Tag Archives: Kun Wang

Memristor-based brain-computer interfaces (BCIs)

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Brief digression: For anyone unfamiliar with memristors, they are, for want of better terms, devices or elements that have memory in addition to their resistive properties. (For more see: R Jagan Mohan Rao’s undated article ‘What is a Memristor? Principle, Advantages, Applications” on InsstrumentalTools.com)

A March 27,2025 news item on ScienceDaily announces a memristor-enhanced brain-computer interface (BCI),

Summary: Researchers have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). This research presents an innovative approach for implementing energy-efficient adaptive neuromorphic decoders in BCIs that can effectively co-evolve [emphasis mine] with changing brain signals.

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So, the decoder in the BCI will ‘co-evolve’ with your brain? hmmm Also, where is this ‘memristor chip’? The video demo (https://assets-eu.researchsquare.com/files/rs-3966063/v1/7a84dc7037b11bad96ae0378.mp4) shows a volunteer wearing cap attached by cable to an intermediary device (an enlarged chip with a brain on it?) which is in turn attached to a screen. I believe some artistic licence has been taken with regard to the brain on the chip..

Caption: Researchers propose an adaptive neuromorphic decoder supporting brain-machine co-evolution. Credit: The University of Hong Kong

A March 25, 2025 University of Hong Kong (HKU) press release (also on EurekAlert but published on March 26, 2025), which originated the news item, explains more about memristors, BCIs, and co-evolution,

Professor Ngai Wong and Dr Zhengwu Liu from the Department of Electrical and Electronic Engineering at the Faculty of Engineering at the University of Hong Kong (HKU), in collaboration with research teams at Tsinghua University and Tianjin University, have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). Published in Nature Electronics, this research presents an innovative approach for implementing energy-efficient adaptive neuromorphic decoders in BCIs that can effectively co-evolve with changing brain signals.

A brain-computer interface (BCI) is a computer-based system that creates a direct communication pathway between the brain and external devices, such as computers, allowing individuals to control these devices or applications purely through brain activity, bypassing the need for traditional muscle movements or the nervous system. This technology holds immense potential across a wide range of fields, from assistive technologies to neurological rehabilitation. However, traditional BCIs still face challenges.

“The brain is a complex dynamic system with signals that constantly evolve and fluctuate. This poses significant challenges for BCIs to maintain stable performance over time,” said Professor Wong and Dr Liu. “Additionally, as brain-machine links grow in complexity, traditional computing architectures struggle with real-time processing demands.”

The collaborative research addressed these challenges by developing a 128K-cell memristor chip that serves as an adaptive brain signal decoder. The team introduced a hardware-efficient one-step memristor decoding strategy that significantly reduces computational complexity while maintaining high accuracy. Dr Liu, a Research Assistant Professor in the Department of Electrical and Electronic Engineering at HKU, contributed as a co-first author to this groundbreaking work.

In real-world testing, the system demonstrated impressive capabilities in a four-degree-of-freedom drone flight control task, achieving 85.17% decoding accuracy—equivalent to software-based methods—while consuming 1,643 times less energy and offering 216 times higher normalised speed than conventional CPU-based systems.

Most significantly, the researchers developed an interactive update framework that enables the memristor decoder and brain signals to adapt to each other naturally. This co-evolution, demonstrated in experiments involving ten participants over six-hour sessions, resulted in approximately 20% higher accuracy compared to systems without co-evolution capability.

“Our work on optimising the computational models and error mitigation techniques was crucial to ensure that the theoretical advantages of memristor technology could be realised in practical BCI applications,” explained Dr Liu. “The one-step decoding approach we developed together significantly reduces both computational complexity and hardware costs, making the technology more accessible for a wide range of practical scenarios.”

Professor Wong further emphasised, “More importantly, our interactive updating framework enables co-evolution between the memristor decoder and brain signals, addressing the long-term stability issues faced by traditional BCIs. This co-evolution mechanism allows the system to adapt to natural changes in brain signals over time, greatly enhancing decoding stability and accuracy during prolonged use.”

Building on the success of this research, the team is now expanding their work through a new collaboration with HKU Li Ka Shing Faculty of Medicine and Queen Mary Hospital to develop a multimodal large language model for epilepsy data analysis.

“This new collaboration aims to extend our work on brain signal processing to the critical area of epilepsy diagnosis and treatment,” said Professor Wong and Dr Liu. “By combining our expertise in advanced algorithms and neuromorphic computing with clinical data and expertise, we hope to develop more accurate and efficient models to assist epilepsy patients.”

The research represents a significant step forward in human-centred hybrid intelligence, which combines biological brains with neuromorphic computing systems, opening new possibilities for medical applications, rehabilitation technologies, and human-machine interaction.

The project received support from the RGC Theme-based Research Scheme (TRS) project T45-701/22-R, the STI 2030-Major Projects, the National Natural Science Foundation of China, and the XPLORER Prize.

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

A memristor-based adaptive neuromorphic decoder for brain–computer interfaces by Zhengwu Liu, Jie Mei, Jianshi Tang, Minpeng Xu, Bin Gao, Kun Wang, Sanchuang Ding, Qi Liu, Qi Qin, Weize Chen, Yue Xi, Yijun Li, Peng Yao, Han Zhao, Ngai Wong, He Qian, Bo Hong, Tzyy-Ping Jung, Dong Ming & Huaqiang Wu. Nature Electronics volume 8, pages 362–372 (2025) DOI: https://doi.org/10.1038/s41928-025-01340-2 Published online: 17 February 2025 Issue Date: April 2025

This paper is behind a paywall.

Words from the press release like “… human-centred hybrid intelligence, which combines biological brains with neuromorphic computing systems …” put me in mind of cyborgs.

The world’s smallest diode is made from a single molecule

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Both the University of Georgia (US) and the American Associates Ben-Gurion University of the Negev (Israel) have issued press releases about a joint research project resulting in the world’s smallest diode.

I stumbled across the April 4, 2016 University of Georgia news release on EurekAlert first,

Researchers at the University of Georgia and at Ben-Gurion University in Israel have demonstrated for the first time that nanoscale electronic components can be made from single DNA molecules. Their study, published in the journal Nature Chemistry, represents a promising advance in the search for a replacement for the silicon chip.

The finding may eventually lead to smaller, more powerful and more advanced electronic devices, according to the study’s lead author, Bingqian Xu.

“For 50 years, we have been able to place more and more computing power onto smaller and smaller chips, but we are now pushing the physical limits of silicon,” said Xu, an associate professor in the UGA College of Engineering and an adjunct professor in chemistry and physics. “If silicon-based chips become much smaller, their performance will become unstable and unpredictable.”

To find a solution to this challenge, Xu turned to DNA. He says DNA’s predictability, diversity and programmability make it a leading candidate for the design of functional electronic devices using single molecules.

In the Nature Chemistry paper, Xu and collaborators at Ben-Gurion University of the Negev describe using a single molecule of DNA to create the world’s smallest diode. A diode is a component vital to electronic devices that allows current to flow in one direction but prevents its flow in the other direction.

Xu and a team of graduate research assistants at UGA isolated a specifically designed single duplex DNA of 11 base pairs and connected it to an electronic circuit only a few nanometers in size. After the measured current showed no special behavior, the team site-specifically intercalated a small molecule named coralyne into the DNA. They found the current flowing through the DNA was 15 times stronger for negative voltages than for positive voltages, a necessary feature of a diode.

“This finding is quite counterintuitive because the molecular structure is still seemingly symmetrical after coralyne intercalation,” Xu said.

A theoretical model developed by Yanantan Dubi of Ben-Gurion University indicated the diode-like behavior of DNA originates from the bias voltage-induced breaking of spatial symmetry inside the DNA molecule after the coralyne is inserted.

“Our discovery can lead to progress in the design and construction of nanoscale electronic elements that are at least 1,000 times smaller than current components,” Xu said.

The research team plans to continue its work, with the goal of constructing additional molecular devices and enhancing the performance of the molecular diode.

The April 4, 2016 American Associates Ben-Gurion University of the Negev press release on EurekAlert covers much of the same ground while providing some new details,

The world’s smallest diode, the size of a single molecule, has been developed collaboratively by U.S. and Israeli researchers from the University of Georgia and Ben-Gurion University of the Negev (BGU).

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“Creating and characterizing the world’s smallest diode is a significant milestone in the development of molecular electronic devices,” explains Dr. Yoni Dubi, a researcher in the BGU Department of Chemistry and Ilse Katz Institute for Nanoscale Science and Technology. “It gives us new insights into the electronic transport mechanism.”

Continuous demand for more computing power is pushing the limitations of present day methods. This need is driving researchers to look for molecules with interesting properties and find ways to establish reliable contacts between molecular components and bulk materials in an electrode, in order to mimic conventional electronic elements at the molecular scale.

An example for such an element is the nanoscale diode (or molecular rectifier), which operates like a valve to facilitate electronic current flow in one direction. A collection of these nanoscale diodes, or molecules, has properties that resemble traditional electronic components such as a wire, transistor or rectifier. The emerging field of single molecule electronics may provide a way to overcome Moore’s Law– the observation that over the history of computing hardware the number of transistors in a dense integrated circuit has doubled approximately every two years – beyond the limits of conventional silicon integrated circuits.

Prof. Bingqian Xu’s group at the College of Engineering at the University of Georgia took a single DNA molecule constructed from 11 base pairs and connected it to an electronic circuit only a few nanometers in size. When they measured the current through the molecule, it did not show any special behavior. However, when layers of a molecule called “coralyne,” were inserted (or intercalated) between layers of DNA, the behavior of the circuit changed drastically. The current jumped to 15 times larger negative vs. positive voltages–a necessary feature for a nano diode. “In summary, we have constructed a molecular rectifier by intercalating specific, small molecules into designed DNA strands,” explains Prof. Xu.

Dr. Dubi and his student, Elinor Zerah-Harush, constructed a theoretical model of the DNA molecule inside the electric circuit to better understand the results of the experiment. “The model allowed us to identify the source of the diode-like feature, which originates from breaking spatial symmetry inside the DNA molecule after coralyne is inserted.”

There’s an April 4, 2016 posting on the Nanoclast blog (on the IEEE [Institute of Electrical and Electronics Engineers] website) which provides a brief overview and a link to a previous essay, Whatever Happened to the Molecular Computer?

Here’s a link and citation for the paper,

Molecular rectifier composed of DNA with high rectification ratio enabled by intercalation by Cunlan Guo, Kun Wang, Elinor Zerah-Harush, Joseph Hamill, Bin Wang, Yonatan Dubi, & Bingqian Xu. Nature Chemistry (2016) doi:10.1038/nchem.2480 Published online 04 April 2016

This paper is behind a paywall.