What is meant by “top-down” and “bottom-up” processing? Give examples of both.

1. What is meant by “top-down” and “bottom-up” processing? Give examples of both. Bottom up processes are evoked by the visual stimulus. Top down processes are operations that reflect the subject’s current cognitive goals. In the case of eye movements, fixations that are for the purpose of getting specific information to accomplish a task are said to reflect top down control. Fixations that are evoked automatically by the occurrence of a stimulus are said to be under bottom up control. Examples?

2. Looming – a potential bottom up mechanism Neurons in Area MT sensitive to looming stimuli.

3. What is “Neuroeconomics”? Explain how the saccadic eye movement circuitry is influenced by reward. Humans/primates exhibit behaviors that lead to expected reward. Reward is provided by the release of dopamine.

4. Neurons at all levels of saccadic eye movement circuitry are sensitive to reward. Neurons in substantia nigra pc in basal ganglia release dopamine. These neurons signal expected reward. This provides the neural substrate for learning gaze patterns in natural behavior, and for modeling these processes using Reinforcement Learning.

5. Dopaminergic neurons in basal ganglia signal expected reward. (Schultz, 2000) SNpc Expected reward is absent. Response to unexpected reward Increased firing for earlier or later reward

6. Conditioned stimulus predicts reward

7. Neural Circuitry for Saccades planning movements target selection saccade decision saccade command inhibits SC Substantia nigra pc signals to muscles Substantia nigra pc modulates caudate

8. Neurons at all levels of saccadic eye movement circuitry are sensitive to reward. LIP: lateral intra-parietal cortex. Neurons involved in initiating a saccade to a particular location have a bigger response if reward is bigger or more likely SEF: supplementary eye fields FEF: frontal eye fields Caudate nucleus in basal ganglia

9. Cells in caudate signal both saccade direction and expected reward. Hikosaka et al, 2000 Monkey makes a saccade to a stimulus - some directions are rewarded.

10. This provides the neural substrate for learning gaze patterns in natural behavior, and for modeling these processes using Reinforcement Learning. (eg Sprague, Ballard, Robinson, 2007)

11. Give some examples that eye movements are learned. Jovancevic & Hayhoe 2009 Real Walking

12. Experimental Design (ctd) • Occasionally some pedestrians veered on a collision course with the subject (for approx. 1 sec) • 3 types of pedestrians: Trial 1: Rogue pedestrian - always collides Safe pedestrian - never collides Unpredictable pedestrian - collides 50% of time Trail 2: Rogue Safe Safe Rogue Unpredictable - remains same

13. Learning to Adjust Gaze • Changes in fixation behavior fairly fast, happen over 4-5 encounters (Fixations on Rogue get longer, on Safe shorter)

14. Top Down strategies: Learn where to look Detection of signs at intersection results from frequent looks. Shinoda et al. (2001) “Follow the car.” or “Follow the car and obey traffic rules.” Time fixating Intersection. Road Car Roadside Intersection

15. Give some examples that reveal attentional limitations in visual processing Difficult to detect color change in one of 8 colored squares. Invisible gorilla Color-changing card trick What are these examples called? What conclusions has been drawn from these experiments.

16. Briefly summarize the experiment by Jovancevic, Hayhoe, & Sullivan. What did they find? • Experimental Question: How sensitive are subjects to unexpected salient events (looming)? • General Design: Subjects walked along a footpath in a virtual environment while avoiding pedestrians. Do subjects detect unexpected potential collisions?

17. What Happens to Gaze in Response to an Unexpected Salient Event? Pedestrians’ paths Colliding pedestrian path • TheUnexpected Event: Pedestrians on a non-colliding path changed onto a collision course for 1 second (10% frequency). Change occurs during a saccade. Does a potential collision (looming) attract gaze?

18. Probability of Fixation During Collision Period Pedestrians’ paths Colliding pedestrian path More fixations on colliders in normal walking. No effect in Leader condition Normal Walking Follow Leader Controls Colliders

19. Why are colliders fixated? Small increase in probability of fixating the collider. Failure of collider to attract attention with an added task (following) suggests that detections result from top-down monitoring.

20. Detecting a Collider Changes Fixation Strategy Time fixating normal pedestrians following detection of a collider Normal Walking Follow Leader “Miss” “Hit” Longer fixation on pedestrians following a detection of a collider

21. Subjects rely on active search to detect potentially hazardous events like collisions, rather than reacting to bottom-up, looming signals. To make a top-down system work, Subjects need to learn statistics of environmental events and distribute gaze/attention based on these expectations.

22. Possible reservations… Perhaps looming robots not similar enough to real pedestrians to evoke a bottom-up response.

23. Our Experiment: Allocation of gaze when driving. Does deviation in the flow field cause bottom up attraction of gaze? Drive along street with other cars and pedestrians. Instructions - drive normally, maintain speed, left lane, be aware of surroundings. Measure fixations on oncoming cars (swerving and controls)

24. Optic Flow

25. What is meant by “optic flow”? How was it involved in Lab 3? Optic Flow Pattern created on the retina by contours in a scene as the observer moves through the nnvironment.

26. Person walking in a simulated environment. The spots on the wall(s) and floor would normally flow past the walker as he or she walked forward (visual flow), but in a simulator they can be made to move faster or slower than they normally would. If the spots are taken away, no visual speed is present. A person in a speed discrimination experiment would be presented with one set of spots moving at one speed (relative to the person) and, after a short blank, a second set of spots, moving at a different speed. The person’s task is to judge which speed was faster. Visual-flow speeds that are near walking speed look slower and are easier to tell apart when you are walking than when you are standing, though the speeds in the retinal image are the same. Idea is that humans subtract out the optic flow generated by self motion, making them more sensitive to object motion in the visual field.