Tag Archives: Vaishnavi Krishnamurthi

Single chip mimics human vision and memory abilities

A June 15, 2023 RMIT University (Australia) press release (also on EurekAlert but published June 14, 2023) announces a neuromorphic (brainlike) computer chip, which mimics human vision and ‘creates’ memories,

Researchers have created a small device that ‘sees’ and creates memories in a similar way to humans, in a promising step towards one day having applications that can make rapid, complex decisions such as in self-driving cars.

The neuromorphic invention is a single chip enabled by a sensing element, doped indium oxide, that’s thousands of times thinner than a human hair and requires no external parts to operate.

RMIT University engineers in Australia led the work, with contributions from researchers at Deakin University and the University of Melbourne.

The team’s research demonstrates a working device that captures, processes and stores visual information. With precise engineering of the doped indium oxide, the device mimics a human eye’s ability to capture light, pre-packages and transmits information like an optical nerve, and stores and classifies it in a memory system like the way our brains can.

Collectively, these functions could enable ultra-fast decision making, the team says.

Team leader Professor Sumeet Walia said the new device can perform all necessary functions – sensing, creating and processing information, and retaining memories – rather than relying on external energy-intensive computation, which prevents real-time decision making.

“Performing all of these functions on one small device had proven to be a big challenge until now,” said Walia from RMIT’s School of Engineering.

“We’ve made real-time decision making a possibility with our invention, because it doesn’t need to process large amounts of irrelevant data and it’s not being slowed down by data transfer to separate processors.”

What did the team achieve and how does the technology work?

The new device was able to demonstrate an ability to retain information for longer periods of time, compared to previously reported devices, without the need for frequent electrical signals to refresh the memory. This ability significantly reduces energy consumption and enhances the device’s performance.

Their findings and analysis are published in Advanced Functional Materials.

First author and RMIT PhD researcher Aishani Mazumder said the human brain used analog processing, which allowed it to process information quickly and efficiently using minimal energy.

“By contrast, digital processing is energy and carbon intensive, and inhibits rapid information gathering and processing,” she said.

“Neuromorphic vision systems are designed to use similar analog processing to the human brain, which can greatly reduce the amount of energy needed to perform complex visual tasks compared with today’s technologies

What are the potential applications?

The team used ultraviolet light as part of their experiments, and are working to expand this technology even further for visible and infrared light – with many possible applications such as bionic vision, autonomous operations in dangerous environments, shelf-life assessments of food and advanced forensics.

“Imagine a self-driving car that can see and recognise objects on the road in the same way that a human driver can or being able to able to rapidly detect and track space junk. This would be possible with neuromorphic vision technology.”

Walia said neuromorphic systems could adapt to new situations over time, becoming more efficient with more experience.

“Traditional computer vision systems – which cannot be miniaturised like neuromorphic technology – are typically programmed with specific rules and can’t adapt as easily,” he said.

“Neuromorphic robots have the potential to run autonomously for long periods, in dangerous situations where workers are exposed to possible cave-ins, explosions and toxic air.”

The human eye has a single retina that captures an entire image, which is then processed by the brain to identify objects, colours and other visual features.

The team’s device mimicked the retina’s capabilities by using single-element image sensors that capture, store and process visual information on one platform, Walia said.

“The human eye is exceptionally adept at responding to changes in the surrounding environment in a faster and much more efficient way than cameras and computers currently can,” he said.

“Taking inspiration from the eye, we have been working for several years on creating a camera that possesses similar abilities, through the process of neuromorphic engineering.” 

Here’s a link to and a citation for the paper,

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation by Aishani Mazumder, Chung Kim Nguyen, Thiha Aung, Mei Xian Low, Md. Ataur Rahman, Salvy P. Russo, Sherif Abdulkader Tawfik, Shifan Wang, James Bullock, Vaishnavi Krishnamurthi. Advanced Functional Materials DOI: https://doi.org/10.1002/adfm.202303641 First published: 14 June 2023

This paper is open access.

Controlling neurons with light: no batteries or wires needed

Caption: Wireless and battery-free implant with advanced control over targeted neuron groups. Credit: Philipp Gutruf

This January 2, 2019 news item on ScienceDaily describes the object seen in the above and describes the problem it’s designed to solve,

University of Arizona biomedical engineering professor Philipp Gutruf is first author on the paper Fully implantable, optoelectronic systems for battery-free, multimodal operation in neuroscience research, published in Nature Electronics.

Optogenetics is a biological technique that uses light to turn specific neuron groups in the brain on or off. For example, researchers might use optogenetic stimulation to restore movement in case of paralysis or, in the future, to turn off the areas of the brain or spine that cause pain, eliminating the need for — and the increasing dependence on — opioids and other painkillers.

“We’re making these tools to understand how different parts of the brain work,” Gutruf said. “The advantage with optogenetics is that you have cell specificity: You can target specific groups of neurons and investigate their function and relation in the context of the whole brain.”

In optogenetics, researchers load specific neurons with proteins called opsins, which convert light to electrical potentials that make up the function of a neuron. When a researcher shines light on an area of the brain, it activates only the opsin-loaded neurons.

The first iterations of optogenetics involved sending light to the brain through optical fibers, which meant that test subjects were physically tethered to a control station. Researchers went on to develop a battery-free technique using wireless electronics, which meant subjects could move freely.

But these devices still came with their own limitations — they were bulky and often attached visibly outside the skull, they didn’t allow for precise control of the light’s frequency or intensity, and they could only stimulate one area of the brain at a time.

A Dec. 21, 2018 University of Azrizona news release (published Jan. 2, 2019 on EurekAlert), which originated the news item, discusses the work in more detail,

“With this research, we went two to three steps further,” Gutruf said. “We were able to implement digital control over intensity and frequency of the light being emitted, and the devices are very miniaturized, so they can be implanted under the scalp. We can also independently stimulate multiple places in the brain of the same subject, which also wasn’t possible before.”

The ability to control the light’s intensity is critical because it allows researchers to control exactly how much of the brain the light is affecting — the brighter the light, the farther it will reach. In addition, controlling the light’s intensity means controlling the heat generated by the light sources, and avoiding the accidental activation of neurons that are activated by heat.

The wireless, battery-free implants are powered by external oscillating magnetic fields, and, despite their advanced capabilities, are not significantly larger or heavier than past versions. In addition, a new antenna design has eliminated a problem faced by past versions of optogenetic devices, in which the strength of the signal being transmitted to the device varied depending on the angle of the brain: A subject would turn its head and the signal would weaken.

“This system has two antennas in one enclosure, which we switch the signal back and forth very rapidly so we can power the implant at any orientation,” Gutruf said. “In the future, this technique could provide battery-free implants that provide uninterrupted stimulation without the need to remove or replace the device, resulting in less invasive procedures than current pacemaker or stimulation techniques.”

Devices are implanted with a simple surgical procedure similar to surgeries in which humans are fitted with neurostimulators, or “brain pacemakers.” They cause no adverse effects to subjects, and their functionality doesn’t degrade in the body over time. This could have implications for medical devices like pacemakers, which currently need to be replaced every five to 15 years.

The paper also demonstrated that animals implanted with these devices can be safely imaged with computer tomography, or CT, and magnetic resonance imaging, or MRI, which allow for advanced insights into clinically relevant parameters such as the state of bone and tissue and the placement of the device.

This image of a combined MRI (magnetic resonance image) and CT (computer tomography) scan bookends, more or less, the picture of the device which headed this piece,

Combined image analysis with MRI and CT results superimposed on a 3D rendering of the animal implanted with the programmable bilateral multi µ-ILED device. Courtesy: University of Arizona

Here’s a link to and a citation for the paper,

Fully implantable optoelectronic systems for battery-free, multimodal operation in neuroscience research by Philipp Gutruf, Vaishnavi Krishnamurthi, Abraham Vázquez-Guardado, Zhaoqian Xie, Anthony Banks, Chun-Ju Su, Yeshou Xu, Chad R. Haney, Emily A. Waters, Irawati Kandela, Siddharth R. Krishnan, Tyler Ray, John P. Leshock, Yonggang Huang, Debashis Chanda, & John A. Rogers. Nature Electronics volume 1, pages652–660 (2018) DOI: https://doi.org/10.1038/s41928-018-0175-0 Published 13 December 2018

This paper is behind a paywall.