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Intro to Cognitive Psychology

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Intro to Cognitive Psychology 4040

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Notes covers chapters 1-4 & a sample test (study guide)
Introduction to Cognitive Psychology
Stephen R. Schmidt
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This 71 page Bundle was uploaded by Ashley Robinson on Sunday January 24, 2016. The Bundle belongs to 4040 at Middle Tennessee State University taught by Stephen R. Schmidt in Fall 2015. Since its upload, it has received 15 views. For similar materials see Introduction to Cognitive Psychology in Psychlogy at Middle Tennessee State University.


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Date Created: 01/24/16
Foundations of Cognitive Psychology I. Metaphors for the Mind A. Analogies and Metaphors B. Prominent Metaphors in Psychology C. Mechanistic Metaphors in the Evolution of Cognitive Psychology II. Methodological Developments A. Introspection B. Performance Measures C. Physiological methods III. Conclusions A. Analogies and Metaphors Thesis: Much of scientific reasoning and discourse is done with metaphorical language. This is especially true in psychology. “In psychology, we can only describe things by help of analogies. There is nothing peculiar in this; it is the case elsewhere as well. But we have constantly to keep changing these analogies, for none of them lasts us long enough.z (Freud, 1926/1959, p. 195) By analyzing the metaphors of the mind, and how those metaphors have changed, we can gain insight into the history and current state of cognitive psychology. Page 1 A. Analogies and Metaphors 1) Metaphors in Science a) Metaphors can aid understanding. analogy: the atom is like the solar system Metaphorical description: electrons orbit the nucleus. 2) Flashbulb Memory Hypothesis Example of a metaphor in psychology. Flashbulb memories are lmemories for the circumstances in which one first learned of a very surprising and consequential (or emotionally arousing event (Brown & Kulik, 1977, p. 73). These memories are “...very like a photograph that indiscriminately preserves the scene in which each of us found himself when the flashbulb was fired (Brown & Kulik, 1977, p. 74)z Do you have “flashbulb memories?” 2) Flashbulb Memory Hypothesis Strengths: Compelling – compliments our own experiences Provides specific predictions - - indiscriminate - high accuracy Page 2 2) Flashbulb Memory Hypothesis Problems Metaphors are often mistaken for explanations: How does flashbulb memory work? Is there a camera like mechanism in the brain? Obviously not, so this is not a compelling explanation of why we remember emotional events. 2) Flashbulb Memory Hypothesis Problems (continued) Compelling metaphors are very difficult to dislodge. - Overwhelming evidence that memories are not indiscriminate and not accurate, yet the hypothesis still holds a prominent place in public discourse. B. Prominent Metaphors of Mind (based on Sternberg,1990) Metaphor Examples Theorists Spatial/ Gestalt Theory Kohler Geographic Structure of Intellect Guilford Mechanistic/ Man as Machine Descartes Computational Modal Model Atkinson & Shiffrin Biological Hemispheric Localization Levy Now print Livingston Epistemological Schema Theory Piaget Sociological Personal event memory Pillemer Zone of Proximal Development Vygotsky Page 3 Metaphors of Mind (based on Sternberg,1990) Can we classify these metaphors? lhard wiredz behaviors lgutz reactions “social network” lthe beast withinz ldriving forcez lletting off steamz lstressz C. Mechanistic Metaphors in the Evolution of Cognitive Psychology 1. Writing Systems Plato: wax tablet carried by his student John Locke (1600`s) "tabula rasa” C. Mechanistic Metaphors in the Evolution of Cognitive Psychology 2. Photography Draper (1856) ganglion cells store limpressions” much like a camera. Brown & Kulik (1977) flashbulb memory hypothesis Page 4 An application of the photography metaphor to the human mind. What goes on in our head when we see a car and say lauto.z (Kahn, 1929). ho·mun·cu·lus (little man) Etymology: Latin, diminutive of homin-, homo human being C. Mechanistic Metaphors in the Evolution of Cognitive Psychology 3. Telephone Systems and Information Transmission Shannon and Weaver (1949) model of communication Miller (1951; 1967) Language and Communication Described humans as a communication channel. 3. But telephone systems required operators. Page 5 4. Computer Metaphor The computer was developed during WWII in a major effort to decode messages sent by the Axis Powers. The code breaking machine Colossus, 1943 4. Computer Metaphor Alan Turing was one of the people who worked on that project Alan Turing “General Turing machinez (Turing, 1950) 1912-1954 Any process that can be defined by a series of precise steps can be programmed to be performed by a general machine that processes symbols. Philosophical foundation of the computer metaphor of mind William James (1842-1910) Functionalism: description of mental processes in terms of their function, or adaptive significance. The mind is what it does. If we can describe what the mind does as a series of steps, then these steps could be preformed by a symbol processing (Turing) machine. Page 6 Are computers an adequate metaphor for the mind? Turing`s test: lTuring (1950) describes the following kind of game. Suppose that we have a person, a machine, and an interrogator. The interrogator is in a room separated from the other person and the machine. The object of the game is for the interrogator to determine which of the other two is the person, and which is the machine.z ( ) Example: Mitsuku Chatbot Cognitive Psychology and the computer metaphor lThe task of a psychologist trying to understand human cognition is analogous to that of a man trying to discover how a computer has been programmed.z (Neisser, Cognitive Psychology, 1966, p. 6) Ulric Neisser 1928-2012 Does the machine matter? Three symbol processing “machines” Yes! Biological foundations of behavior: innate responses prepared learning (e.g., language acquisition) embodied cognition (localization of function) Page 7 5. Neural Networks (beyond the simple computer metaphor) Hopefield (1982) Described a method of storing information that was more lneurologically realistic” than the simple on/off switches of a digital computer. Memory consisted of a set of homogeneous components connected in layers Simple Pattern Associator (Rumelhart & McClelland, 1986) Neural Networks Neural Networks had a number of properties that made them attractive as a metaphor: - large storage capacity - content addressable - distributed representation - lgraceful degradationz Page 8 3. Conclusions on metaphors b) Metaphors are closely tied to discoveries and technologies of the day. c) These metaphors help us understand our mental processes by tying them to everyday experiences (i.e., they are compelling). d) But, we must remember, they are metaphors, not explanations or scientific statements, and they can be misleading, and resistant to change. II. Methodological Advancements Thesis: Changes in the way we view the mind (as seen in our metaphors) have paralleled changes in how we study the mind. Like our metaphors, methodological changes are driven by technological developments. II. Methodological Advancements A.  Introspection 1) definition -  llooking inwardz -  lreflectionz Page 9 A. Introspection 2. Strengths: a) easy b) intuitive appeal 3. Weaknesses: a) How do we resolve disagreements? b) Introspections are often wrong c) Cognitive processes are often hidden from conscious inspection B. Performance Methods 1) Recall, Recollection, and Savings Ebbinghaus (1885) Methodical study of memory. Hermann Ebbinghaus 1850-1909 B. Performance Methods 2) Patterns of errors Example: errors in auditory recognition of letters stimulus responsespercent lcz▯▯▯▯▯▯▯▯▯▯▯▯▯▯▯lcz80 lpz 10 lbz 6 lvz 2 What does this tell us about letter perception? Page 10 3. Reaction Time (RT) Mental Chronometry Donders (1850`s): method of subtraction Hipp Chronoscope Prior to Donders, people thought that mental processes occurred instantaneously. Donders was the first to time perceptual and decision processes. General Assumption: Processes that take longer involve greater number of steps or engage more mental resources than faster processes. D. Physiological methods 1)  magnetic resonance imaging (MRI): “A test that uses a magnetic field and pulses of radio wave energy to make pictures of organs and structures inside the body.” (Web MD) 2) functional magnetic resonance imaging(fMRI) Measures brain activity by detecting changes in the level of oxygen in the blood. Neuronal activity consumes oxygen, and oxygen levels in the blood respond differently to the magnetic fields in the fMRI. - high spatial and temporal resolution - non-invasive and does not involve radiation Page 11 3) Positron emission tomography (PET) “uses trace amounts of short-lived radioactive material to map functional processes in the brain. When the material undergoes radioactive decay a positron is emitted, which can be picked up be the detector. Areas of high radioactivity are associated with brain activity.” (PsychCentral) Example: Reuter-Lorenz, et al., (2000) Pet scans of older and younger adults while rehearsing lists of four letters in memory. III. Conclusions Philosophical and Technological developments have driven how we think about our minds and how we think about ourselves. This can be seen in the metaphors we use to describe mental processes, the theories we develop, and the methods we use to study the human condition. Page 12 A Process Model of Cognition I. Information Processing Approach II. Overview of the Model III. Some important Distinctions IV. Evolution of the Model I. Information Processing Approach A. Computer analogy B. Stage analysis Input Output Stage 1 Stage 2 Stage 3 II. Overview of the Model A. Atkinson and Shiffrin (1971) Model Short-­‐Term  Store Input Sen     Long-­‐Term   Registers Conrehearsal  sses   coding    Store retrieval Output II. Overview (cont) B. Major Central Processing Unit (CPU) Components of the computer system Primary storage Arithmetic unit logic unit Input Output Control Unit Secondary storage Information Processing versus Freudian view of the mind. “Es”, “Ich” and “Überich” refer to the id, ego, and the superego, whereas, voerbewusst is the conscious mind, and unbewusst the unconscious mind, verdrangt is the repressed. III. Some important distinctions A. Structure vs. Processes structure ~hardware process ~ software III. Some important distinctions B. Psychological Structures (e.g., STS) vs. Physiological Structures (e.g., hippocampus) There is no reason to expect a one-to-one relation between these! Psychological vs. Physiological Structures PET activations during a verbal working memory task (Smith & Jonides, 1997) C. Levels of Analysis (Marr, 1982) Computational Algorithmic Implementation What is computed? How are computatiHow are algorithms completed physically realized? Map of input to outForm of representaphysical system Nature of operations Example 1: calculator Example 2: counting windows IV. Evolution of the model Recursive Decomposition Short-Term Store Visio-Spatial Sketch Phonological Loop Central executive resource pool priorities for allocation of resources A Process Model of Cognition I. Information Processing Approach II. Overview of the Model III. Some important Distinctions IV. Evolution of the Model Pattern Recognition I. What is pattern recognition? II. Template Models III. Feature Models IV. Top-Down & Bottom-Up processing V. Neural Network Models VI. Prototype Models VII. Facial Recognition VI. Conclusions I. What is Pattern Recognition A. Definition: A process of identifying a stimulus. Recognizing a correspondence between a stimulus and information in permanent (LTS) memory. I. What is Pattern Recognition B. In the context of the Atkinson and Shiffrin Model Input Sensory Short- Long- Store Term Term Store Store Control Processes rehearsal coding retrieval strategies Response Output Page 1 I. What is Pattern Recognition C.incomplete or ambiguous information.with D. Many variations on a pattern may be objects.ed as the same “object” or class of Page 2 Turing test (used by Yahoo, Hotmail, and ebay) E. Pattern recognition that is difficult for machines is easy for people. Or not! fi yuo cna raed tihs, yuo hvae a sgtrane mnid too. I cdnuolt blveiee taht I cluod aulaclty uesdnatnrd waht I was rdanieg. The phaonmneal pweor of the hmuan mind! Uinervtisy, it dseno’t mtaetr in waht oerdr the ltteres in a wrod are, the olny iproamtnt tihng is taht the frsit and lsat ltteer be in the rghit pclae. Thraed it whotuit a pboerlm. and you can sitll Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe. Azanmig huh? [This demonstration is food for thought. The psychological principles it espouses are only partly correct. See Reicher (1969)] Page 3 II. Template Model A. Basic Assumptions 1) Memory representation is a holistic unanalyzed entity (a template). 2) An input pattern is compared to the stored representation. 3) Identity is determined by selection of the template with the greatest amount of overlap. II. Template Model B. Schematic of a Template System Stimulus Detectorss A Light Source Templates II. Template Model (cont) C. Template systems in action Page 4 Template Model (cont) D. Problems with template models 1. Intolerance to deviations 2. Large number of templates required 3. Cannot support similarity-difference judgments III. Feature Theories A. Basic Assumptions 1. The stored representation is a description of past inputs in terms of list of attributes or features. 2. Inputs are broken down into a small list of constituent features. 3. Identity is determined by selecting the feature list most similar to the input. III. Feature Theories B. Schematic of a Feature Model Stimulus Page 5 III. Feature Theories (cont) C. Supporting Evidence 1. Hubel & Wiesel (1962): Recorded electrical activity in the visual cortex of the cat. Hubel & Wiesel (1962) Results: specific cells respond to specific visual features. III. Feature Theories (cont) B. Supporting Evidence (cont) 2. Letter recognition times Gibson, Shapiro, & Yonas (1968) Step 1: Analyze letters in terms of a small set of features. Stsame or different.s a reaction test two determine if two letters are the e.g. G vs.. RT = 458 msec P vs.. RRT = 571 msec Step 3: Compare the clustering of letters in the reaction time task to the similarities in features. Page 6 Step 1: Feature Analysis of Letters Step 2: Letter Groupings based on RT III. Feature Theories (cont) D. Criticisms of Feature Theories 1. Importance of Context 2. Importance of Arrangement Page 7 IV. Top-Down vs. Bottom-up Processing comprehension Bottom Up phrase processing Top Down (data driven) word processing (conceptually letter processing driven) feature processing Bottom-up vs Top-down Find the word in red: Find the name of a fish lettuce pants broccoli sock tomato shoe cucumber shorts peas sweater corn tuna potato skirt celery jeans onion coat IV. Top-Down vs. Bottom-up Processing In Control of Attention (Bushman & Miller, 2007) implanted electrodes in monkeys the monkeys were trained to search for a target in a visual display the researchers measured reaction time and recorded firing rates in parietal cortex (25 electrodes) (visual- sensory information) and the prefrontal cortex (25 electrodes). Page 8 IV. Top-Down vs. Bottom-up Processing Bushman & Miller (continued) Bottom up: visual pop-out Sensory neurons (parietal) responded first IV. Top-Down vs. Bottom-up Processing Bushman & Miller (continued) Top down (visual search) prefrontal cortex responded first Page 9 IV. Top-Down vs. Bottom-up Processing Conclusion: Button up processing signals arise from the sensory cortex. Top down processing signals begin in the frontal cortex. V. Neural Network Model of Word Analysis Pattern Recognition A. Interactive Activation Model (McClelland & Rumelhart, 1981) Letter Analysis Incorporates top-down processing from the word level to the letter level. Excitatory connections: Feature Inhibitory connections: Analysis Visual Input Simplified view of the Network of Connections Excitatory connections: Inhibitory connections: CAT CHAIR THE Word Level A C H T E Letter Level Feature Level Input Page 10 More Complete view of the Network of Connections: B. Supporting Evidence: The word/letter effect Reicher (1969) Stimulus Example Test Percent Correct 78 letter h h/t series csah csah/csat 76 word cash cash/cast 89 VI. Prototype Theory A. Basic Assumptions 1. The stored representation is a Prototype: an abstraction of the typical or best example of an object. examples: chairs, cars, and trucks 2. Inputs are broken down into feature lists. 3. Recognition is process of comparing the features of the input to the features of prototypes, and selecting the best fit. Page 11 VI. Prototype Theory (cont.) B. Evidence for Prototype Theory Solso & McCarthy (1981) face recognition Faces constructed from a Police “Indentikit” Solso & McCarthy (1981) Sample Materials Prototype 100% VI. Prototype Theory (cont.) Solso & McCarthy (1981) results Old e n C New Old PictuNew Pictures Percent Overlap with Prototype Page 12 VI. Prototype Theory (cont.) C. Prototype Theory and attractiveness 1) “goodness” of category membership can be defined with respect to the prototype. 2) “good” category members may be seen as more attractive, or desirable, than “poor” category membership VI. Conclusions on Pattern Recognition A. Template and Feature Models are inadequate B. Context and top-down processing are very important C. Neural Networks can explain top down processes. D. Important role of prototypes Page 13 Sensory Storage I. Context II. Visual Sensory Store III. Auditory Sensory Store IV. Other Senses? V. Summary I. Context AAtkinson and Shiffrin Model Sensory Short- Long- Input Store Term Term Store Store Control Processes rehearsal coding retrieval strategies! Response Output II. Visual Sensory Store A.  A Brief History Segner (1740, as cited in Baddeley, 1999) attached a glowing ember to a rotating wheel. Sperling (1960) research at Bell Labs Page 1 II. Visual Sensory Store A.  Demonstrations Spinning light Whole report (Sperling`s Experiments) Partial report Targeted report (Averbach & Coriell, 1961) Visual Sensory Memory (cont) B. Results of Sperling`s Experiment Sperling's Data 100 90 80 Partial Report tc 70 C 60 50 40 Whole Report t 30 Pr 20 10 0 -0.2 0 0.2 0.4 0.6 0.8 1 Inter- Stimulus Interval Visual Sensory Store (cont) C. Properties of Visual Sensory Store 1. capacity unlimited 2. forgetting rapid decay: 1/4 to 1/3 sec masking 3. coding visual pattern Page 2 Visual Sensory Store versus After Images Visual Sensory Store versus After Images opponent processing of cone outputs del color/water_color/ Page 3 Visual Sensory Store versus After Images Visual Sensory Store After Image Very brief (250 msec) Lasts several seconds a week True color Complementary color High acuity Fuzzy III. Auditory Sensory Store A. The 3 eared man experiment Darwin, Turvey, and Crowder (1972) Left Both Right B 8 F 2 6 R L U 10 A. The 3 eared man experiments (cont) Results: 5.0 4.5 Items Correct Whole Report 4.0 0 1 2 3 4 Seconds Page 4 III. Auditory Sensory Store (cont) The Modality Effect: Demonstration –series of numbers.itory presentation of a random –order.ust remember the numbers in correct re1all recall Page 5 List 1 (visual) List 2 (auditory) 6 4 4 2 8 7 3 6 5 3 2 5 7 1 1 8 Modality Effect: Serial Position Curve 0.70 0.60 0.50 Probabilit0.40 Visual Correct Auditory 0.30 0.20 0.10 0.00 1 2 3 4 5 6 7 8 III. Auditory Sensory Store (cont) B. The Modality Effect (Conrad & Hull, 1968) 100 90 Silent 80 Aloud Percent 70 Correct 60 50 40 30 20 10 0 1 2 3 4 5 6 7 Serial Position Page 6 III. Auditory Sensory Store (cont) C. Suffix Effect (Crowder 1972) 1.00 Suffix 0.90 No Suffix 0.80 0.70 0.60 0.50 0.401 2 3 4 5 6 7 8 9 IV. Other Senses? A. Tactile Sensory Store Tactile modality and suffix effects. see Mahrer & Miles (1999) B. Smell Olfactory recency and suffix effects. see Miles & Jenkins (2000). C. Taste? V. Summary A. Purpose attention pattern recognition B. Common Properties large capacity brief duration modality bound Page 7 1 Attention I. Introduction II. Early vs. Late Selection III. Broadbent’s Model IV. Treisman’s Model V. Norman’s Model VI.  Resolution VII.  Resource Allocation VIII. Cell Phones IX.  Conclusions 2 I. Introduction A. The bottleneck in information processing attended Sensorys Inputs 3 I. Introduction (cont) B. Demonstration Somewhere Among hidden the in most the spectacular Rocky Mountains cognitive near abilities Central City is Colorado the an ability old to minerselect hid one a message box from of another. gold. We Although do several this hundred by people focusing have our looked attention for on it, certain they cues have such not as found type it color. 4 II. Early vs. Late Selection A. Early selection: Input #1 Perceptual Pattern Control Processes Input # 2 Filter Recognition e.g., memory response organization etc. 5 II. Early vs. Late Selection (cont) B. Late Selection Input #1 Pattern Output Control Processes Input # 2 Recognition Filter e.g., memory response organization etc. 6 III. Broadbent’s Filter Model A. Properties: 1) Early selection 2) Selection (filtering) is based on physical properties of the stimulus (e.g., pitch, loudness, etc...). 3) Attention is directed to information that passes the filter or to physically salient information that leads to a shift in attention. 4) Only one input channel can be processed at a time. 5) It takes time to shift attention. 7 III. Broadbent’s Model B. PhysicalAnalogy Input # 1 Input # 2 5 6 1 2 Sensory processes (wide) Hinged flap (filter) Limited capacity perceptual channel (narrow) outputin condition 1: 1,2,3,4,5,6 outputin condition 2: 1,3,5,2,4,5 8 III. Broadbent (cont) C. Supporting Evidence: Broadbent (1954): split span experiment f/f Stimulus presentation ear #1 ear#2 f/f 7 8 m/f 4 2 3 6 Responses m/f condition 1: recall by ear: “743-826” condition 2: recall in order: “78, 42, 36” 9 III. Broadbent (cont) C. Split Span Experiment (cont): Results: Condition 1: 65% correct Condition 2: 20% correct 10 Further tests of Broadbent’s model 1) Moray’s (1959) & Cherry’s (1953) shadowing experiments a)  Demonstration of the “cocktail party” phenomenon b)  Information not retained from unshadowed ear any of the words spoken any numbers spoken c)  Information retained from the unshadowed ear male vs. female voice speech vs. noise But, participant’s name was detected by 33% of participants 11 Further tests of Broadbent’s model 2. cocktail party and working memory (WM) capacity Conway et al (2001) Detection of name Low WM 65% High WM 20% Thus, attention is related to capacity. Low WM capacity associated with ADHD, providing a model for why ADHD have trouble staying on task. 12 Further tests of Broadbent’s model 3. Counting Voices at a “cocktail party.” (Kawashima & Sato, 2015) Proportion of correct responses as a function of sample length (seconds). Error bars show 95 % CI. 13 3. Voice familiarity and the cocktail party Johnsrude et al. (2013) – spouses voice Fig. 2. Percentage of correct responses as a function of targecondition.r ratio and Johnsrude I S et al. Psychological Science 2013;0956797613482467 Copyright © by Association for Psychological Science 14 Summary evaluation of Broadbent’s Model What he got right 1. We are limited in the number of things we can attend to. 2. Salient physical features can direct attention What he got wrong 1. Meaningful content can direct attention 2. Attention is related to memory capacity 3. Familiarity influences stimulus selection 15 IV. Treisman’s Attenuation Model A. Properties: 1) Early selection 2) Selection (attenuation) is based on physical properties of the stimulus (e.g., pitch, loudness, etc...). 3) Attention is directed toward information that reaches a threshold of recognition. 4) Several inputs can be processed at a time. 16 IV. Treisman’s Attenuation Model B. Diagram of Mental Dictionary High "green" the model: "table" Thresholds "chocolate" "fire" "help" Low your name Subjective Loudness Attenuator Physical Selection (pitch, loudness, etc.) MessagedInput 17 Thresholds of Recognition High Frequency Words Low Frequency Words (low thresholds) (high thresholds) e_fo_t d_r_ss s_ro_g s_e_e h_r_e h_r_e 18 IV. Treisman’s Model (cont) Supporting Evidence (Treisman, 1960) Ear # 1 The body was buried on Moll Legg Island beside the ahead listen arm somebody North Carolina. Ear # 2 We point veiled their many wife he tussles last other grave and a cross put at its head. female/male 19 V. Deutsch-Norman Model (Deutsch & Deutsch, 1963; Norman, 1968) A. Properties: 1) Late selection: i.e., all stimuli are processed to stimulus recognition. 2) Selection (pertinence) is based on the importance of the recognized item. 3) Memory processes (e.g., rehearsal) are devoted to selected inputs. 20 V. Norman’s Model B. Diagram of the model: 21 c. Real life nature of the issue: F A 18 Hornet An F/A-18C taking off from USS Kitty Hawk 22 23 MACDONNELL DOUGLAS F A-18 HORNET: FLIGHT MANUAL 2 24 25 VI. Resolution A. Treisman & Geffen (1967) Task 1: shadow message in one ear. Task 2: subjects asked to tap pencil when they heard the target word “green.” Results: tapping to “green” in shadowed ear: 87% tapping to “green” in the other8%ar: 26 VIII. Resource Allocation Capacity Theories of Attention A. Dual task performance: simple multiplication tapping 27 VII. Resource Allocation Models: B. Diagram of a Capacity theory, based on Kahneman, 1973. 28 c. Automatic vs. controlled processes.  (Shiffrin & Schneider, 1977) Automatic Processes Controlled Processes Do not require attentionalRequire resources Occur without intention Require conscious intention Well practiced responsesouNot well practicedes Fast Slow Examples: freeway driving driving in an unfamiliar city recognition of frequent worecognition of rare words 29 Example of automatic processing Stroop (1935) effect 30 Stroop Continued Blue Red Yellow Green Green Yellow Red Blue Green Green Blue Red 31 D. Resource Allocation: Inattentional Blindness Demonstration: Simons and Chabris (1999): Detection of Unexpected Event Easy 64 % (counting passes by one team) Hard 45 % (counting passes by both teams) Inattentional blindness related to resource allocation. The Invisible Gorilla Strikes 32 Again Drew et al. (2013) Radiologist viewing lung CT scans for nodules (small light circles) 20 out of 24 failed to report seeing the gorilla! 33 Automatic vs. Controlled processes (cont) Klapp, Boches, Trabert, and Logan (1991) Dual task performance: 1) alphabet arithmetic InitBal LetAdde2, 3, 4 ResponD, E, F N 2, 3, 4 P, Q, R 2) month saying (January, February, March, April ...) 34 Klapp, Boches, Trabert, and Logan (1991)  results 2400 Pretest 2200 Posttest s (2000 T1800 1600 n1400 ei R1200 1000 2 3 4 Addend 35 D. Resource Allocation: Cell Phones Cell phone use may be a controlled process, requiring attention, leading to a reduction in resources to devote to driving. Many states are passing laws limiting cell phone use while driving. 36 Simple RT while talking An example of slowed reaction time in a divided attention task: reactiontime/index.php 37 Cell Phones (cont) Field Studies (e.g., Redelmeier & Tibshirani (1997) -cell phone use associated with a 4-fold increase in accidents -no reduction in accidents for those who used hands-free phones. 38 Cell Phones (cont) Strayer & Johnston (2001) Simulated driving study Dual Tasks: 1) Simulated driving: a) use a joystick and a computer to keep the cursor aligned with a moving target. b) press a “stop” button when the cursor turned red. 2) Distraction: (3 conditions) a) converse with a confederate on hand held phone b) converse with a hands free phone c) listen to a radio broadcast of their choice 39 Results: 1.  No difference in results in the hand-held versus the hands-free conditions. 40 Results: 2. Cell Phone use increased the likelihood of “missing” the “stop” signal. 41 Results: 3. Cell Phone use slowed reaction time to the “stop” signal. 42 Strayer & Johnston (2003) Testing driving in a simulator (Ford Crown Victoria): 43 Strayer & Johnston (2003) cont. Exp. 1: tested ability of cell phone users to respond to a vehicle braking in front of them. 40 participants drove 40 miles: control: not talking on cell phones exp: talking on “hands-free” phones In heavy traffic, 3 cell phone users rear-ended the vehicle in front of them. None of them did so in the control condition. 44 Driving Impairs Talking Becic et al (2010) demonstrated a decline in the accuracy of storytelling and memory for stories told during dual task performance. -driving simulator -listened to, and retold stories either while driving or while “parked” 45 Becic et al (2010) results: 46 IX. Conclusion on Attention & Resource Allocation 1) Partial selection occurs early in the information processing stream. 2) Selection is not the result of action of a simple physical filter. 3) The selection process is sensitive to the past experiences (thresholds) of the person and the context of the recognition task. 4) Performance of multiple tasks is a complex process of allocating limited resources and performance of some operations that are automatic and thus do not require resources. 1 Immediate Memory I. Context II.  History (changing views of immediate memory) III. Proposed Properties of Immediate Memory A.  Capacity B.  Coding C.  Forgetting D.  Retrieval 2 Context Immediate Memory refers to the general idea of a memory system dedicated to the storage of the recent past. It includes ideas such as: Short-term storage (STS) Short-term memory (STM) Working memory 3 I. Context The Atkinson and Shiffrin Model Sensory Short- Long- Input Store Term Term Store Store Control Processes rehearsal coding retrieval strategies! Response Output Page 1 4 II. History William James (1890, pp. 646-647) primary memory (immediate) vs. secondary memory (long-term) “An object which is recollected, in the proper sense of that term, is one which has been absent from consciousness altogether, and now revives anew. It is brought back, recalled, fished up, so to speak, from a reservoir in which, with countless other objects, it lay buried and lost from view. But an object of primary memory is not thus brought back; it never was lost; its date was never cut off in consciousness from that of the immediately present moment. In fact it comes to us as belonging to the rearward portion of the present space of time, and not to the genuine past.” 5 II. History (cont.) Freud (1856-1939) Hierarchical architecture of human consciousness: conscious mind preconscious unconscious mind The “magic slate” as a metaphor for memory (Note on the Mystic Writing Pad, 1925) 6 II. History (cont) Atkinson & Shiffrin (1968) Short-term storage buffer model Rehearsal Buffer Long-Term . . . . . . . Store n e S S S S Et ne S Lost from STS Page 2 7 II. History (cont) Buffer as a “push down stack” Input Lost Buffer 8 II. History (cont) Working Memory (Baddeley, 1986) Central Executive (limited capacity) Phonological Loop phonological store Visuo-spatial Sketchpad articulatory control (visual imagery) (short-term buffer) 9 Baddeley (2000) Working Memory Central Executive (limited capacity) Phonological Loop Visuo-spatial phonological store Episodic Buffer articulatory control (multimodal code) Sketchpad (visual imagery) Language Episodic Visual Long Term Memory Semantics Page 3 10 II. History (cont) Cowan (1988) Embedded Process model of Working Memory Central Executive Sensory Store Attention Active Memory Long-Term Store 11 Three component framework of working memory (Oberauer, 2006, 2009) 1. Nodes activated in LTM 2. A small number (4) of items temporarily bound to a mental space. 3. A single focus of attention III. Proposed Properties of Immediate 12 Memory A.  Limited Capacity 1)  digit span task 2)  Miller (1956) The magical number 7 +/- 2 digit span tasks categorization tasks (how many tones, etc) judgments task Page 4 13 A. Limited Capacity (cont) 3) Chunking and Memory Span (Ericsson, 1980) male student practiced digit span task 1 hour of practice a day, 3-5 days a week Total of 20 months practice (230 hours) 14 Ericsson (1980) results 80 70 Digit span increased 60 50 from 7 to 80 40 Digit 30 Span 20 10 0 5 10 15 20 25 30 35 40 Practice (5 day blocks) Conclusion: Exceptional memories: Made not born (Ericsson, 2003) Expert Memory (from an interview with 15 memory champion Nelson Dellis, 2012) Here's how Dellis tackles numbers: 12468146036059283589624433074 ... He'll memorize seven digits at a time, using the "person-action- object" method. Start by splitting the seven digits: 124-68-14 Ahead of time, he's stored 999 people in his head, each associated with an action and an object. In Dellis' mind, 124 is Michael Jordan doing something with a basketball; 68 is Stephen Hawking, whose action is rolling in a wheelchair; and 14 is a hockey player whose object is a hockey stick. So, 124-68-14 is Michael Jordan rolling in a wheelchair while swinging a hockey stick Page 5 16 A. Limited Capacity (continued) 4) The Magical Number 4 (Cowan, 2000, Oberauer, 2006) Compound STM limit (7 +/- 2) (measured by digit span) includes contributions from: Sensory Storage, LTM (chunking) Pure STM capacity limit (4 +/- 1) measured under conditions that prevent contributions from other sources. e.g., Sperlings whole report, measures of chunk size, measures with un-rehearsable material (long phrases) 17 A. Limited Capacity (continued) 5. Visual Working Memory Capacity Focal Cross Stimulus Set Visual Mask Test Set + “The capacity of visual working memory is limited to no more than four items (Švegar, 2011, p. 48).” “Visual working memory capacity is limited on at least three dimensions: the number of objects, the number of features per object, and the precision of memory for each feature”(Oberauer & Eichenberger, 2013, p. 1212).” 18 A. Limited Capacity (continued) 6. Time limit (rather than a number of items limit) For Example, Baddeley’s: Phonological loop •  The capacity limit is apparent because information in the loop decays (in a matter of seconds). •  It must be refreshed through rehearsal •  It is impossible to rehearse a lengthy series of items before decay creates a loss of information. Page 6 19 Memory Span and Word Length Baddeley, Thomson, & Buchanan (1975) List 1 List 2 lice abundant mink approval pain foreigner pint paragraph rose sympathy Lists of short words are easier to remember than lists of long words. Baddeley’s Interpretation: Greater Memory span for shorter words because shorter words are easier to rehearse before they decay. 20 Is working memory limited by time? Jalbert, Neath, Bireta, & Surprenant (2011) Word-length effect disappears when you control for orthographic neighborhood size (short words with more similar neighbors are easy to remember, perhaps because similar words help you reconstruct other list items.). Memory for long phrases (a demonstration). Conclusion – Working memory is not time limited. III. Proposes Properties of Immediate 21 Memory (cont) B. Forgetting from Immediate Memory Two hypotheses: decay: information fades with time interference: new information interferes with old Waugh & Norman (1965) probe-digit tas27485667 beep 5 ? 43259412567 beep 9 ? two rates of presentation: 1/sec vs. 4/sec Page 7 22 C. Forgetting from Immediate Memory (cont) Waugh & Norman’s Results 1.2 1 1 per sec 4 per sec 0.8 Probability of 0.6 Recall 0.4 0.2 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Number of Interfering Items 23 Decay or Interference? Lewandowsky, Duncan, & Brown (2004) •  Participants performed a serial recall task on short list of letters (H, J, M, Q, R,V) •  Recall was paced to create different retention intervals: fast: 400 msec/item (6x400 = 2.4sec) med: 800 msec/item (6x800 = 4.8 sec) slow: 1600 msec/item (6x1600 = 9.6 sec) •  During recall, participants performed an (repeated the word “super’).k to prevent rehearsal 24 Decay or Interference? Predictions from two models: Decay: Interference: Page 8 25 Lewandowsky et al (2004) results: Which model is supported? III. Proposes Properties of Immediate 26 Memory (cont) C. Coding in STS 1) phonological coding Conrad (1964) Experiment 1 Presented letters aurally, immediately after each letter, participants were asked to write down the letter. Experiment 2 Presented 6 letters visually, then participants were asked to write the list (memory span task). Results: Correlation between errors made on the listening and memory tasks was r = .64. 27 Confusion matrix for auditory task Stimulus Letter B C P T V F M N S X B - 171 75 84 168 2 11 10 2 2 C 32 - 35 42 20 4 4 5 2 5 P 162 350 - 505 91 11 31 23 5 5 143 232 281 - 50 14 12 11 8 5 r T e V 122 61 34 22 - 1 8 11 1 0 e R F 6 4 2 4 3 - 13 8 386 238 10 14 2 3 4 22 - 334 21 9 M N 13 21 6 9 20 32 512 - 38 14 S 2 18 2 7 3 488 23 11 - 391 1 6 2 2 1 245 2 1 184 - X Page 9 28 Confusion matrix for Short-term memory task - visual presentation. Stimulus Letter B C P T V F M N S X B - 18 62 5 83 12 9 3 2 0 C 13 - 27 18 55 15 3 12 35 7 P 102 18 - 24 40 15 8 8 7 7 T 30 46 79 - 38 18 14 14 8 10 L V 56 32 30 14 - 21 15 11 11 5 s R F 6 8 14 5 31 - 12 13 131 16 M 12 6 8 5 20 16 - 146 15 5 N 11 7 5 1 19 28 167 - 24 5 S 7 21 11 2 9 37 4 12 - 16 X 3 7 2 2 11 30 10 11 59 - 29 B. Coding in Immediate Memory (cont) 1) phonological coding (cont) b) Schweickert, et al. (1990) GZDBPBV MJYFHRK Phonologically similar list are more difficult to remember. 30 B. Coding in Immediate Memory (cont) 2) Visual Coding Shepard’s Mental Rotation Task Shepard & Metzler (1971) Page 10 31 Shepard & Metzler (1971) results Rotation time related to distance rotated Demonstrates visual coding in working memory 32 3) Phonological and Spatial Coding in Working Memory (PET research) Smith & Jonides (1977) pet scans of subjects performing working memory tasks. L M Verbal + + + r Memory R D 500 msec 200 msec 3000 msec 1500 msec Spatial Memory + + + + 33 Smith & Jonides (1977) cont. Verbal -control Phonological Store: posterior parietal (left lateralized) Phonological Rehearsal: Broca’s area, premotor and supplementary motor area (left lateralized) Page 11 34 Smith & Jonides (1977) cont. Visual -control Spatial Store: Sposterior parietal (right lateralized)l (right lateralized) Spatial Rehearsal: premotor area Sp(right lateralized) premotor area (right lateralized) 35 III. Proposes Properties of Immediate Memory (cont) D. Retrieval from STS (Sternberg, 1966) Task: list 1,9,4,3 (size = 4) test 4 (positive) or 2 (negative) list 2, 7, 1, 4, 9, 0 (size=6) test 9 (positive) or 3 (negative) D. Retrieval from Immediate Memory 36 (Sternberg, 1966, cont) Questions: 1) Is the search serial or parallel? 2) Is it terminating or exhaustive? 3) What is searched (coding)? Page 12 37 Serial or Parallel Search? Serial Search STS Buffer 4 1 9 4 3 “yes” Prediction: reaction time should increase with list length. 38 Serial or Parallel Search? Parallel Search STS Buffer 1 9 “yes” 4 4 3 Prediction: Reaction time should stay the same across list length 39 Serial or Parallel Search? Results: 600 Positive Mean Reaction Time 500 (msec) 400 1 2 3 4 5 6 Memory Set Size Conclusion: Search is serial Page 13 40 Is the search exhaustive or self terminating? STS Buffer 4 1 9 4 3 “yes” STS Buffer 4 1 9 4 3 “yes” Prediction: If it is terminating, RT on yes trials should be faster than RT on no trials 41 Is the search exhaustive or self terminating? Results: Positive 600 Negative Reaction Time 500 (msec) 400 1 2 3 4 5 6 Memory Set Size Conclusion: Search is exhaustive 42 What is searched (coding)? intact STS Buffer 4 1 9 4 3 “yes” STS Buffer degraded 4 1 9 4 3 “yes”


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