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 specificinformation to accomplish a task are said to reflect top down control.

Fixations that are evoked automatically by the occurrence of a stimulus are said tobe under bottom up control.

Examples?

Looming – a potential bottom up mechanism

Neurons in Area MT sensitive to looming stimuli.

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.

Neurons in substantia nigra pc in basal ganglia release dopamine.These neurons signal expected reward.

Neurons at all levels of saccadic eye movement circuitry are sensitive to reward.

This provides the neural substrate for learning gaze patterns in natural behavior, and for modeling these processes using Reinforcement Learning.

Dopaminergic neurons in basal ganglia signal expected reward. (Schultz, 2000)

Response to unexpected reward

Increased firing for earlier or later reward

Expected reward is absent.SNpc

Conditioned stimulus predicts reward

target selection

signals to muscles

inhibits SC

saccade decision

saccade command

planning movements

Neural Circuitry for Saccades

Substantia nigra pc

Substantia nigra pc modulates caudate

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 fieldsFEF: frontal eye fieldsCaudate nucleus in basal ganglia

Monkey makes a saccade to a stimulus - some directions are rewarded.

Cells in caudate signal both saccade direction and expected reward.Hikosaka et al, 2000

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)

Give some examples that eye movements are learned.

Jovancevic & Hayhoe 2009 Real Walking

• 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

Experimental Design (ctd)

Learning to Adjust Gaze

• Changes in fixation behavior fairly fast, happen over 4-5 encounters (Fixations on Rogue get longer, on Safe shorter)

Time fixatingIntersection.

“Follow the car.”

or“Follow the car and obey

traffic rules.”

Car RoadsideRoad Intersection

Shinoda et al. (2001)

Detection of signs at intersection results from frequent looks.

Top Down strategies: Learn where to look

Give some examples that reveal attentional limitations in visual processing

1. Difficult to detect color change in one of 8 colored squares.

2. Invisible gorilla

3. Color-changing card trick

What are these examples called?

What conclusions has been drawn from these experiments.

• 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?

Briefly summarize the experiment by Jovancevic, Hayhoe, & Sullivan. What did they find?

Pedestrians’ paths

Colliding pedestrian path

What Happens to Gaze in Response to an Unexpected Salient Event?

• The Unexpected 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?

Probability of Fixation During Collision Period

Pedestrians’ paths

Colliding pedestrian path

More fixations on colliders in normal walking.

No effect in Leader condition

Controls Colliders

Normal Walking

Follow Leader

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.

Why are colliders fixated?

Detecting a Collider Changes Fixation Strategy

Longer fixation on pedestrians following a detection of a collider

“Miss” “Hit”

Time fixating normal pedestrians following detection of a collider

Normal Walking

Follow Leader

To make a top-down system work, Subjects need to learn statistics of environmental events and distribute gaze/attention based on these expectations.

Subjects rely on active search to detect potentially hazardous events like collisions, rather than reacting to bottom-up, looming signals.

Possible reservations…

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

Our Experiment:

Allocation of gaze when driving.

Does deviation in the flow field cause bottom up attractionof 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)

Optic Flow

Optic Flow

What is meant by “optic flow”? How was it involved in Lab 3?

Pattern created on the retina by contours in a scene as the observer moves through thennvironment.

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 thatare near walking speed look slower and are easier to tell apart when you arewalking 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, makingthem more sensitive to object motion in the visual field.