Binding problems and feature integration theory

1. Binding problems and feature integration theory

2. Feature detectors • Neurons that fire to specific features of a stimulus • Pathway away from retina shows neurons that fire to more complex stimuli • Cells that are feature detectors: • Simple cortical cell • Complex cortical cell • End-stopped cortical cell

3. Single cell recording of neurons in the temporal lobe An electrode is inserted in this area, and measure neural responses when stimuli are changed gradually

5. Neurons in this area respond to complex stimuli like those shown on the left.

6. Selective adaptation

8. Selective adaptation to size

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17. Figure 3.30 How neurons that respond best to narrow (N), medium (M), and wide (W) bars respond to the medium-bar grating on the right of Figure 3.28. (a-b): Response before adaptation. (c) Response after adaptation to the wide-bar grating at the top left. (d) Response after adaptation to the narrow-bar grating on the bottom left.

18. After Image

21. After images: Red  Green Green  Red Blue  Yellow Yellow  Blue R G B Y Color perception

22. R B Y G adaptation adaptation After image After image

23. Binding problem

24. Two visual pathways (what & where/how systems) Image from Neuroscience, 2nd Ed. (2000).

25. Columnar organization • Neurons that respond to the same orientation are packed in the same column Image courtesy of Dr. Paul Wellman and Neuroscience, 2nd Ed. (2000).

26. Distributed coding; then what do you need? •  Combining input

27. Feature integration theory by Treisman & Gelade • Attention plays a central role in solving the binding problem. • Attention helps organize information.

28. Attention and Figure-ground segregation • Depending on where you look at, the figure and the ground switch rapidly. •  Attention plays some role in determining the figure and the ground.

29. Attention and 3D structure Depending on where to look at, you get different 3D structures.

33. Damage to the parietal lobe creates binding errors.

36. Copies of the black (A) and the white (B) vertical contour. Copies of the black (A) and the white (B) diagonal contour.

37. Copies of the left sub-figure (A) The right subfigure (B) And the central sub-figure (C)

38. Feature integration theory • Attention is the “glue” that combines the information from the what and where systems.

39. What can you predict from this theory? • If you can’t attend, you can’t combine information. •  Illusionary conjunction

40. Demonstration • I will show you a scene quickly. • Report first the black numbers. • Report what you see at each of the 4 locations. Mask +++

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45. Report first the black numbers. • Report what you saw at each of the 4 locations.

46. Illusionary conjunctions • We tend to put different features from different objects together. • Some brain damaged patients (parietal lobe) show illusionary conjunctions even when the patients were allowed to view the stimuli for 10 seconds.

47. Visual search experiments • Looking for the target • Feature search • This is easy because you find the target by looking for a single feature. •  you don’t need attention • Conjunction search • For this you need to combine two or more features (color and orientation) •  you need attention

48. Conjunction search • For this you need to combine two or more features (color and orientation) •  you need attention • Because you can attend an item one at a time, the difficulty in the conjunction search increases proportional to the number of items in the stimulus frame. • This is not the case in the feature search.

49. Which is more difficult? Find

50. Which is more difficult? Find