The Green Plant as an Intelligent Organism - Communication in Plants: Neuronal Aspects of Plant Life - page 5

1,000 protein kinases in both animals and plants provides for enormous
numbers of complex elements of control, switching mechanisms and in-
cluding both complex positive and negative feedback interactions (Bhalla
et al. 2002; Chock and Stadtman 1977; Ingolis and Murray 2002). Such
chemical systems parallel the capabilities of simple neural network struc-
tures as a set of on/off switches with feedback (Hopfield 1982; Hopfield and
Tank 1986) on which they are modelled (Hjelmfeldt et al. 1991, 1992). Even
in simple networks collective computational properties arose with paral-
lel processing and extensive numbers of associative memories emerged as
attractors occupying part of the network. Chemical neurons and neural
network behaviour have most applicability to signal transduction studies
(Bray 2003).
From an alternative direction, use of phage display or two hybrid meth-
ods has shown that that all proteins participate in the cellular network,
a structure composed of hubs and connectors in which the number of con-
nections to any one protein obeys a simple power law (Bray 2003; Gavin
et al. 2002; Maslov and Sneppen 2002; Ravasz et al. 2002; Tong et al. 2002).
The metabolic and signalling networks are modular with recognizable re-
curring circuit elements or network motifs that (1) filter out spurious input
fluctuation, (2) generate temporal patterns of expression, and (3) accelerate
throughput (Alon 2003). Such structures provide for robust behaviour that
can also be fragile (Alon et al. 1999; Carlson and Doyle 2002) and exhibit
highly optimized tolerance of variations in individual protein constituents
(McAdams and Arkin 1999). “The cell in which zillions of molecular events
occur at a time computes in parallel fashion” (Huang 2000), just like a brain.
Robustness results from sharing control throughout the metabolic and sig-
nalling network with controlling steps determined by the environmental
state (Strohmann 2000). Emerging network structures indicates how com-
plex feedback controls operate (Davidson et al. 2002).
The cellular network perceives continual environmental variation
through a multiplicity of receptors. Transduction in plants involves numer-
ous second messengers and kinases enabling network information flow
that may diverge, branch, converge, adapt, synergize and integrate through
cross talk (Trewavas 2000). Such networks learn either by increasing the
synthesisofparticularconstituentsorbychangingtheaffinitybetweenpar-
ticular network steps by post-translational modification (Trewavas 1999).
Memory is simply the retention with time of the enhanced pathway of in-
formation flow and can be accessed by other pathways through cross talk
(Taylor and McAinsh 2004). Cellular networks capable of these properties
are entitled to be called intelligent and indeed form the basis of machine
intelligence (Warwick 2001) and other forms of biological intelligence (Ver-
tosick 2002).