Ch. 8: Categories and concepts - PowerPoint PPT Presentation

ch 8 categories and concepts n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Ch. 8: Categories and concepts PowerPoint Presentation
Download Presentation
Ch. 8: Categories and concepts

play fullscreen
1 / 72
Ch. 8: Categories and concepts
146 Views
Download Presentation
osman
Download Presentation

Ch. 8: Categories and concepts

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Ch. 8: Categories and concepts

  2. Concept and Knowledge • Topic: • How do we store and manipulate a concept in the brain?

  3. Concepts, beliefs and behavior

  4. Concept/belief and action • Mother Teresa • Timothy McVeigh (Oklahoma bomber) • Ted Kaczynski (the unabomber) • Osama bin Laden • Mahatma Gandhi • Nelson Mandela • George Washington • 74 men and women died in Waco, TX • Bill Clinton

  5. Psychiatric disorders • Anxiety disorder • Is created by an lingering belief on something threatening happens • Maniac depression • Disbelief on one’s ability, fate, etc.

  6. Political language: • Compassionate conservative • support the rich but also, supposedly, generous to the poor. • Limousine liberal • extremely rich but appreciate liberal ideas. • War president • A president who deals with war. • Death tax • Inheritance tax • Pro-life • a political position against abortion • Pro-choice • a political position that supports abortion • Insurance premium • Insurance fee • Tax cuts • cutting taxes of one group and raising taxes for others

  7. Stereotype • Ethnic conflicts

  8. Concept and memory? • Are they two different things?

  9. What is the structure of “concept”? This is the today’s topic.

  10. Demonstration: • Tell me what you see as accurately as possible.

  11. Why do you say “hammer”? • Why not “hand tool”? • Or why not the $15 hammer I bought in Wal Mart last Wednesday? • Why not “animal”? • Or why not “vegetable”?

  12. What is “concept”? • I don’t know • But maybe concept we have is related to the way we categorize things

  13. Concept --> categories • In order to study “concept”, I’ll talk about “categories” .

  14. There are trillions of categories. • Animals, dogs, cats, birds, mammals, furniture, desks, chairs, tables, books, magazines….. • Trees, grass, weed, stones, rocks, sand, mountains, rivers,….. • Games, sports, hobbies, … • school, banks, shops, restaurants, supermarkets,

  15. Nazi!! Fascists!! Terrorists, racists, sexists, pacifists, philanthropists, sophists, aristocrats, workers, bankers, lawyers, accountants, teachers, students, disciples, masters, gurus, beggars, bigots, • Party animals, beasts!!, dogs!!, • CEO, CFO, CIO, UFO, evp, vip, • IC (Indian Chief)

  16. Ad hoc categories • People I adore, People I admire, People I hang around, People I need, People I avoid. • Things I love, Things I enjoy, Places I love, Food I hate, music I like, movies I enjoy • countries I want to visit, restaurants I avoid

  17. Circles, triangles, squares, dots, lines, rectangles, plane, • 1, 2, 3, 4, 100, 120, • A, B, C, D,…..

  18. The format of representing a category

  19. When we say “dog,” what’s going on in our mind? • What is the mental representation of “categories”? • How do we distinguish in our mind • a dog from a cat? • a circle from a triangle? • What’s going on? • What is the structure? • What is the neural connections?

  20. Which woman looks more attractive/friendly/pleasant/capable?

  21. Concepts • What determines “dog” vs. “cat” or “table” vs. “vegetable”, “game” vs. “sport”,…..

  22. Classical view • Necessary & sufficient rule • we store definitions. • Circle --> an area circumscribed by an equidistant curve. • Triangles --> an area circumscribed by three straight lines having three angles……….. A circle of friends, Dupon circle, Columbus Circle, Circle line Bermuda triangles, triangle defense (Chicago Bulls)

  23. Brother, sister, mother, father, uncle, • Some concepts may be organized with specific rules. • But how about other categories? • Game? • Basketball, softball, horse race, chess, a wheel of fortune, survivor, roulette, love affair, computer game, Super Mario? • furniture • desk, table, rug? Bed? Computer? TV?

  24. Alternative view

  25. Concepts and categories • Pink is basically red. • 99 is almost 100. • Orange is sort of yellow. • Austin is like Rome. • San Antonio is very much like Mexico. • Pita can be bread.

  26. Concepts and categories II • Red is basically pink. • 100 is almost 99. • Yellow is almost orange. • Rome is like Austin. • Mexico is very much like San Antonio. • Bread can be pita.

  27. Birds: which one looks more like “bird”?

  28. Which desk is the best example of “desk”?

  29. Which game is the best example of “game”? • Baseball • Chess • Basketball • Politics • Football • Golf • One-night love affair • Snowboarding • Checker • Ping-Pong • Slot machine • Poker • Mahjong • Horse racing • NASCAR racing

  30. Fruit vs. Vegetable Onion Carrot Pepper Potato Jalapeno Cucumber Bitter Melon Spinach Garlic Ginger Broccoli Plantain Lettuce Cabbage Pumpkin Banana Apple Melon Grapes Lemon Avocado Orange Grape fruit Kiwi Papaya Mango Lime Tomato

  31. Example: • Fruits  banana • Sweet, can eat without cooking, lots of vitamin, from tropical countries, soft, ripe quickly, easy to eat, kids love it, tasty, can bring it for hiking • Vegetables  carrot • Not sweet, not tasty, require some cooking, lots of vitamin, from anywhere, hard, stay long, kids don’t like it, hard

  32. Probabilistic view • The boundaries of categories are fuzzy (probabilistically determined). • Some members are more probable than others. • But we are pretty sure about what “dog” means. • How do we mentally represent categorical knowledge?

  33. Organization of categories • Members of categories are organized in relation to some focal members. (prototype) • Focal members play the role of a “reference point.” • The boundaries of categories may be fuzzy, but people know pretty well which items are “good/bad” members of a category. • Penguin vs. robin, chair vs. rug,

  34. Measuring “goodness” of category members • Rosch et al. (1975) • Experiments: • Subjects were given a list containing the names of category members. • Subjects rated (using a 1-10 scale) the goodness of membership. • E.g., given “pistol”, subjects rated how good a pistol is as a member of the category “weapons.”

  35. Furniture (chair, lamp, rug, dresser, desk, stove, table, stool, television, fan, bed, television, counter) • Fruit (apple, grapefruit, watermelon, banana, cherries, boysenberry, pear, strawberries, lemon, orange, pineapple, nut) • Vehicle (car, airplane, sled, bus, bicycle, wheelchair, truck, boat, tractor, ambulance, trolley, wagon). • Weapon (pistol, arrow, slingshot, sword, tomahawk, whip, knife, cannon, fist, rifle, club, bow) • Vegetable (peas, celery, mushrooms, corn, turnips, potatoes, carrots, tomatoes, green onions, green beans, artichoke, pumpkin)…. • Other categories, bird, sport, toy, clothing.

  36. Results: • Correlations: 0.95 or up (=1 is perfect correlation) • People agree very much which items are good/bad examples of a particular category. • Categories have “good” examples and “bad” examples. • The boundaries of categories are graded, and may be arranged probabilistically with “goodness” of membership. • What determine “goodness”? Or what makes a particular item a good example of a category?

  37. Typicality and feature distribution • What makes an item a typical member of a category. • How do we perceive a particular item a typical member of a given category?

  38. Family resemblance Rosch & Mervis (1975) • Distribution of attributes (features) • The most typical item in a category has the most features in common with other members of a category, • and the fewest features in common with the member of contrasting categories. • These items are ideal examples and may be referred to as “prototype.”

  39. Which woman looks more attractive/friendly/pleasant/capable?

  40. Which woman looks more attractive/friendly/pleasant/capable?

  41. + =

  42. 12 Who is he/she?

  43. 1 4 6 9 12 15 19 20 • Morphed images of two different human faces ( Angelina Jolie – Brad Pitt by Na Yung Yu)

  44. By Na Yung Yu

  45. By me

  46. Just averaging the two faces