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Stanford neuroscientist receives sixth annual Jay Pepose ’75 Award in Vision Sciences

On Wednesday afternoon, March 18, in Gerstenzang 121, Stanford neuroscientist William Newsome received Brandeis University’s sixth annual Jay Pepose ’75 Award in Vision Sciences. The ceremony was called “A New Look at Gating: Selective Integration of Sensory Signals through Network Dynamics.”

Introducing himself and his background relating to vision, Newsome stated, “Over the last 10-15 years, I’ve used the visual system as a platform to ask questions … with a real emphasis on visual decision-making.”

Working with two post-doctoral students from Stanford’s School of Medicine, Newsome’s research focuses on the relationships between different types of visual stimuli and their influence upon the decision-making process in primates, as well as the neural map that processes stimuli and turns it into an output reaction.

Newsome described his work as “context-sensitive decision-making. The classic example of context-sensitive decision-making is the Wisconsin card sorting task.”

In this experiment, subjects are presented with four cards, each with different combinations of shapes and colors printed on it.

“The key thing about the card-sorting task is that you run different trials under different instruction sets… Under one instruction set, you’ll be asked to report the color that’s on the card … On another instruction set, you’ll be asked to report shape … On yet a third instruction task, you’ll be asked to report the number of items … The point is, you have the same stimulus coming into your visual system, but you have different behavioral reports depending on the context, or the instruction set, you’re running under.”

In other words, the cards are exactly the same from trial to trial. The only difference is in what the subject is being asked to do. Newsome is interested in how the instructions, or the context, changes subject behavior patterns.

“We have trained monkeys to do the context-sensitive visual task and we don’t use cards [or] verbal reports, but we use these dynamic motion stimuli,” Newson elaborated. “In the new version of this task, the dots that the animals look at on a TV screen … they have two properties. First of all, they could be drifting … either to the right or to the left, and the monkey will, under one context, report the direction of motion, right or left, by making an eye movement to the right target or the left target. The dots also have this property of color … some proportion is green, some proportion is red, and the second instruction set the monkey gets to report is, is the dominant color green or red?”

With three different intensity levels for each of the four characteristics, there are 36 possible combinations for the monkey to view in any trial. Newsome attempted to arrange two trials with each combination, without overstressing the subject animals. If the monkey makes the correct choice, he is rewarded. If he makes the incorrect choice, he loses the opportunity for a reward.

Explaining how complicated the decision-making process actually is, Newsome explained, “He [the monkey] has to process the information, render a decision based upon the relevance of the information, he has to somehow ignore or disregard the irrelevant information … and make a decision, in which direction is he going to move his eyes.”

His results indicated that, at the level of a single unit, the values of color and motion were completely intermixed. There was no distinct relationship between the two signals.
However, at the population level, the two quantities can be separated. Together, these results seem to indicate that both relevant and irrelevant sensory inputs are present in the decision-making process, regardless of the provided instruction set. Newsome had expected that the irrelevant data would be “filtered out” in the pre-frontal cortex. The selection of a choice appears to occur comparatively late in the process, possibly within the pre-frontal cortex, or other related areas of the brain.

Newsome predicts that in the next five years, “The whole field will be vectoring in on this problem … and trying to invent the best tools”

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