Multi-neuron connection using multi-terminal floating-gate memristor for unsupervised learning.

ABSTRACT: Multi-terminal memristor and memtransistor (MT-MEMs) has successfully performed complex functions of heterosynaptic plasticity in synapse. However, theses MT-MEMs lack the ability to emulate membrane potential of neuron in multiple neuronal connections. Here, we demonstrate multi-neuron connection using a multi-terminal floating-gate memristor (MT-FGMEM). The variable Fermi level (E_F) in graphene allows charging and discharging of MT-FGMEM using horizontally distant multiple electrodes. Our MT-FGMEM demonstrates high on/off ratio over 10⁵ at 1000 s retention about ~10,000 times higher than other MT-MEMs. The linear behavior between current (I_D) and floating gate potential (V_FG) in triode region of MT-FGMEM allows for accurate spike integration at

SUBMITTER: Won UY 

PROVIDER: S-EPMC10224934 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature