“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...

Full description

Saved in:
Bibliographic Details
Published in:Frontiers in psychology Vol. 7; p. 1505
Main Authors: Calvo, Paco, Baluška, František, Sims, Andrew
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 04.10.2016
Subjects:
Psychology
feature detection
plant behavior
predictive coding
plant perception
root transition zone
ISSN:1664-1078, 1664-1078
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Reviewed by: Adam Sanborn, University of Warwick, UK; Anthony Trewavas, University of Edinburgh, UK
This article was submitted to Cognitive Science, a section of the journal Frontiers in Psychology
Edited by: Eddy J. Davelaar, Birkbeck, University of London, UK
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2016.01505