Introduction to Trigonometry: Angles and Radians

The research used an innovative combination of computational modeling and neuroimaging to understand decision making.

The findings provide new insight into the neural mechanisms underlying loss aversion bias in risky decision making.

The computational model accurately predicted behavior and identified a novel role for the ventral striatum in loss aversion.

Loss aversion was associated with increased connectivity between ventral striatum and ventromedial prefrontal cortex.

The work makes important theoretical contributions to prospect theory and the neuroscience of decision making under risk.

Understanding the neural basis of biases like loss aversion can inform efforts to improve decision making.

The combined modeling and neuroimaging approach could be applied to study other aspects of decision making.

The findings have practical implications for addressing biased risk-taking in domains like finance and health.

The computational model provides a tool to predict and modulate loss aversion bias in decision making.

This research significantly advances our understanding of the psychological and neural mechanisms of loss aversion.

Modulating loss aversion bias could help improve decision making in application areas like investing.

The ventral striatum may encode loss aversion by representing the negative utility of potential losses.

Loss aversion demonstrates the importance of emotions and affect in biased decision making.

This interdisciplinary approach combining modeling, behavior, and neuroimaging holds promise.

The findings open future research directions to causally probe the neural drivers of loss aversion.