“Feature Detection” vs. “Predictive Coding” Models of Plant Behavior

In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity m...

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Published inFrontiers in psychology Vol. 7; p. 1505
Main Authors Calvo, Paco, Baluška, František, Sims, Andrew
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 04.10.2016
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Online AccessGet full text
ISSN1664-1078
1664-1078
DOI10.3389/fpsyg.2016.01505

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Abstract In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: "feature detection" and "predictive coding." We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature.
AbstractList In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: "feature detection" and "predictive coding." We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature.
Author Calvo, Paco
Sims, Andrew
Baluška, František
AuthorAffiliation 3 Institute of Cellular and Molecular Botany, University of Bonn Bonn, Germany
1 Minimal Intelligence Lab (MINT Lab), Department of Philosophy, University of Murcia Murcia, Spain
4 Institut Supérieur de Philosophie, Université Catholique de Louvain Louvain, Belgium
2 School of Philosophy, Psychology and Language Sciences, School of Biological Sciences, University of Edinburgh Edinburgh, UK
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– name: 1 Minimal Intelligence Lab (MINT Lab), Department of Philosophy, University of Murcia Murcia, Spain
– name: 3 Institute of Cellular and Molecular Botany, University of Bonn Bonn, Germany
– name: 4 Institut Supérieur de Philosophie, Université Catholique de Louvain Louvain, Belgium
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Keywords feature detection
plant behavior
predictive coding
plant perception
root transition zone
Language English
License This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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Reviewed by: Adam Sanborn, University of Warwick, UK; Anthony Trewavas, University of Edinburgh, UK
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Edited by: Eddy J. Davelaar, Birkbeck, University of London, UK
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Snippet In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond...
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Title “Feature Detection” vs. “Predictive Coding” Models of Plant Behavior
URI https://www.ncbi.nlm.nih.gov/pubmed/27757094
https://www.proquest.com/docview/1835497153
https://pubmed.ncbi.nlm.nih.gov/PMC5047902
https://www.frontiersin.org/articles/10.3389/fpsyg.2016.01505/pdf
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