ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2007
Neural networks for perceptual processing: from simulation tools to theories.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Using artificial neural networks to explain the attraction of jewel beetles (Coleoptera: Buprestidae) to colored traps.Insect science · 2026Article
- Why are biting flies attracted to blue objects?Proceedings. Biological sciences · 2023Article
- Additive factors do not imply discrete processing stages: a worked example using models of the stroop task.Frontiers in psychology · 2011Article
- The brightness of colour.PloS one · 2009Article
- Predator perception and the interrelation between different forms of protective coloration.Proceedings. Biological sciences · 2007Review
- Introduction. The use of artificial neural networks to study perception in animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2007Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neural networks are modelling tools that are, in principle, able to capture the input-output behaviour of arbitrary systems that may include the dynamics of animal populations or brain circuits. While a neural network model is useful if it captures phenomenologically the behaviour of the target system in this way, its utility is amplified if key mechanisms of the model can be discovered, and identified with those of the underlying system. In this review, we first describe, at a fairly high level with minimal mathematics, some of the tools used in constructing neural network models. We then go on to discuss the implications of network models for our understanding of the system they are supposed to describe, paying special attention to those models that deal with neural circuits and brain systems. We propose that neural nets are useful for brain modelling if they are viewed in a wider computational framework originally devised by Marr. Here, neural networks are viewed as an intermediate mechanistic abstraction between 'algorithm' and 'implementation', which can provide insights into biological neural representations and their putative supporting architectures.
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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.