Efforts to design devices emulating complex cognitive abilities and response processes of
biological systems have long been a coveted goal. Recent advancements in flexible …

Neuromorphic computing can potentially solve the von Neumann bottleneck of current
mainstream computing because it excels at self‐adaptive learning and highly parallel …

Associative learning, a critical learning principle to improve an individual's adaptability, has
been emulated by few organic electrochemical devices. However, complicated bias …

Optoelectronic synaptic devices that mimic biological synapses are critical building blocks of
artificial neural networks (ANN) based on optoelectronic integration. Here it is shown that an …

Sensory memory, formed at the beginning while perceiving and interacting with the
environment, is considered a primary source of intelligence. Transferring such biological …

Optoelectronic memristors (OMs) have emerged as a promising optoelectronic
Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic …

Modelling the human brain as a complex network has provided a powerful mathematical
framework to characterize the structural and functional architectures of the brain. In the past …

Abstract Information processing in the brain takes place in a network of neurons that are
connected with each other by an immense number of synapses. At the same time, neurons …

The progress of neural synaptic devices is experiencing an era of explosive growth. Given
that the traditional storage system has yet to overcome the von Neumann bottleneck, it is …

Synaptic transistors stimulated by light waves or photons may offer advantages to the
devices, such as wide bandwidth, ultrafast signal transmission, and robustness. However …