The lobula giant movement detector (LGMD) is the movement-sensitive, wide-field visual neuron positioned in the third visual neuropile of lobula. LGMD neuron can anticipate collision and trigger avoidance efficiently owing to the earlier occurring firing peak before collision. Vision chips inspired by the LGMD have been successfully implemented in very-large-scale-integration (VLSI) system. However, transistor-based chips and single devices to simulate LGMD neurons make them bulky, energy-inefficient and complicated. The devices with relatively compact structure and simple operation mode to mimic the escape response of LGMD neuron have not been realized yet. Here, the artificial LGMD visual neuron is implemented using light-mediated threshold switching memristor. The non-monotonic response to light flow field originated from the formation and break of Ag conductive filaments is analogue to the escape response of LGMD neuron. Furthermore, robot navigation with obstacle avoidance capability and biomimetic compound eyes with wide field-of-view (FoV) detection capability are demonstrated.

The recent achievements in luminescent nanomaterials used in optical and optoelectronic data storage have been reviewed.

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By virtue of energy efficiency, high speed, and parallelism, brain‐inspired neuromorphic computing is a promising technology to overcome the von Neumann bottleneck and capable of processing massive sophisticated tasks in the background of big data. The abilities of perceiving and reacting to events in artificial neuromorphic systems allow us to build the communicative electronic–biological interfaces to get closer to electronic life. Protein materials offer great application potentials in such a system due to their sustainability, low cost, controllable hierarchical structure, intrinsic biocompatibility, and biodegradability. Herein, a timely review of the development of protein‐based memories for data storage and neuromorphic computing is provided. Proteins’ unique mechanical, electronic, optical properties, and their broad applications are discussed. Then, the progress of protein‐based two‐terminal memristor and three‐terminal transistor‐type memory is reviewed, and their applications for data storage, logic circuit, and neuromorphic computing are introduced. Finally, the major challenges and outlook toward the future developing directions of protein‐based computing systems are pointed out.

Resistive random access memory (RRAM) based on hybrid organic-inorganic halide perovskite (HOIP) has recently gained significant interests due to its low activation energy of ion migration. HOIP RRAM has been...