Detailed Study Guide for Exam 1 - Cognitive Psychology
Detailed Study Guide for Exam 1 - Cognitive Psychology
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Date Created: 01/31/15
Cognitive Psychology Section 1 1715 309 PM 17 History Cognitive psychology is dif cult because 39 Mental processes are not directly observable 39 Many cognitive acts involve perceiving attending remembering problem solving Many ways of arriving at any answer History Why do we want to know about history of Cognitive Psychology 39 To know what works and what doesn t to avoid making the same mistakes 0 Methods Experiments successful methods generally applied Phrenology introspection unsuccessful methods generally avoided o Theories and frameworks Humors unsuccessful ideas generally discarded Associations successful ideas broadly applied and reused Framing two key ideas for development of Cognitive Psychology intimately connected 39 Mental representation state or concept that corresponds to a thing perceived objects that have semantics 0 Thoughts concepts percepts ideas impressions notions rules schemas images phantasms 39 Mental computation activity or processing a calculation Historical Series of Movements where these ideas came from examination of ISMS Associationism roots with Aristotle but starting with Locke 39 John Locke 1632 1704 Mind represents the world as a network of ideas 39 Ideas representational unit of mental life 39 Simple ideas combine by association into complex 39 Ideas arise through experience 0 Senses traces of the world 0 Re ection on the minds own activity 39 How are associations formed 0 Psychological principles Contiguity series of things happening in close proximity and you make an association between them Similarity some resemblance between ideas links the ideas Repetition keep seeing the same 2 things being paired together 0 James Mill and John Stuart Mill Sensations and ideas Strength of associations Complex thoughts are different than their elements 0 Intellectual seeds of modern connectionism Experimental psychology begins Structuralism 51 introspection William Wundt grandfather of experimental psychology introspection Rise of experimental psychology 0 Marriage of physiology and philosophy 39 Began with introspection highly practiced form of selfexamination 0 Reports on re ection First psychology lab 1879 Wundt o Consciousness sensations images feelings o Analyzed conscious experience and their contents introspection ti 1 P 11 1 A1 o Consciousness sensations images feelings o Analyzed conscious experience and their contents introspection 0 Study of associations and fundamental principles 0 Cannot research thought because it is too complex Introspectionism 0 Advantages many people can use people can repeat procedure no fancy equipment access to thinking 0 Disadvantages results don t replicate reliability subjective interpretation different people may interpret the same experience differently Functionalism 51 introspection William James Mind is an organ that adapts to its environment 0 Structural and functional how does the mind help us achieve success 0 Pragmatist this philosophy 0 Chapters on reasoning associationism 39 John Dewey 0 Recognition of a problem isolation of the relevant features formulation of alternative solutions testing the solution 39 Early psychologists tried introspection selfreflection as a way to study thinking but found it too hard to do reliably Behaviorism 39 John B Watson 0 Focused on human behavior 0 No point to study inaccessible events of the mind 0 Instead must focus on StimulusResponse 39 BF Skinner o Operant conditioning and classical conditioning 0 Classical conditioning pair unconditioned stimulus with conditioned stimulus to cause conditioned response Unconditioned stimulus 51 unconditioned response U Presenting meat 51 salivation Conditioned stimulus 51 conditioned response E Bell 51 salivation o Operant conditioning Reinforcement or punishment Change probability of response make it stronger or weaker 39 Focus on behaviors explanations in terms of which stimuli which responses associations 0 Stimulus 51 response 39 Works well for simple learning scenarios 39 A behaviorist would explain language as just one kind of external response just like pressing a lever 39 How do you account for accurate processing of totally new experiences How do you explain thinking using stimulusresponse theory 39 Behaviorists went to the opposite extreme by finding rules of behavior and learning without any mention of what happens inside the head thinking 39 Behaviorists adopted focusing on measuring external behaviors and stimulus and response because of disadvantages of introspection History can be viewed as a set of actions and reactions but science is cumulative 1112 Cognitive Psychology 39 Cognitive psychology studies the components of thinking from perception to action 39 Modern cognitive psychology uses careful experimentation to figure out what steps in the head produce behavior Foundations 39 Information Theorv me new prouuce oenav1or Foundations 39 Information Theory 0 Claude Shannon A Mathematical Theory of Communication 1948 o Came up with ways to quantify information and make a science of it 39 Computation 0 Alan Turing computability algorithms 1936 0 Put together theoretical ideas that computation is something that can be studied 39 Donald Broadbent improve human skills theories of IP 39 George Miller chunks of information in memory 1956 o How is memory represented 39 Alan Newell and Herbert Simon 1955 developed arti cial intelligence 39 Ulric Neisser Cognitive Psychology 1967 Example Approaching an issue 39 Why do people forget o Decay vs interference Decay memories decay with time Interference constantly learning new things to be stored that may block the information you re trying to remember Both predict people forget with time Different theories have different predictions Do people forget as much when asleep Decay yes interference no didn t learn anything new while asleep Does forgetting depend on similarity of information Decay no interference yes more likely to forget if you have more similar information in mind 000 0 Theory 39 Organized body of general explanatory principles about a phenomena 39 Role organize current results provide coherence and explanation o Predict new results guide research Examples 0 Theory of Evolution helps to understand many phenomena 0 Data push theory gaps in the fossil record Theory changes punctuated equilibrium genetic drift Scienti c Process 39 Theory deduction 51 data induction 51 theory back and forth Points About Theories 39 All theories are tentative new data new measurements Making a correct prediction is not the same as being true 0 Alternate explanations what s best can often nd some differences Experiments 39 Variables 0 Independent what is being manipulamd o Dependent what is being measured Random assignment 114 Modern Approach and Perception Approaches Symbolic Information Processing 0 Main focus of many theories we will look at 0 Based on analogy with the theoretical principles computer 0 Computers have a symbolic internal representation and rules for operating on them 0 Assume a series of processing stages 0 Input 51 process 1 51 process 2 51 output A T T n Aptanan ntvml nl Assume a ser1es or process1ng stages Input 51 process 1 51 process 2 51 output Type of representation symbol Nature of processes rules It is transmitted discrete all at once or continuous as it becomes available Example Green lI see a green light l green means go Visual input 51 sensory memory simple perceptual features 51 short OOOOOO term memory perceptual semantics 51 longterm memory perceptual semantics 51 retrieved Parallel Distributed Processing PDP connectionism neural networks 0 Brainlike approach Simple units that are off or on I Units work in parallel Units connected with different strengths Activity in one unit affects activity level of other units to which it is connected Excite or inhibit o No symbols and only simple rules Methods 39 Cognitive psychology is interested in representations and processes but neither is directly observable 39 Need methods that allow us to make inferences General Methods Ask them introspection 39 See what they do behavior 39 See what their brains do 39 See what their bodies do Build a model all are useful depending on the questiorf lt Introspection 39 Advantages can give ideas about what people do 39 Disadvantages people can t describe many aspects of cognition unconscious processes even when people can describe what they re thinking they may be wrong Behavioral Methods 39 Look at what people do 39 Techniques to see how people solve a problem 0 The choices they make while doing this 0 The accuracy of their performance 39 Reaction time how fast they do it Brain Research Methods 39 Look at what their brains do 39 Invasive Techniques actively manipulate the brain by direct contact 0 Single Cell Recording 0 Electrode Implants StimulateRecord o Lesion Studies 0 Chemical Alterations PET Drug Trials 39 NonInvasive Techniques 0 Patient Populations o Neuroimaging o EEGERP o lVIRI VIRI Event Related Potentials ERP s 39 Measure ongoing electrical activity from the brain EEG 39 Look at response to events of interest specific 39 Average together several events to see what is consistent many trials of that event 7 397 39 7394 if 397 7 77777 77 39 I 39 Look at response to events of interest speci c 39 Average together several events to see what is consistent many trials of that event 39 Compare across experimental condition 39 Provides very accurate timing Functional Magnetic Resonance Imaging MRI Which brain areas are active 0 Good spatial information 0 Poor timing information 0 Can tell us if 2 processes are similar or different Similarities between ERP and fMRI imaging techniques noninvasive both based on level of activity 39 Differences electrical vs oxygenated blood signal good timing vs good spatial What does the body do 39 Psychophysiological measures eye movements other muscle activity facial muscles 39 Autonomic measures pupil size heart rate blood pressure sweat galvanic skin response Build a Model 39 Popular with IP and PDP 39 Must be explicit formal written out typed on computer 39 Provides tests of assumptions 0 Is the model sufficient to produce performance 0 Is it consistent with our other knowledge 0 Does it lead to new predictions Summary of Overview and Methods 39 Role of theories theories organize and predict tentative progress relies on multiple competing theories Experiments variables allow causal inference 39 Approaches information processing PDP 39 Methods lots of possibilities mpter 3 Perception Assumptions and Illusions What are the goals of Vision 39 What is it o Agnosia without knowledge impairment in visual recognition 0 Prosopagnosia inability to recognize faces but can still recognize objects Where is it 0 Spatial neglect paying attention to only part of the world How is it moving o Damage to motion processing areas can see objects but not motion 0 Can see objects change position but not their motion snapshots rather than motion 39 The goal of perception is to provide the person with relevant information for interacting with the world 0 The system must make assumptions because there is so much irrelevant ambiguous information in the world Illusions 39 Not seeing the world as it is because there s so much ambiguous information our brain needs to make assumptions to help us accomplish our goals evolutionary explanation 39 Show how complex vision is What is Vision for Marr 39 Vision is a process that produces from images of the external world a description that s useful for the viewer and not cluttered with irrelevant information 39 Very active process not just looking 39 It helps us accomplish our goals 39 Very active process not just looking 39 It helps us accomplish our goals 39 It s dif cult because there s lots of ambiguous irrelevant information in the world 0 Size vs distance 0 Shape vs orientation 39 Methods lots of possibilities Want to identify objects not colors or lights or edges Why is it hard to go from retina to object 0 Changing orientation 0 Occlusion partially hidden 0 Distance 0 Changing shapes for objects with parts Optics vs Reverse Optics 39 Optics what retinal projection results from this object Reverse optics 0 Psychology of visual perception 0 Trying to understand what that object is which is projected on the back of the retina o What object led to this retinal projection 0 Much ambiguity example of images from 3 bars Brain supplies missing information assumptions 0 Different object can lead to same retinal image a major problem BottomUp Processing Driven by sensory information 39 Raw sensory information general knowledge 39 Not driven by expectations for given situation Recognition of simple features recognizing object as o A frog based on having features of eyes in certain places and legs in certain places 0 A horse based on having hair in certain places and nose of given length TopDown Processing Driven by knowledge Object Identi cation 39 Analysis what are the parts Features structures 39 Grouping what parts go together Gestalt principles Matching to memory what is it Analysis what are the parts 39 Retina spatial locations and colors 39 Marr primal sketch 0 Use to determine blobs edges if make assumptions about the world 0 Description of image highlight areas of sudden change edges and little changes blobs 39 Visual input 51 lowlevel vision edges motion depth 51 highlevel vision objectface recognition Grouping what parts go together 39 Gestalt Principles 0 Proximity entities near one another are perceived as the same object o Similarity we tend to see similar objects going together 0 Continuity we tend to assume that entitles along a continuous line or surface are one object 0 Closure we often assume shapes are closed and ll in information that seems hidden Matching to Memory 39 What is the object with these parts Models iVIaLLllllls LU iVICIIIUl 39 What is the object with these parts Models 0 Feature 0 Templates 0 Structural RBC 39 Feature Models 0 Assume that objects are composed of separable parts called features 0 The memory representation of an object consists of a list of critical features associated with the object s label Features of the letter A left slanted line right slanted line horizontal line Strengths Some evidence for feature detectors Lots of exibility o Weaknesses Doesn t discriminate many objects with the same features because it doesn t take into account structural relations among features Template Models 0 Like a reverse stencil copy of a previous experienced retinal pattern that s associated with it o Strengths memory representations built from perceptual information o Weaknesses need many templates for each object changes in orientation size etc even so can be confusing similar objects 39 Template Matching OO 0 Have many templates from experiences 0 Visual input is compared to existing templates and recognize pattern if close match to a template 0 The visual image must be transformed to deal with possible differences between the size and orientation of the visual input of the template 0 Weaknesses templates don t have features just general descriptions 126 Structural Description Models Recognitionbvcomponents 39 Object recognition is mediated by recognizing components geons 0 Analysis segment into basic parts relies on nonaccidental properties 0 Grouping put features subobjects geons 0 Matching to memory recognize con gurations of subobj ects Analysis segment into parts 39 Nonaccidental relationships between contours is a signal of a subpart 39 Idea is that in most cases these nonaccidental properties that didn t occur by chance Grouping 39 Combine nonaccidental properties together to form subobjects geons Looking for how properties relate 39 Eg geon of squared block straight smooth continuation particular vertex types parallelism and symmetry along 3 axis Matching to memory RBC model 39 Each object in memory consists of structural descriptions of geons 39 So compare con gurations of geons from visual input to memory representations 39 Much more efficient eg describe word by letters vs line segments Evidence for RBC a sample 39 Vertices are more important than midsegments since vertices show the geons and their structural relations If geons are missing then much harder to recognize 0 Recognition by components RBC Model 39 Strengths 0 Structural features A anll vnnnl nlnrv nf noan can huilrl mnnv nhientq 39 oucuguls 0 Structural features 0 Small vocabulary of geons can build many objects 0 Large number of predictions supported 39 Weaknesses 0 Can t capture all objects bread 0 Objects with similar shapes not distinguished dog vs wolf Assumption single view of each object is represented Object Recognition Still much controversy but seems to have 0 Some type of structural description 0 Ability to encode multiple viewpoints Context Effects 39 Combining bottomup and topdown Proof reading idea of multiple constraints 39 Clear that topdown processing plays a role in object recognition but how early does it come in mpter 4 Attention Attention multiple senses Direct attention focus 39 Splitting attention divide 39 Pay attention effort 39 Grab attention not willful 39 Stand at attention tiring What is the problem 39 Presented with too much information Limited in how much we can process To accomplish our goals we need to 0 Focus on information ignore some 0 Divide our efforts among multiple tasks 0 Do some things without much effort Types of Attention 39 Focused attention select to attend to some ignore others 0 Present with multiple stimuli and ask to respond to only one 39 Divided attention try to do multiple tasks at same time 0 Present with multiple stimuli and ask to respond to more than one Focused Attention Selection 39 Sensory stores when does selection occur What information is selected How does selection work 0 Observation people can t see or hear everything that occurs around them or at least they can t remember long enough to use Where is the problem 0 Begin with some demonstrations When does selection occur 39 We filter out information very early Information is available for a short time only and if it s not selected then it s lost 0 By 5 seconds we ve lost all of that information Focusing Attention 39 Cocktail party effect focus on a single speaker although lots of background noise 39 Laboratory equivalent Cherry 1953 o Dichotic listening two messages one to each ear 0 Shadowing one of the ears saying one of them aloud Surprising how little people can get from unattended message 39 Can tell if it s a voice or a noise and if it s a man or a woman Cannot tell if it s foreign language or not or if it s repeated words over and over Mulrllvlllb llv vv ll l llv vvr lv vnll bvw Al vlll lln l lvllwvw lllvvvnbv 39 Can tell if it s a voice or a noise and if it s a man or a woman Cannot tell if it s foreign language or not or if it s repeated words over and over 39 Implication we can hear the sounds but not what exactly is being said Early Selection Broadbent 39 Quick and early analysis to select what information to process 39 Based on physical characteristics Problems with early selection 0 Can hear if your own name is on unattended 30 0 Can shadow even if both voices are the same 0 Bilinguals 50 of bilinguals notice if same message is in different language 39 If early selection process were correct we would never hear our name Late Selection All information sent forward and selection happens at shortterm memory stage 0 Semantic meaning effects allowed Problems with late selection 0 ERP shows that certain brain components are sensitive to which channel is attended to as early as 116 second indicating that some selection early 0 Predicts that we should be able to make simple responses to unattended but cannot 87 vs 8 S0 is it early or late selection Yes 39 Attenuation Theory related to lter model in book pg 116 o Attenuate weaken early but not totally filter out 0 So attend as much as one needs to select 0 Attenuation sensitive to experience and goals Simple summary we select information early but not total What information is selected 39 Space location or objects 0 Space we tend to the space around an object o Objects we attend to speci c objects in our environment 39 Spotlight metaphor selecting space 0 A spotlight of enhanced perceptual processing aimed at particular part of space 0 Spotlight has a size and can be shifted from one location to another 39 Attention to objects 51 useful to track things Attention spatial or objectbased Yes 39 We have multiple skills we can attend to both space and objects 39 Area of much research but seems like can attend on both the basis of space and object Experimental and patient studies May have different roles How does focused attention work Visual Search Method 0 Give a target to search for o Show display 0 Measure reaction time to respond Terminology 0 Target item you re searching for o Distractors other items in display 0 Display size number of distractors and target Predictions o If unlimited and parallel no effect of display size 0 If limited the larger displays take more time Results V n wuuuuw am parallel no we or display mm o If limited the larger displays take more time Results 39 For single feature search search time was not very different with display size 0 Popout effect 0 Suggests that individual features can be processed in parallel o The target jumps out 39 For conjunctive search search time was a linear function of display size 0 Suggests the need to attend to parts of space successively or at least limited in order to process conjunctions 0 You have to scan the space looking around for the target Treisman s Feature Integration Theory 39 Role of attention is to combine features into objects 39 Have two processes 0 Rapid automatic parallel processing of individual features red o Slower effortful limited serial processing that combines features integrates Implication of Feature Integration Theory Claims that 0 Information about individual features must focus attention on location to properly bind features 0 Thus predicts illusory conjunctions when binding fails Summary of Visual Search 39 Some information can be processed very rapidly and with little attention 39 But more complex combinations of features require more time perhaps serial run through of spatial locations bind features by location Summary of Selective Attention 39 When much of selection is early but doesn t completely stop processing of unattended stimuli 39 What evidence for both spatial and objectbased 39 How evidence from visual search two processes 1715 309 PM 1715 309 PM
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