Optimal Population Codes for Control and Estimation

TL;DR

This paper explores how sensory adaptation in biological systems is optimized for control tasks rather than perception, highlighting differences from traditional sensory adaptation models and emphasizing task-specific considerations.

Contribution

It demonstrates that sensory adaptation for control differs from perception, emphasizing the importance of task-specific optimization in biological sensory systems.

Findings

Sensory adaptation for control is distinct from perceptual adaptation.

Task context significantly influences sensory optimization.

Control-oriented sensory adaptation aligns with recent experimental observations.

Abstract

Agents acting in the natural world aim at selecting appropriate actions based on noisy and partial sensory observations. Many behaviors leading to decision mak- ing and action selection in a closed loop setting are naturally phrased within a control theoretic framework. Within the framework of optimal Control Theory, one is usually given a cost function which is minimized by selecting a control law based on the observations. While in standard control settings the sensors are assumed fixed, biological systems often gain from the extra flexibility of optimiz- ing the sensors themselves. However, this sensory adaptation is geared towards control rather than perception, as is often assumed. In this work we show that sen- sory adaptation for control differs from sensory adaptation for perception, even for simple control setups. This implies, consistently with recent experimental results, that when studying sensory adaptation, it is essential to account for the task being performed.