Plant behavior and the plant neurobiology debate

Brought to you in part by Larry Matt York

semantics

neurons?

neurotransmitters

information processing

modularity

network

signaling

Presentation Outline

Plant behaviorbehavior as phenotypic plasticitybehavior as result of sensitive and perceptive monitoring systems.behavior as a basic feature of living forms

The plant neurobiology debatephysiological basis of behaviorsimilarities and differences between metazoan neurological systems and other methods of information acquisition and manipulation leading to acclimative phenotypic plasticity

Behavior is often ambiguously defined or not defined at all. The most straight-forward definition would simply be "what an organism does," or an organism's response to stimuli, ie, phenotypic plasticity which is defined as the ability of a single genotype to assume multiple phenotypes. It is not the fault of the plant behaviorist the term remains so poorly defined, yet it can be argued all living things behave, in fact, that is precisely why life is so associated with animation. It is behavior that makes a living thing distinguishable from a rock.

Plants exhibit a great diversity of responses to the abiotic and biotic environments, and it is now apparent plants have perceptive and reactive abilities related to vision, smell, taste and touch.

A classification of behaviors appropriate for plant science

Silvertown and Gordon 1989

Plants exhibit diverse behaviors in response to their perception of diverse signals and cues. Many behaviors have to do with plastic development and organismal modularity (heteroblastic development), but some approximate any definition of behavior.

Movements - Venus fly trap catching insect, Mimosa leaves reacting to heat, sleep movements, sun-tracking, nutations, plastic growthgoogle: plants in motion

Proto-vision - Plants can determine aspects of their environment by perceiving the quality of light arriving on their leaves. Many plants avoid shade and grow towards light, but some exhibit skototropism growing (moving) away from light, such as climbing plants looking for a host stem. Plants can detect neighboring plants when those other plants influence the red/far-red spectrum. Like animals, plants use the cues of night and day to form a circadian rhythm, and to perform associated behaviors such as sleep movements.

Phytochrome mediated responses - plant vision

Smith 1995

Proto-touch - many plants exhibit thigmotropism, or response to touch. Venus fly traps are a good example, as are climbing plants.

Proto-smell - plants use cues in the air to determine aspects of their environments. The dodder plant uses such cues to track down its prey, while other plants have been shown to use volatiles released after herbivore attack as a cue for inducing defense. Interesting, the volatiles also attract predators and parasites of the attacking herbivore.

Plant responses to insect herbivory

Kessler and Baldwin 2002

Callaway et al. 2003

Proto-taste - roots respond to many compounds within the rhizosphere. They communicate with rhizobia to orchestrate nodule development. Plants have been show to discriminate between self / non-self, kin / non-kin, and conspecific / heterospecific classes, and perhaps use something like chemical sonar to navigate soil

Exudates and rhizospheric interactions

Bais et al. 2004

It is apparent plants meet the basic criteria of a perceptive and responsive organism, becoming the behaviorist's black box giving particular responses to particular stimuli.

Behavioral ecology has given great evolutionary insight to the phenotypic plasticity of animals referred to as behavior, where behavior is defined as what is studied in behavioral ecology. Cognitive ecology is a more recent development focused on the mechanisms giving rise to behavior in animals, that is in the acquisition and manipulation of information leading to response. The field places constraints on performance, and exposes non-intuitive biases of the systems when modeled as artificial neural networks.

Neurobiology has long been considered the field studying the most proximate features of information perception giving rise to behavior in animals. Is neurobiology up to exposing the plant's black box?

Introducing Plant Neurobiology

There is a new journal: Plant Signaling and Behavior by the Society for Plant Neurobiology

"Plant neurobiology is a newly focused field of plant biology research that aims to understand how plants process the information they obtain from their environment to develop, prosper and reproduce optimally. The behavior plants exhibit is coordinated across the whole organism by some form of integrated signaling, communication and response system. This system includes long-distance electrical signals, vesicle-mediated transport of auxin in specialized vascular tissues, and production of chemicals known to be neuronal in animals. Here we review how plant neurobiology is being directed toward discovering the mechanisms of signaling in whole plants, as well as among plants and their neighbors."

Brenner ED, Stahlberg R, Mancuso S, Vivanco J, Baluška F, Van Volkenburgh E. Plant neurobiology: an integrated view of plant signaling. Trends in Plant Science. 2006 ;11(8):413-419.

True action potentials have been found to travel along the phloem in response to touch, light changes, and cold shock.Slow-wave potentials are electrical phenomena associated with positive turgor pressure change in the xylum after rain, wounding, and burning; the electrical fluxes sorta follow this pressure waveAuxin is transported via vesicles across intercellular domains in the root cap, been called plant synapsePlants contain animal-like neurotransmitters and neuroregulators: acetylcholine, epinephrine, dopamine, levodopa, GABA, glutamate, indole acetic acids, melatonin, serotonin, catecholamines, and nitric oxidePlants behave

Neurobiological-like features of plants

Communication in plants 2006

Struik & Meinke 2008

Major criticisms: No evidence for neurons, synapses or brainNeeds intellectually rigorous foundation

Agreed:Plant cells have APs, process molecular informationSignals are transduced and transmitted across the whole plant

A simple transduction sytem, converting one signal to another: Ligand to Signal molecue

Bray and Lay 1994

Training a simple molecular module

At left, the module is trained to give a temporally variable output from a constant input, the first being a pulse and the second acting as an "on switch"

At right, the module evolves a pattern of producing a given output as a function of a variable input.

Bray and Lay 1994

Artificial Neural Networks can bridge theory with mechanisms, and imply functional equivalence of true animal neurons and other nodes in connectionist, computationalist networks

Bhalla 2003

Input

W1 W2

Output

Sigma

Biomolecular signal transduction modules seem to functionally mimic nodes in an ANN. Both can receive a signal and react varyingly. The power of such a system does not show under a reductionist perspective but through emergent properties of a complex system modulated by hundreds and thousands of factors.

Bray and Lay 1994

Bhalla 2003

A small signaling network is bewildering in complexity

Bhalla 2003

Levels of molecular and cellular analysis needed to model signaling pathways, from simple chemical reactions to mass action models incorporating compartmentalization

Compartmentalization lessens cross-talk in general, but also allows specific connectivity between systems.

Neurons seem to fit as a higher level of compartmentalization, yet maintain the same connectionist and computationalist properties... the more things change, the more they are the same?

Bhalla 2003

Modularity is becoming increasingly stressed in the understanding of cellular signaling networks, and such a basic perspective is also required for a full understanding of traditional

neurobiology, which must be understood from the workings of single neurons to the workings of neurons in network.

If a simple molecular loop is a module, the conglomerations are supermodules, then perhaps the neuron is a metamodule allowing extreme compartmentalization

Bhalla 2003

Circuit diagram of C. elegans neurobiology

Taken from wormatlas.org

In fact, traditional neurobiology is not sufficient to explain all the information acquisition and manipulation leading to acclimative behavioral responses in animals. The field of neuroimmunomodulation integrates neurobiology with the larger endocrine system as well as the immune system for the study of disease, showing a trend for some type of unification of biological information processing systems.

Essentially, plant neurobiologists are asking neurobiology to be an umbrella for all living information processing and behavioral systems in which biological signaling provides the informational representation and computation, at all levels of organization.

Perhaps plant neurobiology isn't quite right after all...

Hmmm....

Introducing Plant Endocrinology

Surprisingly, even endocrinology is unorthodox when applied to plants even though there has been extensive research into plant hormones. Endocrinology is the study of cell-to-cell signaling, and the brain is really nothing but a specialized endocrine system. Any pair-wise association of two neurons is no more powerful than the signaling between any two cells. Plant neurobiologists ask to us consider every cell a neuron, but perhaps we need only consider every neuron a cell. Every cell is a computer made of many biomolecular modules. Associations of communicating cells make use of similar mechanisms to form a multi-cellular biomolecular computer, which is the basic assumed function of the brain.

Systems biology

Neurobiology

Molecular information processing

Immunobiology

Behavioral endocrinology

?

Empirical foundations of biological intelligence

Behavioral ecology

Cognitive ecologyBehavioral endocrinology

ConnectionismComputationalism

Theoretical foundations of biological intelligence

Connectionism and computationalism provide a philosophical foundation for the abilities of seemingly intelligent systems, or that living things can achieve optimal outputs through a distributive and empirical "adaptive representational network."

Cognitive ecology provides biases and and constraints of these systems and is largely where the material foundations of these living systems interact with theory, at least in animals.

Bourret and Stock 2002

E. coli chemotaxis and other bacterial behaviors provide a simple behavioral and informational system

Informational processing systems are likely related by common descent, and thus an evolutionary science studying informational acquisition, manipulation, and response is justified. Cellular and molecular signaling provide the physiological basis, while higher-level abstractions integrate the theoretical with mechanisms. All organisms possess abilities of perception and interpretation, and the field of plant neurobiology asks scientists to focus on these similarities towards a grand unification, rather than focusing exclusively on differences and semantics.

"Indeed, the history of life can be described as the evolution of systems that manipulate one set of symbols representing inputs into another set of symbols that represent outputs (Hartwell et al. 1999)."

Works Cited1.Baluska, F., Mancuso, S. & Volkmann, D. Communication in Plants: Neuronal Aspects of Plant Life. 438 (2007). 2.Bais, H.P. et al. How plants communicate using the underground information superhighway. Trends in Plant Science 9, 26-32 (2004). 3.Bhalla, U.S. Understanding complex signaling networks through models and metaphors. Progress in Biophysics and Molecular Biology 81, 45-65 (2003). 4.Bourret, R.B. & Stock, A.M. Molecular Information Processing: Lessons from Bacterial Chemotaxis. Journal of Biological Chemistry 277, 9625-9628 (2002). 5.Bray, D. & Lay, S. Computer simulated evolution of a network of cell-signaling molecules. Biophysical Journal 66, 972-977 (1994). 6.Brenner, E.D. et al. Plant neurobiology: an integrated view of plant signaling. Trends in Plant Science 11, 413-419 (2006). 7.Hartwell, L.H. et al. From molecular to modular cell biology. Nature 402, C47-C52 (1999). 8.Regev, A. & Shapiro, E. Cellular abstractions: Cells as computation. Nature 419, 343-343 (2002). 9.Silvertown, J. & Gordon, D.M. A Framework for Plant Behavior. Annual Review of Ecology and Systematics 20, 349-366 (1989). 10.Struik, P.C., Yin, X. & Meinke, H. Plant neurobiology and green plant intelligence: science, metaphors and nonsense. Journal of the Science of Food and Agriculture 88, 363-370 (2008). 11.Alpi, A. et al. Plant neurobiology: no brain, no gain? Trends in Plant Science 12, 135-136 (2007). 12.Trewavas, A. Green plants as intelligent organisms. Trends in Plant Science 10, 413-419 (2005).