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Upcoming Stuff:

Upcoming Stuff:. Finish attention lectures this week No class Tuesday next week What should you do instead? Start memory Thursday next week Read Oliver Sacks – The Lost Mariner for Thursday (26 th ) Read Elizabeth Loftus (For the following week). Features and Objects in Visual Processing.

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  1. Upcoming Stuff: • Finish attention lectures this week • No class Tuesday next week • What should you do instead? • Start memory Thursday next week • Read Oliver Sacks – The Lost Mariner for Thursday (26th) • Read Elizabeth Loftus (For the following week)

  2. Features and Objects in Visual Processing

  3. The Visual World is an Arrangement of Features • Color • Motion • Form • Depth • Orientation

  4. Pre-attentive vs. Attentive Processing • Pre-attentive processing • Does the visual system register some basic features automatically (without attention) • if so, what features? • How would you know?

  5. Pre-attentive vs. Attentive Processing • Indicators of Pre-attentive processing • 1. processing precedes orienting - if you shift your attention to something or someplace because of some processing you did on the information there, you must have done that processing without attending

  6. Pre-attentive vs. Attentive Processing • Indicators of Pre-attentive processing • 2. processing done in parallel - if you can process features of several objects simultaneously, you must have done that processing without attention

  7. Parts vs. Wholes • We see wholes, but the visual system initially sees parts (i.e. features) of objects

  8. Parts vs. Wholes • For example: We see two rectangles, but the visual pathways initially detects small lines with some orientation

  9. Parts vs. Wholes • Simple features form boundaries We see two rectangles, but the visual pathways initially detects small circles with some color

  10. Parts vs. Wholes • Conjunctions don’t form boundaries We see only one rectangle (at least initially) because the boundaries of the inner one are made of conjunctions – these require attention to be perceived

  11. “Early parsing of the visual field is mediated by separate properties, not by particular combinations of properties”

  12. What does Treisman conclude from this observation? • “Analysis of properties and parts precedes their synthesis” • What is the “strong prediction” Treisman makes?

  13. Illusory Conjunctions • “errors of synthesis”

  14. Illusory Conjunctions • Identify the letter on the left of the screen and the digit on the right

  15. Illusory Conjunctions Q 4

  16. Illusory Conjunctions What colored shapes did you see?

  17. Illusory Conjunctions • Illusory conjunction - when perceived combination of attributes was not present

  18. Illusory Conjunctions • Illusory conjunction - when perceived combination of attributes was not present • Supports notion that primitive features are processed independently and then bound together to form objects • This is thought to require attention focused on the location of the object to be bound

  19. Visual Search • Visual Search: finding a single item in a cluttered visual scene

  20. Visual Search • Is there a green square?

  21. Visual Search • Is there a green square?

  22. Visual Search • Parallel search: like many independent spotlights

  23. Visual Search • Serial search: each item is selected until target is found

  24. Visual Search • Serial search: each item is selected until target is found

  25. Visual Search • Serial search: each item is selected until target is found

  26. Visual Search • Serial search: each item is selected until target is found

  27. Visual Search • How could you test which kind of search was happening?

  28. Visual Search • Parallel search - search time is independent of distracter number

  29. Visual Search • Serial Search - linear increase in search time with number of distractors

  30. Visual Search • Search slope for color singletons is flat. What does this tell us about color and attention?

  31. Visual Search • Search slope for shape singletons is flat. What does this tell us about shape and attention?

  32. Visual Search • Conjunction search: NOT FLAT!

  33. Visual Search • Search Slopes can be flat for targets defined by: • color • orientation • curvature • motion • depth • What does this imply about these features ? • What does it tell us about conjunctions of features ?

  34. Treisman’s Feature Integration Theory • Early visual system parses scene into features represented in “feature maps” • “Attention Spotlight” can be moved across an overlay of these feature maps • Focused attention is required to “bind” features together into objects

  35. Feature Integration Theory • What term does Treisman use to describe the bundle of features at a specific location?

  36. Feature Integration Theory • Object Files are mental (neural?) representations of the features associated with an object • whenever an object is selected by attention its features are bound and an object file is “opened” • when the features of that object change, the object file is updated

  37. Feature Integration Theory • How did Treisman et al. test whether the visual system uses object files?

  38. Feature Integration Theory • Priming: observers are faster to respond to something they’ve just seen

  39. Feature Integration Theory +

  40. Feature Integration Theory G + N

  41. Feature Integration Theory +

  42. Feature Integration Theory +

  43. Feature Integration Theory G +

  44. Feature Integration Theory What Letter?

  45. Feature Integration Theory • Compare “primed” box with “unprimed” box. What was the result?

  46. Feature Integration Theory • What was the result? • Naming was faster if the prime occurred in the same box, even though the object had moved

  47. Feature Integration Theory • What was the result? • Naming was faster if the prime occurred in the same box, even though the object had moved • Interpretation?

  48. Feature Integration Theory • What was the result? • Naming was faster if the prime occurred in the same box, even though the object had moved • Interpretation? • visual system establishes object files (e.g. a box with a G in it) and updates them as the location and features of the object change • It is faster to make small changes than large changes

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