Seeing smarter with a light-controlled synaptic device

A thin-film, flexible optical device that mimics the way the human brain senses and interprets visual information has been developed by KAUST researchers^[1]. This “optical synapse” may help address the growing need for more efficient artificial vision systems.

“Today’s cameras and computers usually separate sensing, memory, and processing into different parts, which requires data to move back and forth constantly, wasting both time and energy,” explains Manoj Kumar Rajbhar, who worked on the project supervised by Nazek El-Atab. “Our goal was to move closer to the human visual system, where sensing and processing are tightly linked.”

Previous designs for light-sensitive synaptic devices required both electrical and optical signals to operate. They were composed of complex ‘stacks’ of materials, or utilized unstable compounds such as perovskites or black phosphorus. Rajbhar and colleagues designed a synaptic device controlled entirely by light, improving energy efficiency and eliminating the need for electrical signals. Exposure to different colors of light can strengthen or weaken their device’s response, similar to how synapses in the human brain behave during learning.

“In the brain, synapses don’t only become stronger, they can also become weaker,” says Rajbhar. “That balance is essential for learning new information, filtering noise, forgetting unimportant signals, and adapting to changing environments.”

For example, the researchers imitated the classic Pavlov’s dog experiment, in which a dog learns to associate the sound of a bell with food and begins salivating in response. By using one wavelength of light to represent a bell and another to represent food, they trained the device to associate the ‘bell’ signal with ‘food’ and initiate a ‘salivation’ response.

“This type of training is especially valuable for future machine vision and neuromorphic hardware, because it allows the device to process visual information in a more brain-like way,” says Rajbhar. “Practically, this helps systems become more adaptive and better at tasks such as recognition, memory formation, and decision-making without relying on separate sensing and processing units.”

The team also simplified their device’s structure by using an ultrathin layer of manganese oxide on a flexible silicon substrate. The device works even when the silicon substrate is bent. Manganese oxide is relatively abundant and affordable, supporting future scalability. It is also more environmentally friendly than some other potential materials and hosts multiple oxidation states.

“These mixed oxidation states help create controllable defect states and oxygen vacancies, which are important for tuning how the device stores and modulates information,” says Rajbhar. “We consider these features to play an important role in the light response and memory behavior of the device.”

Their device is capable of real-time image detection and processing, and preforms logical operations compatible with existing semiconductor computing.

“This device could be useful where there is a need for lightweight, low-power systems that can sense visual information and process it locally,” says El-Atab. “Our results support advances in AI hardware, robotics, wearable electronics, and artificial vision. The study also aligns with Saudi Arabia’s Vision 2030 goals in advanced technology and semiconductor research.”