Dear Brian O.Bush and netters,
> I am looking for some biological organisms and/or a chemical mixture
> whereby I can interface my BEAM (nervous networks in analog electrical
> circuits). I am looking for some symbiotic behavior possibly, but at
> first I want some "natural mechanism" to store electrical impulses (a
> crude memory).
> Brian O. Bush
I am very glad to contact with another biologists and computer
specialists which are interesting in the problem of
biocomputer.The following idea seems a little bit phantastic
but I am sure that the creation of microbial "brain" is very
real and useful thing. One thermostate and one computer may are
needed to grow and learn thousands of specialized microbial
"brains" during five days.The price of such biochips will be
negligible in the comparatively with the electronic ones. I am
sure that the described below idea will work.
Best regards,
Vladimir Ivanov
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Prof.Vladimir Ivanov
Department of Microbiology and General Immunology,
Ukrainian National University ,
60 Vladimirskaya Str.,Kiev 252017,Ukraine
Tel: 380-44-244-4403; 380-44-266-6206
Fax/Tel :380-44-216-7012; 380-44-244-4403
E-mail: ivanov at wlab.freenet.kiev.ua
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MICROBIAL "NEURAL NETWORK": ARTIFICAL INTELLIGENCE FROM FUNGY
by Vladimir N. Ivanov
Department of Microbiology and General Immunology,Ukrainian
National University, 60 Vladimirskaya St.,Kiev,252017,Ukraine
E-mail : ivanov at wlab.freenet.kiev.ua
ABSTRACT.Microbial chip ("artificial intelligence") may be
created as a pseudo-neural network grown as mycelium of
fungy.This network is grown/created under the learning action
of computer .Such chip will be very cheap.Notwithstanding the
low rate of fuzzy logic operations such chip may be useful for
the solving the anthropomorphic problems and for the
biosensoring .The theoretical and engineering issues of
fungy-based artificial intelligence are briefly considered in
this paper.
CONCEPTUAL FRAMEWORK. The theory and simulation of Neural Networks
(NN) are considered to be the basis for the construction of
Neurocomputers (NC) for solving informational problems with
simultaneous influences of numerous factors and various kinds of
information on the system .The use of NC in the elaborations of
expert systems or systems of sciences is based on special
electronic or optical elements. They provide the stability and
reliability of artificial NN and,in the future,of Artificial
Intelligence (AI).Nevertheless the recognition of information
under uncertain and fluctuated conditions and under conditions of
fuzzy reasoning is the evolutionary prerogative of the biological
systems.Therefore the hybridization of any NN-like biological
system with computer can give the best results for solving
anthropomorphic information problems such as pattern or speech
recognition.This way may be effective to construct AI because the
base for this is not only the limited human intelligence ,but the
evolutionary attainments of other biological systems as well.
PHYSICAL AND BIOLOGICAL BASIS . The hybrid of computer - enhanced
learning and working systems with NN-like mycelia of microscopic
fungi may be called as mycocomputer or Fungal Artificial
Intelligence (FAI). Fungy are the kingdom of heterotrophic
organisms widespread in nature.Cultivation of fungal colonies in
laboratory is feasible for many species of fungi by ordinary
microbiological methods in liquid or solid synthetic media.The
growth of filamentous fungi is the extention and branching of
hyphae. Hyphae is a cylinder covered by rigid cell wall with
diameter from 5 to 15 micrometers. Fungal hyphae grow in a strict
polarized manner,extending only at the extreme tip,called
apix.Hyphae can connect, aggregate and interlace between
themselves,forming mycelium.Fungal hyphae conduct electric
currents through themselves and establish endogenous electric
fields .One type of this field is the membrane potential and other
one is the lateral polarity of hyphae mainly expressed at apical
region of hyphae. Electric currents into the apex and out of the
trunk have been noted in a variety of fungi . As a consequence,
the applied electric field affects the hyphae growth and
branching.For the majority of fungal cells the physiological range
of steady electric fields would be within 0.1-10 mV per cell
diameter .The growth of fungal colonies in the applied electric
fields with intensity from 15 to 30 V/cm shows the branching and
growth of hyphae towards the anode or the perpendicular growth .
Applied electric fields may generate intracellular voltage
gradients by depolarizing the membrane at the cathodic end of a
cell and hyperpolarizing it at the anodic end.A cytoplasmic
electric field between the apices and distal region of hyphae is
about 0.5 V/cm.The time required for polarization makes up some
minutes.This time is necessary for the electrophoretical
distribution of active polymers in fungal hyphae.
ANALOGIES NETWEEN NEURON NETWORK AND MYCELIUM.Typical neuron
consists of a cell body ,branching dendrites ,one axon with
collaterals.The neurons are connected between themselves
throughout stimulating and braking synapses. The natural NN-like
mycelial network also has interhypae electic contacts.It is
proposed that these contacts hyperpolarize or depolarize the
membrane potential in the apical regions of hyphae as the
consequences of disposition of electic contacts from the apices
and synchronism of polarity of electric fields applied to
contacting mycelia. Individual mycelia may be considered as
neuron-like biological element of NC.The difference between neuron
and mycelium is in great number of mycelial exit channels. Natural
neural networks and mycelial networks are very similar
systems.Taking into account the technological possibility to
cultivate the fungal mycelium and to connect them with any
electric system,it would be interesting to build AI as a hybrid of
FAI and computer-enhanced learning and working system.
LEARNING,WORK AND MEMORY OF FAI. The learning of NN is based on
the increase of the connections between synchronously active
neuron-like elements.The learning of FAI can be carried out by
synchronization of the electric impulses from electronic or
biological receptors and the impulses corresponding to right
answer(s) from learning computer.Coincidence of these impulses may
stimulate or inhibit the extention and branching of neighbouring
hyphae and effect the number of interhyphal electric contacts.It
can be the base of FAI memory . The growth of mycelium and memory
of FAI will correlate between themselves .The duration of fungal
growth and the duration of FAI learning is near 5 days.After
learning the growth of fungi is finished and the using of FAI may
begin.The duration of FAI active work is about 20-30 days.The mass
of one mycelium is about one microgramm and the information
capacity of one mycelium as pseudo-neuron is about 10 bits .Thus,
the specific volume of FAI memory is about 10,000,000 bits per 1 g
of fungal biomass.The result of FAI work is the information in a
form of electric signals transformed and analyzed by computer.
ENGINEERING APPROACHES. The main engineering problems in the
building of FAI are the guarantee of stability,the formation of
electric contacts of sensors and computer with some thousands of
inlet,outlet and inlet mycelia, providing of fungi with oxygen and
nutrients. Stabilization problem may be solved by the using of
thermophilic micromycetes as the biological base.The providing of
fungy with oxygen and nutrients is carried out by cultivation of
fungi on porous hydrophilic carrier.The electric contacts of
sensors and computer with some thousands of inlet,outlet and inset
mycelia are formed by disposition of fungal conidia in
micropittings connected with electrical contacts,as well as
germination of conidia throughout the liquid isolation layer
between the micropittings and porous hydrophilic carrier.
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