.png){kind=icon}
.png){kind=icon}
Return
Emulation of biphasic plasticity in retinal electrical synapses for light-adaptive pattern pre-processing
.png){kind=icon}
PRE
AI
DOI：10.1039/d0nr08012h.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Electrical synapses provide rapid, bidirectional communication in nervous systems, accomplishing tasks distinct from and complementary to chemical synapses. Here, we demonstrate an artificial electrical synapse based on second-order conductance transition (SOCT) in an Ag-based memristor for the first time. High-resolution transmission electron microscopy indicates that SOCT is mediated by the virtual silver electrode. Besides the conventional chemical synaptic behaviors, the biphasic plasticity of electrical synapses is well emulated by integrating the device with a photosensitive element to form an optical pre-processing unit (OPU), which contributes to the retinal neural circuitry and is adaptive to ambient illumination. By synergizing the OPU and spiking neural network (SNN), adaptive pattern recognition tasks are accomplished under different light and noise settings. This work not only contributes to the further completion of synaptic behaviour for hardware-level neuromorphic computing, but also potentially enables image pre-processing with light adaptation and noise suppression for adaptive visual recognition.
Keywords:
RESISTIVE SWITCHING MEMORY
LONG-TERM POTENTIATION
AII AMACRINE CELL
DEPENDENT PLASTICITY
GAP-JUNCTIONS
CLASSIFICATION
BEHAVIORS
DEVICE
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.