INTRO TO COGNITIVE PSYCHOLOGY
INTRO TO COGNITIVE PSYCHOLOGY PSY 305
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This 19 page Class Notes was uploaded by Marco Wolf on Monday September 7, 2015. The Class Notes belongs to PSY 305 at University of Texas at Austin taught by Arthur Markman in Fall. Since its upload, it has received 18 views. For similar materials see /class/181787/psy-305-university-of-texas-at-austin in Psychlogy at University of Texas at Austin.
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Date Created: 09/07/15
Foundations cont Complexity Testing explanations in psychology Cognitive Neuroscience Complexity is key The amazing thing about thought is that everything is too complicated for us to do 7 Yet We manage to get around the World What do we mean by complexity 7 There are always many possibilities 7 Only a few of them are relevant 7 How do We decide which ones are correct Example How can you get to Dallas from here Possibilities 7 Drive 7 Take a bus 7 Take a plane 7 Walk There are many other options too 0 Unlikely routes 7 Drive via Peru 0 Unlikely modes of transportation 7 Scooter Impossible actions 7 Magical transportation devices 0 Unlikely time scales 7 3 minutes 275 years 0 If we considered all of these possibilities how would we ever decide what to do Complexity 0 Somehow we manage to solve these problems 0 What must happen 7 We must limit the options we consider 7 We must think quickly enough to consider a reasonable number of options 0 How does this happen Constraints 0 A central theme this semester is constraints 0 The cognitive system has many ways of focusing on what is relevant 7 Constraints promote inform ation likely to be relevant 7 Some possibilities may be missed 0 Constraints determine what is easy or hard to do 7 Theories suggest possible sets of constraints 7 Experiments test Whether people use those constraints Ways of testing theories Return to levels of explanation Theories may describe constraints at different levels of explanation 7 Computational level 7 Algorithmic level 7 Implementational level Different kinds of data will be relevant to each type of explanation an experiment m human 62C x your highnm your gt lzeal name is won Bekhenyou39re ogging mus me 9 it39s lee lBQquot home 539 Computational level explanations Computational level explanations specify inpuU output relationships Studies must explore these relationships Given a particular situation or stimulus 7 What is the output 7 Does that output differ from what is optimal That is the best that could happen 7 Example Psychophysics 7 What possibilities are considered Are some possibilities excluded 7 Example Parsing language Methods Ratings and judgments 7 Similarity typicality gmmmaticality Problemsolving studies Classi cation and Learning Memory tests 7 Recognition 7 Recall Algorithmic level explanations Specify representations and processes 7 O en suggests What Will be easy and hard to do Tests must distinguish between types of representations and processes Response time 7 A measure of What is easy and hard Example Mental rotation Thinkaloud protocols 7 Speaking aloud the inner voice Example Selfexplanation elfects Implementational level explanations Speci es how thought is implemented 7 Human thought occurs in the brain We cannot open up people s brains in general Cognitive neuroscience 7 Using natqu experiments 7 Noninvasive brain imaging PET MRI and ERP 7 Let s focus on these a bit more This is your brain Four lobes IFrontal IP arietzl ITemporal I Occipitzl It is not this color of course Neurons and activity 0 The active cells in the brain are neurons 0 They send signals called action potentials 7 These signals in uence neighboring cells 7 Signals are electrical The combined activity of neurons carries activation What When and Where There are three key aspects to studying people s brains What functions are performed Where are they performed When does the activity occur Lesion Studies Studying brain damage can tell us something about what areas of the brain affect particular functions 7 Ifan area has a lesion and the person shows a speci c de cit then that area probably has some thing to do with that lnction Pretty vague conclusion Example Memory disorders 7 Lesions of the hippocampus and memory Brain imaging We want to know where the activity is happening 7 Spatial resolution We want to know when it occurs 7 Tempoml resolution Different techniques have different strengths ERP Event Related Potentials Electrodes are placed at the scalp 7 Measure small changes in voltage a er presentation of some stimulus Poor spatial resolution 7 Current must pass through scalp Excellent temporal resolution HWRI Functional Magnetic Resonance Imaging Measures cerebral blood ow 7 Probably related to neural activity Excellent spatial resolution Poor temporal resolution PET Positron Emission Tomography Also a measure of brain activity 7 Traces path of radioactive substance put in blood 7 Often measures glucose uptake 7 More invasive than M I Not used as o en as fMRI any more Good spatial resolution Poor temporal resolution EROS EventRelated Optical Signals Shine an infrared light into the skull 7 Measure how it is re ected back from the brain 0 Gives a measure of activity on the cortex 7 Good temporal resolution 7 Good spatial resolution 0 Cannot give information about subcortical internal structures in the brain 7 Can be used in conjunction with M1 Summary Much remains to be learned about the brain We will touch on evidence from cognitive neuroscience this semester There may be limits on what we can learn from the brain 7 It is not necessaiy that the Way my bmin does something is the same as the Way your brain does the same thing Perception Outline for the next 2 lectures 7 What is perception for 7 Aspects of perception 7 Lowlevel perception 7 Constmints 7 Midlevel vision Gestalt organization 7 Perception and the brain What is perception Somehow we must connect to the world There are sources of energy around us 7 Some are good light sound heat 7 Some are bad sharp obj ects intense heat These sources of energy provide information to allow us to satisfy goals Perception allows us to use this energy Perceptual modalities We perceive many aspects of the world 7 Light in the visible spectrum vision 7 Air movement hearing 7 Infrared mdiation heat 7 Forces approaching dangerous levels pain 7 The presence of certain chemicals taste odor 7 The position of our bodies in space proprioception In this course we focus primarily on vision Organization of Vision Finding edges Detecting colors Locating objects in space Organization of Vision Determining obj ect features Segregating Obj ads from Mid level vision background Organization of Vision 39 Object High level vision recognition Face reco nition g Mld level Vlslon Scene recognition The problem of Vision 0 Visual space is threedimensional We have two eyes The retina of each eye is twodimensional Information about the threedimensions must be extracted from twodimensions Percepts are ambiguous Possibilities There are far more possibilities than we see 0 Vision immediately gives us objects We don t just see squiggles and textures The Visual system makes guesses about What is out in the world We are interested in how it makes those guesses Constraints Constraints limit the possibilities considered What kinds of constraints does the visual system use Example 7 How far away is an object Depth Cues 7 Monocular cues only one eye is needed Stationary cues Kinetic cues 7 Binocular cues two eyes are needed Many have been incorporated into paintings Monocular cues lnterposition 7 Nearer things block farther things Linear Perspective 7 Things recede into the distance l l Constraints and illusions Sometimes the guesses made by the visual system turn out to be wrong 7 The MullerLyer illusion 7 Why might this happen Linear perspective Relative size The same object makes a smaller retinal image when it is far away than when it is close Kinetic cues to depth Motion parallax Things that are close move more quickly than things that are far away Animators make use of this cue On the freeway Trees whiz by Mountains do not move as much The sun or moon seems to stay in the same place Binocular cues to depth Convergence When objects are very close the eyes point inward When objects are at a distance eyes point in a more parallel direction Stereopsis 0 Your eyes are a few inches apart They get slightly different Views of an object 0 Try it 0 The Visual system matches up the images from each eye The amount of disparity between corresponding points is used as a measure of distance Images do not need to have meaning Random dot stereograms can give the illusion of depth Summary of depth cues Monocular Stationary cues Kinetic cues Binocular cues 0 These cues take some time to develop What are the objects The visual system must gure out what aspects of the world go together 7 What aspects ofa scene are part ofthe same object 7 What aspects are a pan of different objects Example Gestalt laws of grouping Grouping principles Proximity vs Similarity 0000 OOOOOOOOO vs 000000000 000000000 Good Continuation Common Region 0000000 0000000 Vs Why we have these rules 0 Vision must happen quickly 7 We cannot afford to spend much time processing 0 There are not a lot of likely possibilities 7 Optics does not change I Evolution had along time to nd good methods of perception 7 There are many useful regularities in the visual world 7 Illusions rarely happen in the Wild Lowlevel vs Highlevel perception I Many regularities in lowlevel perception I Fewer regularities in highlevel perception 7 Many possible kinds of objects 7 Complex kinds of motion I Biological motion I We explore issues in highlevel perception next class Biological Motion Perception and the brain I Visual information 7 Retina 7 Thalamus like a relay station 7 Occipital lobe 7 Information is initially separated by visual field I Le Visual eld to right hemisphere I Right Visual eld to le
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