Chapter 9 terms - cog psycho:)

Categorization

Categories are pointers to knowledge organizing objects into groups for example classifying a sparrow as a bird

Category

Once you know something is in a category you know general things about it a group of related objects such as birds

Concepts

mental representations of categories for example the concept bird includes properties like flying

Family resemblance

family resemblances deal with the fact that definitions do not include all members meaning overlapping similarities such as games sharing features

Definitional approach to categorization

categorizing based on strict defining features such as triangle defined by three sides

Prototype

a prototype is formed by averaging category members meaning an average representation such as a robin as a typical bird

Prototype approach to categorization

deciding whether something is similar to a prototype such as recognizing a robin faster than a penguin

Exemplars

actual members of a category that a person has encountered such as specific birds like sparrows and robins

Exemplar approach to categorization

determining whether something matches stored examples such as comparing a penguin to known birds

Typicality

there are good and bad examples within a category such as a robin being more typical than a penguin

Typicality effect

reaction times are faster for more typical members such as verifying robin is a bird faster

Central tendency

averageness approach to typicality meaning representation reflects average features such as average bird characteristics

Hierarchical organization

larger categories are divided into smaller ones such as animal to bird to robin

Hierarchical model

a network that consists of nodes connected by links such as a semantic hierarchy

Cognitive economy

properties are stored at higher level nodes reducing redundancy such as has skin stored at animal level

Basic level

a privileged level of categorization most useful in everyday use such as dog

Superordinate global level

most general level such as animal

Subordinate specific level

most specific level such as golden retriever

Semantic network

concepts are arranged in networks such as bird linked to animal

Spreading activation

activation spreads to nearby locations in a network such as bird activating canary

Lexical decision task

indicating whether a letter string is a word or nonword such as word versus nord

Sentence verification technique

verifying statements about category membership such as a robin is a bird

Connectionism

approach modeling cognition using neural networks such as learning through connections

Connectionist network

units links and connection weights forming a network such as canary activating properties like fly

Parallel distributed processing PDP

processing distributed across many units simultaneously such as concept represented across a network

Units in a network

basic processing elements such as a node representing canary

Input units

units that receive incoming information such as word input

Hidden units

intermediate processing units with patterns of activity

Output units

units that produce responses such as activating can fly

Connection weight

strength of connection between units influencing activation

Back propagation

learning by adjusting weights based on error

Error signal

difference between actual and desired output used for learning

Graceful degradation

gradual decline in performance after damage such as partial knowledge loss

Semantic memory

memory for facts and knowledge such as knowing birds can fly

Anterior temporal lobe ATL

brain area that serves as a hub integrating information

Hub and spoke model

central hub with spokes representing sensory and motor information such as ATL connected to sensory areas

Category specific memory impairment

deficits for specific categories such as difficulty recognizing animals

Semantic dementia

loss of conceptual knowledge such as inability to recognize objects

Multiple factor approach

explaining deficits using multiple contributing factors

Sensory functional hypothesis

living things rely on sensory features while nonliving rely on function

Semantic somatotopy

activation occurs in brain areas related to object use such as tools activating motor cortex

Embodied approach

knowledge grounded in sensory and motor processes such as thinking of actions activating motor areas

Mirror neurons

neurons that respond during action and observation such as seeing grasping activates same neurons

Transcranial magnetic stimulation TMS

technique that disrupts processing in specific brain areas

Conceptual knowledge

knowledge about objects and their properties such as knowing what a chair is

Semantic category approach

organizing concepts based on meaning such as grouping animals

Specific level

most detailed level such as golden retriever

Global level

most general level such as animal

Basic level categorization

most useful level for naming such as dog

Crowding

difficulty recognizing objects in cluttered environments

Delayed copy task

memory task showing influence of stored representations such as copying after dela