Processing Bias: Extending Sensory Drive to Include Efficacy and Efficiency in Information Processing

TL;DR

This paper introduces a processing bias model rooted in empirical aesthetics, linking perception, preference, and signal design evolution through effective and efficient information processing in communication signals.

Contribution

It extends the sensory drive model by incorporating processing bias, connecting perception, pleasure, and evolutionary signal design through information processing dynamics.

Findings

Preferences are influenced by emotional responses to information processing.

Signals evolve to maximize effectiveness and efficiency in information transmission.

The model links environment, perception, pleasure, and signal evolution in a causal chain.

Abstract

Communication signals often comprise an array of colors, lines, spots, notes or odors that are arranged in complex patterns, melodies or blends. Receiver perception is assumed to influence preference and thus the evolution of signal design, but evolutionary biologists still struggle to understand how perception, preference, and signal design are mechanistically linked. In parallel, the field of empirical aesthetics aims to understand why people like some designs more than others. The model of processing bias discussed here is rooted in empirical aesthetics, which posits that preferences are influenced by the emotional system as it monitors the dynamics of information processing, and that attractive signals have either effective designs that maximize information transmission, efficient designs that allow information processing at low metabolic cost, or both. We refer to the causal link between preference and the emotionally rewarding experience of effective and efficient information processing as the processing bias, and we apply it to the evolutionary model of sensory drive. A sensory drive model that incorporates processing bias hypothesizes a causal chain of relationships between the environment, perception, pleasure, preference, and ultimately the evolution of signal design, from simple to complex.