# Stochastic models of evidence accumulation in changing environments

arXiv: https://arxiv.org/abs/1505.04195 · HTML: https://mlsanity.com/paper/1505.04195/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2015.

## Built on by (most cited first, 1 of 1)

- [Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain Environments](https://mlsanity.com/paper/2503.19107/) (2025)

## Abstract (arXiv)

Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing world. What effect does such impermanence have on classical results about decision making? To address this question we use sequential analysis to derive a tractable model of evidence accumulation when the correct option changes in time. Our analysis shows that ideal observers discount prior evidence at a rate determined by the volatility of the environment, and the dynamics of evidence accumulation is governed by the information gained over an average environmental epoch. A plausible neural implementation of an optimal observer in a changing environment shows that, in contrast to previous models, neural populations representing alternate choices are coupled through excitation. Our work builds a bridge between statistical decision making in volatile environments and stochastic nonlinear dynamics.