PSCH 352 Unit 3 Notes PDF

PSCH 352 Unit 3 Notes Unit Three Notes Conceptual Knowledge ❖ What is a concept? Concept: the mental representation of a class or individual that gives it meaning The “concept” of a cat ❖ Why are concepts...

PSCH 352 Unit 3 Notes Unit Three Notes Conceptual Knowledge ❖ What is a concept? Concept: the mental representation of a class or individual that gives it meaning The “concept” of a cat ❖ Why are concepts important? Conceptual knowledge allows us to recognize objects and events and to make inferences about their properties What is this item we’ve encountered? What makes it a pumpkin? How do we tell apart from other things? What do we do with it? Is it safe? Can we eat it? ❖ What is a category? Concept: the mental representation of a class or individual that gives it meaning Category: group of objects or entities that have something in common - defined by the concept Include all possible examples of a particular concept The category of a cat includes Categorization: the process by which things are placed in categories PSCH 352 Unit 3 Notes ❖ Why are categories important? Allow for generalization across members of a category Allow us to make predictions about new objects based on previous experience with related objects Allow us to communicate our unique experiences to others “pointers to knowledge” (Yamauchi & Markman, 2000) ❖ Categorization theories Definitional theories We decide whether something is a member of a category by determining whether the object meets the definition of the category Categories have a clear set of defining features Necessary: an object must have the defining features to be a category member Sufficient: an object has all of the defining features, then it is a category member Prediction: all members of a category should be equally easy to identify Determine what features the new object has Compare them to the defining features of each category Pick the category that has all its defining features satisfied Limitations of this view Defining features don’t exist for all categories (e.g., chairs, games, furniture Possible solution = family resemblance (Ludwig Wittgenstein, 1953) Category members can resemble each other in different ways There is no set of characteristics that all category members must share Allows for some variation within a category ◆ For example: What defines a game? practiced by children engaged in for fun has rules involves multiple players Is competitive Prototype theories Category membership decided by comparing the object to a prototype that represents the category Prototype: a summary or average of all experienced members of a category ◆ Captures the family resemblance of category members – is like a “typical” member PSCH 352 Unit 3 Notes ◆ Does not have to be real exemplar from the category ◆ Objects are categorized by finding their most similar prototype Three real birds– a sparrow, a robin, and a blue jay–and a “Prototype” bird that is the average representation of the category “birds” ◆ Eleanor Rosch (1975a) Demonstrated that typicality is an important factor in categorization People consistently rate typical category members as being better category examples Connections between prototypicality and behavior Mervis and coworkers (1976) Smith and coworkers (1974) PSCH 352 Unit 3 Notes Smith and coworkers (1974) determined how fast people could answer questions about an object’s category ◆ Sentence verification technique: Participants answer “yes” (for true) or “no” (if false) to presented sentences “An apple is a fruit” “A pomegranate is a fruit ◆ ◆ Results: People were faster to verify sentences that include typical members (an apple is a fruit) ◆ Called the typicality effect Rosch (1975b) Eleanor Rosch (1975b) asked whether more prototypical category members are more easily primed than non-prototypical members Methods ◆ A color name was presented before participants saw two colors ◆ Participants then had to identify whether the two colors were identical or different ◆ Side-by-side colors were paired in three different ways Results: After priming, participants faster to identify typical colors as being the same compared to atypical colors Conclusions: Category labels prime typical members more than atypical members Solso and MacCarthy (1981) PSCH 352 Unit 3 Notes Solso and MacCarthy (1981) tested whether we generate prototypes while learning about categories Methods ◆ Shown a series of faces which were based on a non-presented prototype ◆ Then given a recognition test containing: Old faces New faces The prototype Results: Recognition was highest for the prototypes even though they were never presented during the study phase! Conclusions: We spontaneously create prototypes Ponser and Keele (1968) we also generate prototypes while learning about the abstract categories Exemplar theories Categories are not represented by a single prototype; instead, they are represented by individual objects in a category that a person has encountered in the past (called exemplars) Example: sparrows, robins, and bluejays as exemplars for the category “birds” PSCH 352 Unit 3 Notes Categorization is based on how similar the object is to all exemplars of a category Benefits: Can explain many of the same phenomenon as prototype theories and are better at dealing with outliers (penguin) and variable categories (games) Disadvantages: efficient due to higher storage requirements We may use both prototype and exemplar approaches → → → May average exemplars into a prototype early in learning, with some of the exemplar information becoming stronger later in learning! Theories and rule All categorization judgments are not based on similarities Gelman and Markman (1986) asked children to rate the similarity between pairs of objects Children rated the bat and blackbird as being more similar than the flamingo and blackbird Next, asked “if a flamingo mashes up food to feed its babies and a bat feeds its babies milk, what does a blackbird do?” Children chose “mashes up food”, even though they thought the blackbird was more similar to the bat All categorization judgments are not based on similarities We also use theories and rules about the natural world Children in the Gelmen study could use their biological theories to answer questions For example: Even though blackbirds look more like bats, they work differently This implies that we can treat some features, or combination of features, as being necessary for group membership Allen and Brooks (1991) Had two groups of participants learn about “builders” and “diggers” PSCH 352 Unit 3 Notes Rule group: builders have at least 2 of Angular bodies Spots Long legs Memory group: memorize the examples Subjects were given new examples to categorize at test Easy: looked similar to previous examples of the same category Hard: looked dissimilar to previous examples of the same category, but had the required features Results Memory condition: wrong answer to hard examples 86% of the time Rule condition: wrong answer hard examples only 45% of the time Conclusion: Demonstrates we can use different strategies – such as rules – to form categories ❖ Organization of categories Hierarchical organization Larger, more general categories are divided into smaller, more specific categories Creates a number of levels of categories PSCH 352 Unit 3 Notes Study 1: Rosch & coworkers (1976a) Study 2: Rosch & coworkers (1976b) ❖ But knowledge affects things! Rosch’s work showed “basic” category level reflects college undergraduate students’ everyday experience Tanaka & Taylor (1991) study with experts vs. non-experts Method: Asked bird experts and non-experts to name pictures of objects Results Experts responded by providing specific-level category information for the birds (“robin”) Non-experts provided basic-level category information (“bird”) The level that is “special” – that people tend to focus on – is not the same for everyone! PSCH 352 Unit 3 Notes Semantic Network Models of Categorization - Cxognitive framework for how we represent and organize concepts in the mind based on semantic relationships. - It is a network-like structure that connects concepts to each other. - Supports efficient retrieval and categorization of information. Collin’s and Quillian (1969) - Proposed one of the first semantic network models for how concepts and properties are associated in the mind. PSCH 352 Unit 3 Notes Predictions made 1) Time it takes to retrieve information about a concept should be determined by distance that must be traveled through the network. - Tested using sentence verification technique (yes or no statements) - ”a canary is an animal” —> travels in 2 links - ”a canary is a bird” —> travels in 1 link - Statements that required farther travel from canary resulted in longer reaction time 2) Meyer and Schvaneveldt (1971) Theory - Concepts receiving spreading activation (activity that spreads out along any link connected to an activated node) should be retrieved more easily from memory PSCH 352 Unit 3 Notes - Used the lexical decision task (Participants asked to read pairs of words, some were real words and some were nonwords) - They reported on whether each pair was made up of two real words (“yes”) or not (“no”) as quickly as possible - Measured their response times - FASTER REACTION TIMES WITH 2 ASSOCIATED WORDS - Could be because retrieving one word from memory triggers spread of activation to other nearby locations in the network Criticisms of Collin’s and Quillan Semantic Network Model 1) Can’t explain the typicality effects - Faster reaction times for statements about more typical category members 2) Cognitive economy? - Evidence that people store some shared properties of concepts at lower-level nodes 3) Some sentence-verification results are problematic for the model - “Pig is an animal” verified more quickly than “a pig is a mammal” Connectionist network models of categorization Connectionist network models Originated in response to: - Criticism of semantic networks - Advances in understanding how information is represented in the brain Can explain a lot of experimental / real-world findings - How concepts are learned - How damage to the brain affects our knowledge about concepts What are connectionist network models? PSCH 352 Unit 3 Notes Computer models representing cognitive processes - We’re talking about ones that represent “concepts” Also called parallel distributed processing (PDP) models b/c they propose concepts are represented by activity that is distributed across a network Circles = units Concepts and their properties are represented by the pattern of activity across these units Lines = connections that transfer information between units Units are activated by: - Stimuli from the environment [input units] - Signals received from other units [hidden and output units] Connection weight: Determines how signals sent from one unit influence the activity of the next unit - Can increase the next unit’s activity (increase weight) - Can decrease the next unit’s activity (decrease weight) Activation of units in a network depends on: - The signal that originates in the input units - The connection weights throughout the network Representation of a stimulus = the pattern of activity that’s distributed across all units PSCH 352 Unit 3 Notes How are connectionist networks different? - Property nodes might be activated that have nothing to do with the concept. - For things to work, connection weights must be adjusted so that activating a particular concept and relation unit results in only the correct property units. How does this happen? - Adjustment of weights achieved by a learning process - Mistakes in the property units (e.g., a canary has petals) cause error signals that are sent backward through the network via back propagation - Error signals provide information on how connection weights need to be adjusted so that the correct property units are activated (e.g., a canary has feathers) - Process repeats until the error signal = zero! PSCH 352 Unit 3 Notes Support for Connectionist Network Models - Explains graceful degradation: Network operation is not totally disrupted by damage - Explains generalization of learning: Training system recognizes properties of one concept provides information about related concepts - But there are still limits to what it can explain - Let’s look at additional research focusing on how concepts may be - represented in the brain! Representation of Concepts in the brain 1. Sensory-Functional Hypothesis Proposes different brain areas are specialized to process information about sensory versus function features Support: Some patients with category-specific memory impairments May be because: - living things → sensory properties - artifacts → functions But subsequent research suggests brain damage effects can’t be explained by a simple dissociation between sensory and function PSCH 352 Unit 3 Notes 2. The Multiple-Factor Approach Goes beyond two factors for sensory and function - Animals → motion and color and sounds they create - Artifacts → actions (using, interacting) - Musical instruments → overlap with both animals (sounds they create) and artifacts (how you use / play them) More factors guide how concepts are divided into categories 3. Semantic Category Approach (Hugh 2016) Proposes there are specific neural circuits in the brain for specific categories Also emphasizes that the brain’s response to items from a particular category is distributed across several different cortical areas - Example: Identifying faces may depend on activation in the face area of the temporal lobe + areas that respond to emotions, facial expressions, facial attractiveness, etc 4. Embodied Approach (Hauk 2004) Proposes our knowledge of concepts is based on reactivation of sensory + motor processes that occur when we interact with the object Link between perception + motor responses is central (think about mirror neurons) Support: - Doing actions and reading words about the same body part activate a similar part of the brain (semantic somatotopy) Semantic Dementia Insight Causes a general loss of information for all concepts Patients tend to be equally deficient in identifying living things and artifacts Characterized by general damage to the anterior temporal lobe (ATL) PSCH 352 Unit 3 Notes Hub and spoke model of semantic knowledge Inspired by the generalized deficits in individuals with semantic dementia Areas of the brain associated with specific functions (the “spokes”) are connected to the ATL The ATL (the “hub”) integrates the information from these areas Supporting evidence - Damage to a “spoke” brain area can cause deficits in a certain area - Damage to the “hub” brain area - the ATL – causes overall deficits Problem Solving and Creativity ❖ Creativity Set of mental processes that support the generation of novel and useful ideas Alternative Uses Task (Guilford, 1956) You will be told a common object and then asked to think of as many different uses for the object as you can that are (1) different from the way the object is normally used and (2) different from each other. For example, the common use for a newspaper is for reading, but it could also be used for swatting flies, to line drawers, to make a paper hat, and so on. PSCH 352 Unit 3 Notes ❖ Alternative Uses Task + Divergent Thinking The alternative uses task measure “divergent thinking” Many examples and definitions of creativity focus on divergent thinking Divergent thinking is open-ended thinking that involves coming up with a large number of potential “solutions” ❖ Problem An obstacle between a present state and a goal Not immediately obvious how to get around the obstacle Difficult to solve ❖ What is Gestalt Psychology? A school of psychology that emerged in the early 1900’s Suggests the mind perceives and interprets sensory information as organized wholes instead of a sum of individual parts “Gestalt” roughly translates to “configuration” or “pattern” in German ❖ The Gestalt approach to problem solving 1. Representing a problem in the mind Problem representations are models of the situation as experienced by the person They differ from person to person 2. Restructuring Analyzing the problem according to different dimensions or “changing from one representation to another” Can make a problem more difficult or much easier to solve 3. The idea of insight A sudden comprehension, realization, or problem solution that involves a reorganization of a person’s mental representation of a stimulus, situation, or event to yield an interpretation that was not initially obvious Task that require insight usually require something new and non-obvious to be done Usually associated with an “AHA-experience”, where the solution pops up all of a sudden PSCH 352 Unit 3 Notes Experiment on insight vs. non-insight problems Janet Metcalfe & Davide Wiebe (1987) ◆ Hypothesis: there should be a difference in how participants feel they are nearing a solution between insight vs. non-insight problems ◆ Method Completed insight problems (triangle and chain problems) Completed non-insight problems (algebra problems) Judge distance from the solution ranging from cold (1 - not close) to hot (7 - very close) every 15s ◆ 4. Functional fixedness and mental set When trying to solve a problem, we focus on familiar functions or uses of an object… we get “fixed” on the functions for which we’re most familiar! Out preconceptions about the uses of objects can work against solving a problem You likely delt with some “functional fixedness” when doing the alternative uses task during our last discussion Mental set: preconceived notions about how to approach a problem, which is determined by your experience of what has worked in the past PSCH 352 Unit 3 Notes The Gestalt idea that problem solving depends on how the problem is represented in the mind a starting point for the information processing approach to problem solving ❖ Problem solving as a “search” is part of our language “Searching for a way to reach a goal” “Getting around roadblocks” “Hitting a dead end” “Approaching a problem from a different angle” ❖ The information-processing Approach Alan Newell and Herbert Simon describe a computer program they had created that was designed to simulate human problem solving Marked the beginning of research movement toward describing problem solving as a process that involves “search” Search: A process that happens between the posing of the problem and its solution ❖ Newell and Simon’s approach Suggested solving problems consists of a sequence of choices of steps that takes you across various problem states Initial state: conditions at the beginning of the problem Intermediate state(s): states between the initial and goal state Goal state: the solution of the problem Operators: actions that take the problem from one state to another Solving the Tower of Hanoi problem according to the the information-processing PSCH 352 Unit 3 Notes A key contribution of Newwll and Simon’s approach Provided a way to specify the possible pathways from the initial to goal states But there is more to problem solving than specifying the problem space and subgoals ❖ Importance of how a problem is stated How a problem is stated can affect its difficulty Kaplan & Simon (1990): the mutilated checkerboard problem Asked : If we eliminate two corners of a checkerboard, can we cover the remaining checkerboard square with 31 dominos? The solution requires understanding the principle that each domino covers two squares and that these squares must be of different colors, so removing the two corner squares with the same color makes it impossible to solve the problem PSCH 352 Unit 3 Notes ❖ The possible use of analogies When faced with a new problem, it is sometimes helpful to consider whether another problem you have solved before is similar to it Ask yourself: can I apply the same methods to solving this problem? This technique of using an analogy is called analogical problem solving Glick and Holyoak Propsed that analogical problem solving involves three steps 1. Noticing an analogous relationship (considered most difficult step!) 2. Mapping the correspondence between the source problem (the Russian Marriage problem) & the target problem (the mutilated checkerboard problem) 3. Applying that mapping to come up with a parallel solution to the target problem ❖ Experts “A person who, by devoting a large amount of time to learning about a field and practicing and applying that learning, has become acknowledged as being extremely knowledgeable or skilled in that field.” Solve problems in their field more quickly and with a higher success rate than beginners Why? William Chase & Herbart Simon (1973): Examined how fast people could reproduce the positions of pieces on a chessboard after looking at it for 5 seconds Compared Chess masters with > 10,000 hours of experience Beginners with male librarians If Robert was randomly chosen from population, it was much more likely he a farmer We tend to use base rate information if that is all that is available We tend to disregard base rate information if descriptive information is also provided Example In a group of 100 people, there are 70 lawyers and 30 engineers. What is the chance that if we pick one person from the group at random that the person will be an engineer? Estimations change if we add: The person randomly picked is Jack, a 45-year-old man. He is married and has four children. He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies, which include home carpentry, sailing, and mathematical puzzles. ❖ Other potential sources of judgment errors 1. Conjunction rule Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and she also participated in antinuclear demonstrations. Which of the following alternatives is more probable? A) Linda is a bank teller B) Linda is a bank teller and is active in the feminist movement PSCH 352 Unit 3 Notes The probability of two events (“A” + “B”) happening cannot be greater than that of either one of them happening alone Errors occur when we violet this rule → assign a higher probability to the conjunction (both “A” + “B” happening) 2. Law of large numbers Simulated coin tossing experiments + law of larger numbers The larger the number of individuals drawn from a population, the more representative the group will be of that population Errors occur when we assume a number of individuals accurately represent the entire population 3. Confirmation bias Lord and coworkers (1979) had those in favor of capital punishment and those against it read the same article Those in favor found the article convincing Those against found the article unconvincing Selectively looking for information that agrees with a hypothesis and overlooking information that goes against it Errors occur when we narrowly focus on confirming information and ignore opposing information 4. Backfire effect When your support for certain viewpoint becomes stronger when presented with facts that oppose it Errors occur when we hold onto our beliefs in the face of contradictory evidence PSCH 352 Unit 3 Notes ❖ Deductive reasoning Determining whether a conclusion logically follows from premises In other words: you start with broad principles and make logical predictions about specific cases The conclusions reached can be (but are not always) definitely true ❖ Aristotle The father of deductive reasoning → introduced the syllogism Categorical syllogism example Premise 1: All birds are animals Premise 2: All animals eat food Conclusion: Therefore, all birds eat food ❖ Syllogism The basic form of deductive reasoning Includes 2 broad statement (premises) Followers by a 3rd conclusion statement Can be evaluated in two ways Validity: whether the conclusion logically follows from the premises Truth: whether the conclusion is consistent with the real world ❖ Syllogism and belief We sometimes incorrectly think syllogism are valid because the conclusion “believable” ❖ Mental model of deductive reasoning (Philip Johnson-Larid (1999) 1. People create an imagined representation of the situation for a reasoning problem 2. They generate a tentative conclusion based on the model and then look for exceptions that might falsify it 3. If they find an exceptions, they modify the model 4. If they can find no more exceptions and their current model matches the conclusion, they can conclude the syllogism is valid PSCH 352 Unit 3 Notes ❖ Is the mental model of deductive reasoning correct? Supported by results from multiple experiments One of the easiest models to apply and explain But there are other proposals for how we asses validity in syllogisms Difficult to know for sure how we do this! ❖ Decision making How we make judgements that involve choices between different courses of action What school to attend? Which basketball player should we draft? Which grocery store should we buy the turkey at? ❖ Expected Utility Theory Early theory on how we make decisions If we have all of the relevant information, we will make a decision that results in the maximum expected “utility” Utility = outcomes that achieve a person’s goals (e.g. money) But we often ignore probabilities when making decisions Jelly Bean Study by Denes-Raj & Epstein (1994) PSCH 352 Unit 3 Notes Participants offered the chance to earn $ every time they drew a red jelly bean from a bowl containing red and white jelly beans When given a choice, many participants drew from the larger bowl, even though the probabilities were against them ❖ Emotions influence decision making Anxious people avoid making decisions that might lead to large negative consequences → “Risk avoidance” Optimistic people are more likely to ignore negative information → base decisions on incomplete information Study by Kermer and coworkers (2006) Gave participants $5 Based on a coin flip they would either gain an additional $5 or lose $3 Had them predict how their happiness would change if they won or lost the coin toss Bad prediction of our emotions can hurt our decisions ❖ Kermer and Coworkers (2006) Some people were reluctant to take a bet when there was a 50% chance of winning $200 and a 50% chance of losing $100 Even though, in accordance with utility theory, this would be a good bet PSCH 352 Unit 3 Notes ❖ Incidental emotions Emotions we carry with us to the decision that have nothing to do with decision Person’s general disposition Something that happened earlier in the day General environment such as background music being played “Clouds Make Nerds Look Good” paper (Simonsohn, 2007;2009) Analysis of university admissions decisions Applicants’ academic attributes were more heavily weighted on cloudy vs sunny days Nonacdemic attributes won out on sunny days Prospective students visiting an academically highly-rated university were also more likely to enroll if they had visited the campus on a cloudy day ❖ Decisions are impacted by context Shai Danziger and coworkers (2011) Analyzed 1,000+ judicial rulings on parole requests made by prisoners to Israeli parole boards Results Chance of parole granted was 65% when judge heard the case just after meal break Dropped to near 0% when judge heard case just before break Example of extraneous factors in judicial decision Shen and coworkers (2010) Presented physicians with a hypothetical test case involving a possible candidate for a cesarean section Asked them to decide if they would “opt out” of the cesarean section under one of 3 possible context 1. Control: test case presented first 2. Serious previous cases: test case presented after 4 cases with serious complications that would usually call for cesarean section 3. Not serious previous cases: test case presented after 4 years fairly routine cases PSCH 352 Unit 3 Notes ❖ Decisions depend on how choices are presented Paul Slovic and coworkers (2000) Showed forensic psychologist + psychiatrist a case history of mental health patient, Mr. Jones Asked the likelihood he would commit a violent act within 6 months of discharge Group 1: “20 out of every 100 patients similar to Mr. Jones are estimated to commit an act of violence”’ 41% refused to discharge him Group 2: “Patients similar to Mr. Jones are estimated to have a 20 percent chance of committing an act of violence” 21% refused to discharge him The 1st may conjure images of 20 people being beaten up The 2nd, more abstract statement could be interpreted to mean there is only a small chance he’ll be violent Example 2: Organ donation decisions 85% of Americans approve of organ donation Only 28% percent have granted permission by signing a donor card In France and Belgium, the consent rate is > 99% Why the difference? US requires signing a donor card → “opt-in procedure” requires an active step France and Belgium use an “opt-out procedure” → everyone is potential organ donor unless he or she request not to be Status quo bias: tendency to do nothing when faced with the need to opt in Status quo bias in marketing Subscription service that auto-renews unless you cancel it Taking advantage of default behaviors Money-back guarantees and free trials without any obligation Reducing the perceived risk of loss and regret Internet providers charging customers for switches to an upgraded package Taking advantage of loss aversion PSCH 352 Unit 3 Notes Hope to persuade the customer to begin with the upgraded package Expensive packages become the status quo ❖ What underlies the status quo bias? Making decisions is hard!!! To reduce complexity, we sometimes resort to irrational mechanisms These often result in a preference for the current option or situation Several concepts that contribute to the status quo bias Loss aversion Regret avoidance Mere-exposure effect ❖ Neuroeconomics The study of how brain activation relates to decisions involving potential gains or losses Combines psychology, neuroscience, and economics research Example: Sanfey and coworkers (2003) Two participants played the ultimatum game Proposer + responder Proposer is given $10 and makes an offer to the responder as how they should split the money Responder can accept the offer (money is split accordingly) Responder can reject the offer (neither one gets any money) Game over once the responder makes their decision Participants played 20 separate games as responder Half with different human partners Half with a computer partner Offers were determined by the experimenters, with some being “fair” (evenly split) and some “unfair” (responder receives $1-3) All responders accepts an offer of $5, most accept the $3 offer, and half or more reject the $1 or $2 offers from a “human” PSCH 352 Unit 3 Notes More accepted “unfair” proposals from a computer People were angry because they felt the offers were unfair To always accept the prosper’s offer is the rational response Anterior insula: connected with negative emotional states including pain anger PFC: may help weighing the choices to determine which decision the best Perception ❖ Perception Experience resulting from stimulation of these sense Perception can change based on added information Involves a process similar to reasoning or problem solving Perceptions occur in conjunction with actions ❖ Human perceptual processes may be unique Attempts to create artificial forms of perception have had limited success, with problems that could not be solved ❖ The visual pathway PSCH 352 Unit 3 Notes Visual information travels from the eyes to the thalamus then to the primary visual cortex (V1) Neurons in V1 acts as feature detectors: responding to lines with specific orientations and in particular locations Hierarchical processing from V1 to the temporal and parietal lobes bind line features into complex shape ❖ Why can’t machines perceive like humans? 1. Inverse Projection Problem Must determine the object responsible for a specific image on the retina Each 2D retinal image could reflect infinitely distinct 3D stimuli Solution: Unconscious inference! 2. Objects can be hidden of blurred 3. Objects look different viewpoints 4. Scenes contain high-level information are more complex ❖ Two types of Information Environmental energy that stimulates the receptors Knowledge and expectations that observer brings to the situation Bottom-up processing (“stimulus driven”) Starts with the senses Incoming raw data Energy registering on receptors Top-down processing (“knowledge driven”) Starts with the brain PSCH 352 Unit 3 Notes Person’s knowledge, experience, and expectations Top-down processing impacts visual perception Top-down processing impacts language perception Language perception involves: ◆ Speech segmentation: ability to tell when one word ends and another begins Based on our individual experience with the language ◆ Transitional probabilities: knowing which sound will likely follow another in a word Saffran, Aslin, & Newport (1996) showed this true even of 8-months-olds ❖ Approaches to Understanding Perception Direct perception theories Bottom-up processing Perception come from stimuli in the environment Parts are identified and put together, and then recognition occurs Constructive perception theories Top-down processing People actively construct perceptions using information based on expectations ❖ Four Theoretical Viewpoints 1. Helmoltz’s Theory of Unconscious Inference Likelihood Principle: we perceive the object that is most likely to have caused the pattern of stimuli that we received Views perception as a form of problem solving! We unconsciously and automatically draw inferences that are based on our experience and basic principles of simplicity Allows for top-down biases on perception 2. The Gestalt Principles of Organization PSCH 352 Unit 3 Notes “Old” view–structuralism Perception involves adding up individual sensations “New” view–Gestalt principles The mind group patterns according to intrinsic laws of perception organization Perceiving whole patterns or structures rathe than just individual components Perceptions is determine by specific organizing principles, not just dark and light stimuli activating the retina Experience plays minor role compared to these intrinsic, “built in” principles → cam influence perception but is not the key driver Principle of good continuation ◆ Lines tend to be seen as following the smoothest path Points are assumed to be connected by smooth lines Principle of simplicity/ good figure (Law of Pragnanz) ◆ Every stimulus pattern is seen as being as simple as possible Principle of similarity ◆ Points which share features are grouped together 3. Regularities of the Environment Current views of perception note that people make use of regularities to help them perceive PSCH 352 Unit 3 Notes Physical regularities ◆ Common physical properties of the environment Oblique effect: We perceive vertical and horizontal more easily than other orientations ◆ Light-from-above assumption: Assume light comes from above b/c this is common in our environment ◆ Ames room - optical illusion Semantic regularities ◆ The characteristics associated with functions carried out in different types of scenes ◆ Scene schema: Knowledge of what a given scene ordinarily contains In the jewelry case as Macy’s, would you expect to see a plate of fish and chips or diamond rings? ◆ Stephen Palmer (1975) showed how environmental knowledge can influence perception PSCH 352 Unit 3 Notes 4. Bayesian inference The estimated probability of an outcome is influenced by two factors The prior which is our initial belief about the probability of an outcome The likelihood of a given outcome Scenario: Charles has a bad cough. What could be the cause? Mary has 3 guesses: cold, heartburn, or lung disease Prior: she initially believes a cold and heartburn are more frequent/likely Likelihood: Data indicate heartburn is less associated with coughing Conclusion: Her updated belief is that Charles’ cough is probably due to a cold ◆ ❖ Steeping Back to Compare Conceptions of Object Perception Bottom-up processing Gestalt principles Top-down processing Unconscious inference Environmental regularities Bayesian inference ❖ How does the brain navigate our complex visual world? Experience-dependent plasticity When neural responses are shaped by experience PSCH 352 Unit 3 Notes “Plastic” enough to adjust to an upside-down world? Interaction with action Picking up coffee mug Perception and Action: what and where What pathway: ◆ Determining the identity of an object ◆ Ventral pathway (lower part of the brain) Where pathway: ◆ Determining the location of an object ◆ Dorsal pathway (upper part of the brain) Perception and Action: Mirror Neurons PSCH 352 Unit 3 Notes Respond in the same way both performing and watching the action