ways
Prototype approach
“Typical”
- average representation of the “typical” member of a category
- characteristic features that describe what members of that concepts are like
- an average of category members encountered in the past
> think of a piece of furniture
Typicality effect
Prototypical objects are named first
- highly prototypical objects judged more rapidly
- objects are processed preferentially
Sentence verification technique
Smith et al. Example
- read a sentence and then verify if it’s accurate or not
- “an apple is fruit”
Exemplar approach
“Specific”
Concept is represented by multiple examples (rather than a single prototype)
- ex: actual category members (not abstract averages )
- to categorize, compare the new item to stored examples
Basic level
Special because
Going above basic level = large loss of info
Going below basic level = little gain of info
Semantic networks
Concepts are arranged in networks that represent the way concepts are organized in the mind
Collins & Quillian:
- nodes = category/concept
- concepts are linked
- model for how concepts and properties are associated in the mind
Hierarchical model
Consists of levels arranged so that more specific concepts, such as “canary” & “salmon” are at the bottom and more general concepts are at higher levels
Spreading activation
Activation is the arousal level of a 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
Lexical decision task
Participants read a stimuli and are asked to say as quickly as possible whether the team is a word or not
(Dog, cat, smooth, Kahot, tea, coffee, lef)
Connectionist approach
Creating computer models that represent cognitive processes
Knowledge is represented in the distributed activity of many units
Input units
Activated by stimulation from environment
Hidden units
Receive input from input units
Output units
Received input from hidden units
Superordinate
Global level
Most general category level distinguished
(Ex: furniture)
Subordinate
Specific level
Most specific category level distinguished
(Ex: kitchen table)
Error signal
Differences between actual activity of each output unit and the correct activity
Back-propagation
Error signal transmitted back through the circuit
Indicates how weights should be changed to allow the outputs signal to match the correct signal
The process repeats until the error signal is zero
Graceful degradation
Disruption of performance occurs gradually as parts of the system are damaged
Category-specific memory impairment
Impairment in which they had lost the ability to identify one type of object but retained the ability to identify other types of objects
Sensory-functional (S-F) hypothesis
Explanation of how semantic information is represented in the brain that states that the ability to differentiate living things & artifacts depend on one system that distinguishes senses attributes & another system that distinguishes function
Mirror neurons
Neurons that fire when we do a task or when we observe another doing that same task
Semantic category approach
Specific neural circuits in the brain for specific categories
Crowding
When different concepts within a category share my properties
(Ex: “animals” all share eyes, legs and ability to move)
Semantic dementia
Condition which there is a general loss of knowledge for all concepts
Anterior temporal lobe
Damage ATL has been connected with semantic deficits in dementia patients and with the savant syndrome
