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History influences signal recognition: neural network models of túngara frogs.
Phelps, S M; Ryan, M J.
Afiliação
  • Phelps SM; Center for Behavioral Neuroscience, Emory University, Atlanta, GA 30329, USA. sphelps@rmy.emory.edu
Proc Biol Sci ; 267(1453): 1633-9, 2000 Aug 22.
Article em En | MEDLINE | ID: mdl-11467426
ABSTRACT
Animals often attend to only a few of the cues provided by the complex displays of conspecifics. We suggest that these perceptual biases are influenced by mechanisms of signal recognition inherited from antecedent species. We tested this hypothesis by manipulating the evolutionary history of artificial neural networks, observing how the resulting networks respond to many novel stimuli and comparing these responses to the behaviour of females in phonotaxis experiments. Networks with different evolutionary histories proved equally capable of evolving to recognize the call of the túngara frog, Physalaemus pustulosus, but exhibited distinct responses to novel stimuli. History influenced the ability of networks to predict known responses of túngara frogs; network accuracy was determined by how closely the network history approximated the hypothesized history of the túngara frog. Our findings emphasize the influence of past selection pressures on current perceptual mechanisms, and demonstrate how neural network models can be used to address behavioural questions that are intractable through traditional methods.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anuros / Redes Neurais de Computação / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2000 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anuros / Redes Neurais de Computação / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2000 Tipo de documento: Article País de afiliação: Estados Unidos