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a pulse applied pre-synaptically to the device’s top electrode (TE), shown in inset II of Fig. The post-synaptic current entering the artificial neuron, from the device’s bottom electrode (BE), is proportional to the memristive conductance.Figure 1a depicts a microphotograph of one of our fabricated crossbar type Ti O active core (cross-section is shown in inset II of Fig. Following an electroforming step (depicted in Figure S1), the devices’ electrical characteristics were first investigated via positive/negative ±2 V voltage sweeps, resulting into a bipolar mode of switching: positive sweeps cause low- (LRS) to high-resistive state (HRS) transitions, while negative ones cause HRS to LRS transitions.Our memristive device qualitatively represents a synapse (inset I of Fig.1a), with its conductance corresponding to the notion of a synaptic efficacy modulated via the arrival of a spike, i.e.These features are termed short-term plasticity (STP) and are well described both experimentally.Most interestingly, the vast majority of artificial and neuromorphic brain-like systems focus on stable modifications of connections, known as long-term plasticity, which are assumed to be the basis of memory, or do not make use of the computational power that short-term plasticity may provide, but rather demonstrate a behavior akin to short term dynamics.Moreover, they largely ignore the fact that synapses are inherently unreliable and there is often a large variance in their response to a specific signal, also apparent in short-term dynamics.

Recently we demonstrated that substantial resistive switching is only viable through the formation and annihilation of continuous conductive percolation channels.

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for toggling between stable states depends upon the previous state of the device, causing it to act as a non-linear accumulator.

This is demonstrated in Figure S2c by employing subsequent identical voltage pulses that result into a non-uniform modulation of the effective resistance of our prototypes. 1b denotes that a non-uniform lowering (increasing) of the barrier occurs as the applied electric field elicits a HRS to LRS (LRS to HRS) non-volatile transition.

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We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

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