Science & SciLifeLab Grand Prize to Neir Eschel at Stanford University
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Neir Eshel, psychiatry resident at Stanford University, has discovered how interactions between brain neurons make us able to predict the consequence of a certain behaviour. For these findings he has now been named Grand Prize Winner of the Science & SciLifeLab Prize for Young Scientists.
The Science & SciLifeLab Prize for Young Scientists is awarded yearly and aims to acknowledge young researchers at the beginning of their career. The prize of 30,000 USD to the Grand Prizewinner and 10,000 USD each to three category winners, was established by SciLifeLab together with the scientific journal Science.
Grand Prizewinner Neir Eshel and his colleagues have investigated how learning is facilitated in our brains. It has already been shown that we learn things by comparing the result of an action with how we guessed it would be before we performed the action. The signal substance dopamine is essential in this process. The neurons that signal with dopamine actually have a unique ability to calculate the difference between the reward we expect with the one we actually receive. Until now it has not been known how the neurons perform this calculation.
By controlling the neurons with optogenetics in mice, Neir Eshel studied how the dopamine neurons interact with another type of neuron: GABA-neurons. The mice got to perform simple learning tasks and the researchers could see that when the GABA-neurons were stimulated, the dopamine-neurons reacted to unexpected rewards as if they were expected. The team trained the mice to expect a certain reward and then increased the mice’s expectations by stimulating the GABA-neurons. After several trials where the mice expected a higher reward than they received, they gave up and stopped expecting a reward at all.
It is these findings that Neir Eshel describes in his essay ”Trial and error” in the prize category Cell and Molecular Biology for which he is now awarded Science & SciLifeLab Prize for Young Scientists Grand Prize. The essay was published in Science on 2 December 2016.
David Naylor