The Directorate of Social, Behavioral and Economic Sciences offers postdoctoral research fellowships to provide opportunities for recent doctoral graduates to obtain additional training, to gain research experience under the sponsorship of established scientists, and to broaden their scientific horizons beyond their undergraduate and graduate training. Postdoctoral fellowships are further designed to assist new scientists to direct their research efforts across traditional disciplinary lines and to avail themselves of unique research resources, sites, and facilities, including at foreign locations. This postdoctoral fellowship award supports a rising interdisciplinary scholar at the intersection of psychology, neuroscience and economics. In this project, the goal is to explore how decision-making is influenced by episodic memory, by using tools and theories from the above-mentioned fields, with the addition of computational modeling. Memory is essential to adaptive behavior, enabling organisms to draw on past experience to improve choices. Yet, the neural and cognitive mechanisms by which memory guides decision making are poorly understood. Despite substantial advances in understanding neural mechanisms of memory, on one hand, and those of decision making, on the other, remarkably little is known about a central adaptive aspect of memory function: how memory for the past is used to guide decisions. The proposed research aims to address this gap by bringing together three fields: psychology, neuroscience and economics. This NSF Fellow proposes a novel framework for beginning to understand how memory for specific episodes ("episodic memory") is used to guide value-based decisions. Our overarching hypothesis is that many value-based decisions involve sampling evidence from memory to inform the decision. This team will test their hypothesis by integrating computational modeling with eyetracking and functional imaging (fMRI) in humans to investigate the neural mechanisms by which episodic memory contributes to decision making. Determining the brain and cognitive mechanisms by which memory guides decisions will lay the foundation for potential future interventions which could radically shape policy. Poor decision making has been linked to poverty and aging with cascading effects on society more generally. The proposed results could help improve individual and collective decision making with clear implications for improving education and decision making across a diverse population.

Although it may seem obvious that many decisions are guided by memory, most studies on value-based decisions have focused on how repeated rewards incrementally form habitual decisions, which are distinct from pervasive more flexible and deliberative decisions that rely on episodic memory. This team's overall approach draws on advances in the neurobiological mechanisms of perceptual decision making. In perceptual decisions, such as deciding the direction of moving random dots, visual motion information is accumulated and when enough information is accumulated, a decision is made. This accumulation process is reflected in the firing rates of neurons in association and premotor cortices. Furthermore, the speed and accuracy of the decision are explained by a threshold (or bound) applied to the accumulation of information from the visual cortex. This team hypothesizes that a similar process accounts for how memories guide value-based decisions; in particular, we propose that sequential memory retrieval enters value based decisions in the same way that visual motion information is accumulated towards a perceptual decision. By linking memory, value and choice, this knowledge is expected to have important implications for multiple fields, including psychology, economics and neuroscience.

Agency
National Science Foundation (NSF)
Institute
SBE Office of Multidisciplinary Activities (SMA)
Application #
1606916
Program Officer
Josie S. Welkom
Project Start
Project End
Budget Start
2016-07-01
Budget End
2018-06-30
Support Year
Fiscal Year
2016
Total Cost
$219,091
Indirect Cost
Name
Columbia University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10027