Synaptic Suppression Triplet‐STDP Learning Rule Realized in Second‐Order Memristors

Abstract

The synaptic weight modification depends not only on interval of the pre-/ postspike pairs according to spike-timing dependent plasticity (classical pair-STDP), but also on the timing of the preceding spike (triplet-STDP). Triplet-STDP reflects the unavoidable interaction of spike pairs in natural spike trains through the short-term suppression effect of preceding spikes. Second-order memristors with one state variable possessing short-term dynamics work in a way similar to the biological system. In this work, the suppression triplet-STDP learning rule is faithfully demonstrated by experiments and simulations using second-order memristors. Furthermore, a leaky-integrate-and-fire (LIF) neuron is simulated using a circuit constructed with second-order memristors. Taking the advantage of the LIF neuron, various neuromimetic dynamic processes, including local graded potential leaking out, postsynaptic impulse generation and backpropagation, and synaptic weight modification according to the suppression triplet-STDP rule, are realized. The realized weight-dependent pairand triplet-STDP rules are clearly in line with findings in biology. The physically realized triplet-STDP rule is powerful in developing direction and speed selectivity for complex pattern recognition and tracking tasks. These scalable artificial synapses and neurons realized in second-order memristors can intrinsically capture the neuromimetic dynamic processes; they are the promising building blocks for constructing brain-inspired computation systems.

Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices

“…The different device fabrication methods and electrodes may be responsible for the different memristive behaviors. A similar Schottky barrier based memristive mechanism was reported in our previous work and other literature 22,36,44,48 .…”

Flexible and Energy-Efficient Synaptic Transistor with Quasi-Linear Weight Update Protocol by Inkjet Printing of Orientated Polar-Electret/High- k Oxide Composite Dielectric

“…According to the empirical relationship of spike time-related plasticity, the dependence of synaptic weight changes on the Δ t pre-post can be described as follows: G ( Δ t pre‐post ) = { true A + nobreak0em0.25em⁡ normalexp ( Δ t pre‐post τ + ) goodbreak0em1em⁣ if Δ t normalpre‐post .25em ≥ 0 A − nobreak0em0.25em⁡ normalexp ( Δ t pre‐post τ − ) goodbreak0em1em⁣ if Δ t normalpre‐post .25em < 0 where A + , τ + and A – , τ – are the scaling factors and time constants for the positive and negative Δ t pre-post , respectively. The calculated results of τ + = 28.5 ms and τ – = −30.8 ms are similar to the time scales of STDP in a typical biological system . The successful implementation of STDP provides a novel working model for the development of neuromorphic systems …”

Transferable and Flexible Artificial Memristive Synapse Based on WOx Schottky Junction on Arbitrary Substrates

“…The continuous tuning of device conductance can be attributed to the modulation of Pt/WO x Schottky barrier height. This mechanism has been partially demonstrated in some previous publications . In our device, the oxygen ions driven by the external field will migrate towards the Pt electrode and further accumulate at the Pt/WO x interfaces, which can downshift the Fermi level near the WO x surface.…”