ch. 9 Flashcards
(25 cards)
what is a concept?
mental constructions representing categories of information that contain defining attributes
how do we organize concepts?
categories: a group of objects that belong together
categorization: the process by which things are placed into
groups/categories
why are categories useful?
they help us understand individual cases that have not been previously encountered, they provide a wealth of information about an item
what is the definitional approach to categorization?
we can decide whether something is a member of a category by determining whether the object meets the definition of a category and use strict criteria to define a category.
problem: not all members of everyday categories have the same defining features
what is family resemblance?
items in a category resemble one another in a number of ways which allows for some variation
items in a category that have a large amount of overlap have high family resemblance.
how do we decide if something is in a category?
compare it to a prototype: an average representation of the “typical” member of a category
prototypical objects have high family resemblance
prototypical category members are more affected by a priming stimulus
what is the typicality effect?
prototypical objects are processed preferentially
highly prototypical objects are judged more rapidly and named faster
whats the exemplar approach?
a concept that is represented by multiple examples rather than a single prototype. exemplars are actual members of a category that an individual has encountered in the past and it can explain exceptions
what is hierarchical organization?
larger more general categories that are divided into smaller more specific categories which can further be divided into even smaller more specific categories which creates several levels.
what is the semantics networks approach?
concepts are arranged in networks that represent the way concepts are organized in the mind (a hierarchical model)
what is supporting evidence for the semantic networks?
if it takes longer to travel in the network, it should lead to longer reaction times.
what is spreading activation?
activity that spreads out along any link in a semantic network that is connected to an activated node, when a node is activated all activity is spread along all connected links
concepts that receive activation are primed are more easily accessed.
what are criticisms of the collins and quillian model?
it cannot explain the typicality effects, it predicts that more specific levels would yield the same reaction time if they are equal distance from a node
what is connectionism?
creating computer models for representing cognitive processes, these models contains nodes and links but operate differently from semantic networks, theyre inspired by neurons
what is the connectionist approach?
units are like neurons (inhibit or excite other units)
knowledge is represented in the distribution of many units
weights determine how strongly an incoming signal will activate the next unit.
connection weights between units determine hoe units interact: positive weights result in strong tendency to excite their next unit and lower weights cause less excitation
negative weights can inhibit activation of the receiving unit
describe the connectionist approach
there is an input unit (dog breed: pug, lab), it goes through hidden units, that then go through output units (properties: barks, four legs)
how are concepts represented in a connections network?
training the model: the connection weights must be adjusted so that activating the concept unit and the relation unit only activate the property units. this is done by supervised learning
what is supervised learning?
at the start, all weights are random
step 1: input is presented activation propagates through the layers to the output layer
step 2: output is compared to the correct output, the difference is an error signal
step 3: error signal is used to adjust weights (back propagation)
repeat this process until error signal is 0
what is graceful degradation?
damage and/or incomplete information does not completely disrupt a trained network, explains generalization of learning
because similar concepts have similar patterns, network can make predictions about concepts its never seen
what are the four proposals for how concepts are represented in the brain?
sensory functional, multiple factor, semantic category, embodied
what is the sensory functional approach?
concepts are stored based on sensory (how it looks) vs. functional (how its used) features
ex. apple = red, round (sensory), hammer = tool (function)
what is the multiple factor approach?
many different features (colour, shape, function) are used to represent concepts
ex. elephant = big, grey, walks, has a trunk
what is the semantic category approach?
the brain has special areas for different categories (tools, faces, animals)
ex. the “face area” in the brain helps to recognize faces
what is the embodied approach?
thinking about concepts involves activity caused by motor and sensory properties
