Testing the implications of a dynamic, neurally-informed computational model of valuation, decision making, and self-control
Principal Investigator: Cendri Hutcherson
Grant Names: NSERC ; Discovery Grant ;
Award Years: 2016 to 2021
Have you ever started reaching for a tempting plate of cookies, only to stop a fraction of a second later when you remember that they’re full of fat and sugar? Or struggled to resist the lure of TV and the Internet while working? Effective self-control allows us to resist these kinds of immediate temptations and make decisions we know will leave us better off in the end. Unfortunately, people often struggle with temptation and choose in ways they later regret. Despite decades of research, we don’t fully understand why. What makes self-control feel so hard sometimes? Why do some people have more difficulty than others? Most importantly, how can we develop better self-control?
The proposed program of research will provide new answers to these longstanding questions by investigating the computational and neural bases of decision making. Recent results highlight something that often goes underappreciated despite its deep importance: self-control doesn’t just “happen.” It is a process that unfolds and changes over time, sometimes quite quickly, sometimes agonizingly slowly. Drawing on insights from psychology, neuroscience, and economics, and combining sophisticated computational approaches with novel behavioral and neural measures, we are beginning to show how values and priorities are represented in the brain, and how these lead to cognitive and affective dynamics that promote or interfere with good decision making. Understanding the basic mechanisms underlying choice will help us understand both adaptive and maladaptive choices, and develop more effective interventions to improve health and well-being.