Soft Report - Dipartimento di Fisica - Sapienza

Scientific Report – Non Equilibrium Dynamics and ComplexityPolymeric Elements For Adaptive NetworksWe consider an adaptive network to be a system ofinput and output electrodes, connected through acomplex net of nonlinear elements and “intelligent”wires, providing numerous possible pathways forsignal propagation from each input to each output.Characteristic feature of the network is the possibilityof the establishing preferential pathways accordingto the previous experience of the system (“learning”)and to the training procedure performed by externalaction. Thus, a specific output signal will appear incorrespondence with a given input signal or asequence of input signals. However, to be reallyadaptive, the network must have temporal evolutionof these connections, and must allow the variation ofthe input-output relationships according to the“learning” or if the new information from the externaltraining appears (“teaching”). A final feature of thenetwork is its topological complexity: such parametershould influence strongly the efficiency of theaforementioned processes.The only known perfectly working adaptive system,namely, the neuron network of biological cognitivesystems, is constructed from organic molecules anduses electrochemical principles for most of itsfunctioning. Furthermore, the adaptive mechanismswe wish to consider are conceptually similar to theso-called Hebbian rule [1] which is at the basis ofmodern neuroscience. Thus it is of interest to searchfor an organic complex adaptive network inspired byneurosystems.Within this general research program, we haveobtained the following results:1. We have fabricated and characterized anelectrochemically controlled non linear polymericheterostructure [2] Such structure should mimic inCurrent (A)7.0E-086.0E-085.0E-080.0E+00 2.0E+03 4.0E+03 6.0E+03 8.0E+03Time (s)Fig. 2: Temporal behaviour of the current of thepolymeric analog of generating neuron.our network the functional behavior of synapses inbiological cognitive systems. In particular, we havefound an asymmetric behavior in the time relaxationof the electrochemically controlled current, which isessential for the adaptive behavior we seek.2. We have shown that our device, with some smallbut essential modifications, can have self-sustainingcurrent oscillations for constant applied bias. Thismakes our device analogous to the so-calledgenerating neurons. In the case of the pond snail,Lymnaea stagnalis, which we chose as our biologicalbenchmark, this corresponds to the N1M neuron [3].Furthermore, we have some preliminary evidencethat such oscillations may be similar to the wellknown Bielousov-Zhavatinski reaction [4].3. We have also verified the possibility of usingstatistical assembly to create mixed networks of ourbasic polymeric components, namely doped PEO anddoped PANI fibers, in which due to sufficiently highcomplexity the probability of the occurrence ofjunctions with the same characteristics of ourfabricated PEO-PANI heterojunction is high [5].bReferences[1] D.O. Hebb, The organization of behavior: Aneuropsychological Theory, Wiley Sons, NY (1961).[2] V. Erokhin, Y. Berzina, and M.P. Fontana, J. Appl.Phys., 97, 064501 (2005).[3] V.A. Straub, K. Staras, G. Kemenes and P.R.Benjamin, J. Neurophysiol., 88, 1569 (2002).[4] V. Erokhin, T. Berzina, M.P. Fontana, Crystallogr.Rep., in press (2006).[5] V. Erokhin, T. Berzina, P. Camorani, M.P.Fontana, manuscript submittedAuthorsV. Erokhin, T. Berzina, and M.P. FontanaUniversity of ParmaCRS SOFT CNR-INFMFig. 1: Temporal behaviour of the current of thepolymeric synapses analog for positive (a) andnegative (b) bias.SOFT Scientific Report 2004-0670