"Transcranial Stimulation Over Right Inferior Frontal Gyrus Increases the Weight Given to Private Information During Sequential Decision-Making" Free Download

XIAOFEI NIU, Nankai University

An information cascade occurs when a sequence of imperfectly informed decision makers, each of whom observes all previous decisions, has reached a point after which all future decision makers will rationally ignore their private information. However, people are often assigning too much weight to their own private information, relative to the publically observable decisions of preceding decision-makers. Recent neuroscience data show that the overweighting private information is associated with increased activity in inferior frontal gyrus (IFG) and control-related N200. Are these correlated neural processes causally involved in overweighting private information? Here, we employed tDCS and computational modeling to examine the role of the IFG for biasing choices in line with private information. Specifically, we applied different types of tDCS over the right IFG while participants completed a sequential decision-making task. Our results show that when private information conflicted with public information anodal tDCS significantly increased the percentage of choosing with private signal and decreased the average RTs, but left unaltered by cathodal or sham stimulation. Importantly, the impact of anodal stimulation over the rIFG was specific to situations when the information conflict or the task difficulty reach a threshold that triggered inhibition-related processes. Our findings suggest a critical role of the right IFG in tradeoff between private information and public information, and thus elucidate neural mechanisms in information cascades.


About this eJournal

This eJournal distributes working and accepted paper abstracts focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University


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Advisory Board

Neuroeconomics eJournal

Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER), Principal Investigator, Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Professor, Baylor University - Department of Neuroscience

Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law