Title :
Connecting spiking neurons to a spiking memristor network changes the memristor dynamics
Author :
Gater, Deborah ; Iqbal, Azlan ; Davey, Jay ; Gale, Ella
Author_Institution :
Khalifa Univ. of Sci., Technol. & Res., Abu Dhabi, United Arab Emirates
Abstract :
Memristors have been suggested as neuromorphic computing elements. Spike-time dependent plasticity and the Hodgkin-Huxley model of the neuron have both been modelled effectively by memristor theory. The d.c. response of the memris-tor is a current spike. Based on these three facts we suggest that memristors are well-placed to interface directly with neurons. In this paper we show that connecting a spiking memristor network to spiking neuronal cells causes a change in the memristor network dynamics by: causing a change in current decay rate consistent with a change in memristor state; presenting more-linear I-t dynamics; and increasing the memristor spiking rate, as a consequence of interaction with the spiking neurons. This demonstrates that neurons are capable of communicating directly with memristors, without the need for computer translation.
Keywords :
memristors; neural nets; Hodgkin-Huxley model; dc response; decay rate; linear I-t dynamics; memristor network dynamics; neuromorphic computing elements; spike-time dependent plasticity; spiking memristor network; spiking neuronal cells; spiking rate; Computational modeling; Current measurement; Electrodes; Joining processes; Memristors; Neuromorphics; Neurons;
Conference_Titel :
Electronics, Circuits, and Systems (ICECS), 2013 IEEE 20th International Conference on
Conference_Location :
Abu Dhabi
DOI :
10.1109/ICECS.2013.6815469