ReviewProceedings. Biological sciences2019
Processing bias: extending sensory drive to include efficacy and efficiency in information processing.
Review in Proceedings. Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Less is more: Aesthetic liking is inversely related to metabolic expense by the visual system.PNAS nexus · 2025Article
- Contingency, determinism, and constraint in the evolution of elaborate courtship phenotypes.Evolution; international journal of organic evolution · 2025Article
- Comparing Activation Typicality and Sparsity in a Deep CNN to Predict Facial Beauty.Computational brain & behavior · 2025Article
- A Comparison of Image Statistics of Peacock Jumping Spider Colour Patterns and Natural Scenes.Ecology and evolution · 2025Article
- Sparsity in an artificial neural network predicts beauty: Towards a model of processing-based aesthetics.PLoS computational biology · 2023Article
- Article
- When less is more: coy display behaviours and the temporal dynamics of animal courtship.Proceedings. Biological sciences · 2023Review
- The aesthetic value of reef fishes is globally mismatched to their conservation priorities.PLoS biology · 2022Article
- Increased signal complexity is associated with increased mating success.Biology letters · 2022Article
- The use of cognitive psychology-based human-computer interaction tax system in ceramic industry tax collection and management and economic development of Jingdezhen city.Frontiers in psychology · 2022Article
- Darwin, sexual selection, and the brain.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Habitat selection and human aesthetic responses to flowers.Evolutionary human sciences · 2021Article
- Higher-Order Musical Temporal Structure in Bird Song.Frontiers in psychology · 2021Article
- Sexual signaling pattern correlates with habitat pattern in visually ornamented fishes.Nature communications · 2020Article
- Dubious Claims about Simplicity and Likelihood: Comment on Pinna and Conti (2019).Brain sciences · 2020Article
- Endless forms of sexual selection.PeerJ · 2019Article
- Mechanistic constraint and evolutionary history matter for the origin of innovation in animal communication.Behavioral ecology : official journal of the International Society for Behavioral EcologyReview
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.