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Introduction to Cognition

by: Ethyl Hammes

Introduction to Cognition PSYC 2150

Marketplace > University of Virginia > Psychlogy > PSYC 2150 > Introduction to Cognition
Ethyl Hammes
GPA 3.77

Daniel Willingham

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Daniel Willingham
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This 7 page Class Notes was uploaded by Ethyl Hammes on Monday September 21, 2015. The Class Notes belongs to PSYC 2150 at University of Virginia taught by Daniel Willingham in Fall. Since its upload, it has received 145 views. For similar materials see /class/209731/psyc-2150-university-of-virginia in Psychlogy at University of Virginia.


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Date Created: 09/21/15
Psychology Chapter 8 Memory Storage The Classical View Of Categorization O OO Concept a list ofnecessary and sufficient conditions for membership in a category Like representation of a dog Every object must have all attributes on the list and having those attributes is sufficeitn to be an example of the concept Category membership should be set up as a list ofnecessary and sufficient confitions where one or two features of the cards in the experiment on pg 235236 determined category membership and everything else was irrelevant Typicality Effects 0 O Typicatlity refers to the fact that not all exemplars are equally good members that is how do we decide whether something is a typical representative of its class Eleanor Rosch experiment birdier birds fruitier fruits made psychologists reexamine how we categorize The Probabilistic View of Categorization O O 0 Category membership is proposed to be a matter of probability Mind s representation ofa concept is not set up to make a black and white judgment about category membership Two versions ofprobabilistic view prototype theories and exemplar theories Prototypes 0 000 O Crucial experiment Posner and Keele 1968 Created two categories from scratch Had to memorize until categorized 12 items correctly twice in a row Then participants were tested on three types of stimuli old new and prototypes Results showed that memory representation supporting categorization is an amalgamation of the examples of the category Exemplars O O O The M O O Medin and Schaffer 1978 showed that prototypes are not necessary to understand categorization or typicality effects Posner and Keele s results indicated abstraction takes place Exemplar model maintains that all exemplars are stored in memory and categorization judgments are made by judging the similarity of the new exemplar to all the old exemplars ofa category Similarity is the key factor in both ultiple Systems View of Categorization Lance Rips 1989 had participants make categorization judgments with very little info about an object just one feature Restricted the choices to two categories 0 People see things as having rules such as how a quarter cannot be 3 inches and therefore in exible when compared to a exible option such as a pizza Allen and Brooks 1991 believed people might be able to use either rules or similarity Ashby 199820052005 who in addition to deceloping a mathematical model of category learning also tie learning to the brain Argues that there are four different systems in the brain that are responsible for learning different types of categories Attempts to use neuroscintific data to argue that there are multiple systems of categorization How is Memory Organized 0 We are unsure about how categorization operates but we can say something about how memory is organized Addressing Systems 0 Libraries use an addressing system because each entity in the storehouse has a unique address which is critical for finding what you want 0 The human mind does not use an addressing system our memory behaves in ways inconsistent with such a system ContentAddressable Storage 0 A system that seems to work more like human memory the content of the memory is itself the storage address 0 Find information based on the content of the memory 0 When you try to retrieve info that hasn t been encoded directly your memory system often pulls up related info that allows you to make an inference to answer the question Hierarchical Theory 0 One of the first models to address the question of quotwhat is the organization that allows not just the simple retrieval of facts but also the retrieval of relevant facts that we would not expect to necessarily be explicitly stored came from Allan Collins and Ross Quillian 1969 1972 Says memory is composed ofnodes and links 0 Nodes represent concepts such as red candy bird president and so forth 0 They have levels of activation meaning that they have some level of energy or excitement 0 Links represent relationships between concepts such as quothas this property or quotis an example of 0 Property Inheritance we see that concepts inherit properties from the concepts above a property in a hierarchy o Principle of Cognitive Economy refers to designing a cognitive system in a way that conserves resources Spreading Activation Theories 0 Collins and Elizabeth Loftus 1975 proposed the spreading activation model to address the shortcomings of the earlier model 0 O O O Another network that consisted ofnodes and links but now the links represent associations between semantically related concepts Memory is conceived as a cast web of linked concepts called a semantic network SiX properties of semantics A set of units Each unit represents a concept A state of activation Each unit has its own state ofactivation an amount of quotenergyquot at a given moment An output function Units pass activation to one another The amount ofactivation a unit passes to its neighbors depends on its output function which relates the current activation state of the unit to the amount of activation it sends down its links The output activation function may simply be to multiply the activation by 1 sending the same amount of activation down the links as the unit itself has or 05 sending half the activation Other models use a threshold function so the unit must meet an activation threshold before it can in uence its neighbors A pattern or connectivity Unites are connected to one another by links of different strengths The eXtent to which you know that birds y for example depends on the strength or weight of the link between bird and l39es An activation rule A unit follows a rule to integrate the activation send to it by other units via links IfI say to you quotcaramel color carbonated cold these words are closely associated with the concept of cold Suppose that these three concepts which were activated when I said the words send activation of 085 048 and 015 to the concept cola What will the activation of cold now be Should we find the mean yielding 049 Should we allow only activations higher than 025 to enter our calculations and take the mean of those yielding 067 The activation rule determines how the inputs should be combined Learning rules to change weights A semantic network cannot be static The knowledge of the network is in weights so there must be a mechanism to change the weights if the model is to learn The link between horse and peppermint would be 0 Now that you ve read that fact one time what should the weight of that link be There must be a rule by which the weights change What Else Is in Memory What Are Separate Memory Systems If there are separate memory systems in the brain then sometimes we should see a person with brain damage that disables one memory system but leaves the other system intact This finding is called an anatomic dissociation meaning that different tasks are supported by different parts of the brain 0 Five Separate Memory Systems 0 O O O OO 00 0000 0 000 O O Declarative Memory systems support conscious memory of facts for example knowing that America declared its independence in 1776 Also stores personal events for example your memory of what you did after dinner last night Declarative memory is often contrasted with procedural memory a term that encompasses other memory systems Declarative Priming Motor Skill Learning Classical Conditioning Emotional Conditioning Supported by a network of subcortical structures as well as parts of the cortex Repetition Priming Supported by the cortical perceptual areas visual priming by visual cortex and auditory priming by auditory cortex Motor Skill Learning Motor Skill can be defined as the improved accuracy ofmovements in space or time as a consequence ofpractice Most important contributor are the basal ganglia primary and secondary motor cortex prefrontal cortex the cerebellum and parietal cortex Classical Conditioning Discussed in Chapter 1 Emotional Conditioning Classical conditioning situation in which one of the unconditional responses is an emotion Fear has been studied most frequently Episodic and Semantic Memory Episodic associated with a particular time and place Also associated with a quotthis happened to me feeling there is a personal quality to the act of remembering Semantic no time or place associated with remembering or answering something Contains knowledge of things you know Chapter 11 Pp 354371 Reasoning Why Do People Reason Logically I Decision making is not the only type of problem humans face I Another class ofproblems arguably have a single answer I Problems can be analyzed using formal logic 0 Start with same question that began our discussion of decisionmaking Do people use these formal processes to answer such questions I Engage these processes dozens of times a day 0 Class at 11 it s 1050 I should leave for class 0 Formal Logic I Noted that there are optimal or correct answers to many choice problems 0 This is also true with deductive reasoning in which answers can be derived by formal logic I In problems where we apply simple logic we begin with some number or premises statements of fact that are assumed to be true I Deductive reasoning allows us to make further statements of fact conclusions 0 Premise If an election is contentious many people will turn out to vote 0 Premise The election is contentious 0 Conclusion Many people will turn out to vote I Inductive reasoningshows that conclusion is more likely or less likely to be true 0 Premise IfI cook cabbage the house smells funny 0 Premise The house smells funny 0 Conclusion I cooked cabbage I How do we know a deductive argument is valid 0 Studied in two formats 0 Conditional statements and syllogisms I Conditional statementsactually have three statements 0 First is a premise of the form quotIf P then Q o P is a condition and Q is a consequence o IfP is met Q follows I Syllogisms o Spent ALL last semester learning about these in Philosophy like 0 All candy tastes good 0 This is candy 0 It must taste good 0 Human Success and Failure in Reasoning Conditional Statements I Jean Piaget argued that the final stage of cognitive development is characterized by the use oflogic o Pragmatic Reasoning Schemas I Generalized sets of rules that are defined in relation to goals I Called pragmatic because they lead to inferences that are practical in solving problems I Schema for permissions is composed of four ifthen rules 0 Rule 1 If the action is to be taken then the precondition must be satisfied Rule 2 If the action is not to be taken then the precondition need not be satisfied 0 Rule 3 If the precondition is satisfied then the action may be taken 0 Rule 4 If the precondition is not satisfied then the action must not be taken I Schema becomes active if the problem contains words like allowed or permitted or if the problem is described in terms matching one of the rules in the schema o The Evolutionary Perspective I Leda Cosmides and John Tooby and Gerd Gigerenzer and his colleagues appealed to evolutionary concerns in reasoning I Argued that humans evolved as social animals meaning that we live in communities and have social ties that we rely on to help us survive I This rule is so important that our minds make it easy for us to understand such as when someone is breaking a moral code 0 We are also easy at detecting cheaters I We know that people are not logic machines who can plug any problem into logic algorithms with the correct answer popping out 0 Content of problems matter 0 Human Success and Failure in Reasoning Syllogisms I One type of mistake people make is conversion error in which the participant reverses terms that should not be reversed I Another problem is conversational implicature o Refers to the fact that syllogisms are a logical form and thus use the language of logicians which is not always the same as everyday language although it is easily confused I Another source of systematic errors people show in syllogistic reasoning is the atmosphere created when two premises ofa syllogism are both either positive or negative or when the quantifiers of the premises are the same I Both conclusions seem appropriate because they are consistent with the atmosphere created by the premises either because they are all negative or because they all use the same quantifier I Atmosphere accounts for about 50 of the erroneous responses in a multiplechoice format I People may also be in uenced by prior beliefs 0 Syllogisms are suppose to be purely logical exercise in which we evaluate the conclusion only in light ofits relationship to the premise 0 General Models of Reasoning I Going to consider three models of reasoning that seek to account for a wide variety of reasoning situations not just a single class of them 0 IohnsonLaird s Mental Models Theory I In mental models theory the meaning of the premises remains in a meaningbased format I Premises are used to construct a mental model of the situation that represents a possible configuration of the world I Mental models don t just represent the world they can also be used for deduction because we can combine mental models I The fact that move than one mental model can represent a premise has important implications for the way the theory works I We must generate multiple mental models representing all possible situations given the stated premises I Limitations ofworking memory seem only to predict that people will fail on problems that are difficult but the types of errors that people make are systematic beyond this failing I Many errors arise from the principle of truth which states that people tend to construct mental models representing only what is true and not what is false 0 Chater and Oaksford s Information Gain Model I Probability models of reasoning including Chater and Oaksford s 1999 model hold that people seldom engage in deductive reasoning in the everyday world rather they make judgments based on probabilities I For example when you hear about a dog you assume that the dog has fur not by deduction but because you know there is a high probability that a dog has fur I Chater and Oaksford proposed that people s main motivation in reasoning tasks may be to seek out information that will be maximally informative not necessarily information that will lead to answers that are correct according to formal logic 0 Dual Process Models


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