4.2 Article

Emulating the short-term plasticity of a biological synapse with a ruthenium complex-based organic mixed ionic-electronic conductor

Journal

MATERIALS ADVANCES
Volume 3, Issue 6, Pages 2827-2837

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/d1ma01078f

Keywords

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Funding

  1. Korea Institute of Science and Technology [2E31031, 2E31041]
  2. National Research Foundation of Korea (NRF) [NRF-2019M3F3A1A02072175, NRF2021M3F3A2A01037738]

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This study presents an organic mixed ionic-electronic conductor (OMIEC) memristor that mimics the short-term plasticity (STP) of biological synapses. By controlling the ion conductivity of the active layer, the behavior of neurotransmitters is emulated. The addition of salt influences the short-term memory behavior, making it similar to biological synapses. This memristor can be employed in SPICE simulations to modulate the spike-timing-dependent synaptic plasticity learning rule.
Short-term plasticity (STP) is a phenomenon in the biological brain where the synaptic weight changes depending solely on the presynaptic activity in the biological brain. STP is an essential brain function for processing of short-term temporal information. Implementation of STP as an electronic device requires mimicking the dynamic behavior of calcium-induced neurotransmitters at presynaptic terminals. This study provides an organic mixed ionic-electronic conductor (OMIEC) memristor based on Ru(bpy)(3)(PF6)(2) as an organic active layer to mimic the STP of a biological synapse. The behavior of the neurotransmitters was emulated through the drift and diffusion of mobile ions in the OMIEC active layer. The ion conductivity of the OMIEC memristor was tuned by adding the LiClO4 salt, which affects the short-term memory behavior. Specifically, our OMIEC memristor exhibited a timescale of paired-pulse facilitation decay similar to that of biological synapses with the addition of 2 wt% salt. Furthermore, the device containing 2 wt% LiClO4 showed similar recovery timescales to a biological synapse when 4 + 1 spikes were applied for emulating the short-term synaptic plasticity. Lastly, our OMIEC memristors were employed as the STP component of a SPICE simulation to modulate the spike-timing-dependent synaptic plasticity learning rule by combining with a non-volatile memristor.

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