Processing bias: extending sensory drive to include efficacy and efficiency in information processing

Author:

Renoult Julien P.1ORCID,Mendelson Tamra C.2

Affiliation:

1. Centre of Evolutionary and Functional Ecology (CEFE UMR5175), CNRS—University of Montpellier—University Paul-Valery Montpellier—EPHE), 1919 route de Mende, 34293 Montpellier, France

2. Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA

Abstract

Communication signals often comprise an array of colours, lines, spots, notes or odours 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 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, both simple and complex.

Funder

Centre National de la Recherche Scientifique

National Science Foundation

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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