paulf at manor.demon.co.uk (Paul Fawcett) writes:
:: Biologically Plausible Dynamic Artificial Neural Networks.
: -----------------------------------------------------------
Biologically Plausible Artificial Neural Network sounds to me
a bit like an oxymoron. I tend to consider any `Artificial Neural
Networks' as not biologically plausible.
:: A *Dynamic Artificial Neural Network* (DANN) [1]
: possesses processing elements that are created and/or
: annihilated, either in real time or as some part of a
: development phase [2].
:: Of particular interest is the possibility of
: constructing *biologically plausible* DANN's that
: models developmental neurobiological strategies for
: establishing and modifying processing elements and their
: connections.
:: Work with cellular automata in modeling cell genesis and
: cell pattern formation could be applicable to the design
: of DANN topologies. Likewise, biological features that are
: determined by genetic or evolutionary factors [3] would
: also have a role to play.
:
Cellular automata? One might feel reminded of the Game of
Life, where the cells change their state of being alive or
dead according to the states of the neighbouring cells. If
something like that is suggested, I feel somewhat skeptical if
that is of use. I thought that the main issue of neurogenesis
was the formation of synapses. That means, e. g., how do the
neuronal processes find their way to their targets through a
nascent entanglement of cells (not necessarily neurones, but
also glia)? How is synaptic coupling changed in response to some
stimulus? So, are your `cells' neurones, processes, synapses, or what?
But perhaps you meant a concept of a cellular automaton so general
that one might consider the use of the word as nearly
meaningless.
At least, the point seems to be a little mute to a person with
some half-knowledge about cellular automata and neurogenesis.
: Putting all this together with a view to constructing a
: working DANN, possessing cognitive/behavioral attributes of
: a biological system is a tall order; the modeling of nervous
: systems in simple organisms may be the best approach when
: dealing with a problem of such complexity [4].
There seems to be enough work to be done to simulate `static' Neural
Networks in simple organisms. An interesting question is, e. g.,
what role the complex electrophysiological properties of the single
neuron play for the behaviour of the whole network? What are
the effects of neuromodulators? And these questions may
also be of relevance in neural development.
Artificial Neural Networks do hardly play any role in that
kind of research, IMVHO, unless they have sophisticated
neuronal properties, which most information scientists never
dream of, but I wouldn't call such a model Artificial Network
in order to distinguish it from much more primitive devices,
which might be appropriate to describe spin glasses or
whatever.
As you can see, my view is that the Artificial Neural Network research
is an engineering discipline detached from natural paradigmata,
just as the whole AI. (As this is also crossposted to AI
groups, I expect to have to put on my flame-proof suit.)
:: Any comments, opinions or references in respect of the
: above assertions would be most welcome.
::: Many thanks
:: Paul Fawcett.
:: University of Westminster
::: References.
[deleted]
--
Ulf R. Andrick andrick at rhrk.uni-kl.de
FB Biologie - Tierphysiologie
Universitaet Was du nicht selber weiszt,
D-W 6750 Kaiserslautern das muszt du dir erklaeren (Tegtmeier)
--
Ulf R. Andrick andrick at rhrk.uni-kl.de
FB Biologie - Tierphysiologie
Universitaet Was du nicht selber weiszt,
D-W 6750 Kaiserslautern das muszt du dir erklaeren (Tegtmeier)
