Neuroscientist Christine Constantinople will examine our economic decision-making process under a five-year, $1.5 million grant from the National Institutes of Health.

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When it comes to making decisions about investments, medical treatment, or insurance policies, we are more worried about financial loss than we are confident about monetary gain. But the intricacies of how our brain functions to bring about these sentiments are not clear.

New York University neuroscientist Christine Constantinople will examine this process under a five-year, $1.5 million grant from the National Institutes of Health—a project that will shed new light on this every-day, but not well understood, phenomenon. The work will also enhance our understanding of how the brain makes mathematical calculations, with the findings having potential implications for education and related fields.

Constantinople’s grant (DP2 MH126376-01) is a New Innovator Award, which supports innovative research from early-career researchers and is part of the NIH Common Fund’s High-Risk, High-Reward Research program, which backs studies with the potential for broad impact in the biomedical, behavioral, or social sciences.

“The High-Risk, High-Reward Research program catalyzes scientific discovery by supporting research proposals that, due to their inherent risk, may struggle in the traditional peer-review process despite their transformative potential,” NIH said in announcing this year’s recipients.

“The breadth of innovative science put forth by the 2020 cohort of early career and seasoned investigators is impressive and inspiring,” said NIH Director Francis S. Collins, M.D., Ph.D. “I am confident that their work will propel biomedical and behavioral research and lead to improvements in human health.”

Constantinople’s research will specifically focus on how neurons perform arithmetic for economic decision-making, including integration and summation of information as well as subtraction and multiplication.

“This type of exploration is crucial because our aversion to loss is often not based on actual probabilities—in fact, we often overestimate the likelihood of a negative outcome and make sub-optimal choices as a result,” explains Constantinople, an assistant professor in NYU’s Center for Neural Science. “With a better grasp of the neural mechanisms underlying our often-misguided economic judgments, subsequent work can begin to address how to improve them.”

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