Microfoundations of Expected Utility and Response Times

TL;DR

This paper derives a neural-based rule for decision-making that links neuroscience, economics, and psychology, challenging classical utility concepts and providing a microfoundation for understanding response times and choice behavior.

Contribution

It introduces a neural circuitry-based decision model that replaces axioms with biological principles, connecting neuroscience with economic and psychological theories of choice.

Findings

Expected utility should be modified based on neuroscientific evidence

Utility is a network property involving multiple neural layers

The model can simulate markets and games using neural principles

Abstract

This paper builds a rule for decisionmaking from the physical behavior of single neurons, the well established neural circuitry of mutual inhibition, and the evolutionary principle of natural selection. No axioms are used in the derivation of this rule. The paper provides a microfoundation to both Economics Choice Theory and Cognitive Psychologys Response Times Theory. The paper finds how classical expected utility should be modified to account for much neuroscientific evidence, and how neuroscientific correlates of choice should be linked to utility. In particular, the model implies the concept of utility is a network property and cannot be calculated as a function of frequencies in one layer of neurons alone; it requires understanding how different layers work together. The resulting rule is simple enough to model markets and games as is customary in the social sciences. Utility maximization and inaction are endogenous to the model, cardinality and independence of irrelevant alternatives, properties present in classical and random utility theories, are only met in limiting situations.