(Press-News.org)
Electroencephalography (EEG) is a fascinating non-invasive technique that measures and records the brain’s electrical activity. It detects small electrical signals produced when neurons in the brain communicate with each other, using electrodes placed at specific locations on the scalp that correspond to different regions of the brain. EEG has applications in various fields, from cognitive science and neurological disease diagnosis to robotic prosthetics development and brain-computer interfaces (BCI).
Different brain activities produce unique EEG signal patterns. One important example is motor imagery (MI)—a cognitive process in which specific brain regions are activated just by imagining movements, without any actual physical motion. This process generates stable and distinct EEG patterns. MI-EEG is a crucial component of BCI systems, serving as a valuable tool for prosthetic control and neurorehabilitation research. However, decoding MI-EEG signals is extremely challenging due to their low signal-to-noise ratio, high nonlinearity, and variability over time.
Traditionally, researchers have relied on machine learning methods to extract the temporal, spatial, and spectral features (frequency distribution and power variations) of MI-EEG signals for decoding. Recently, deep learning models have shown some promise for decoding MI-EEG signals; however, they still face several challenges in accurately capturing the complex nature of EEG data.
To overcome these challenges, Ph.D. student Chaowen Shen and Professor Akio Namiki, both from the Graduate School of Science and Engineering, Chiba University, Japan, have developed an innovative topology-aware multiscale feature fusion (TA-MFF) network. “Current deep learning models primarily extract spatiotemporal features from EEG signals, overlooking potential dependencies on spectral features,” explains Prof. Namiki. “Moreover, most methods extract only shallow topological features between electrode connections, limiting a deeper understanding of the spatial structure of EEG signals. Our approach introduces three new modules that effectively address these limitations.” Their study was made available online on September 26, 2025, and will be published in Volume 330, Part A of the journal Knowledge-Based Systems on November 25, 2025.
The TA-MFF network comprises a spatiotemporal network (ST-Net) and a spectral network (S-Net). It enhances MI-EEG signal decoding capability through the coordinated operation of three main modules: spectral-topological data analysis-processing (S-TDA-P) module, the inter-spectral recursive attention (ISRA) module, and the spectral-topological and spatiotemporal feature fusion (SS-FF) unit. Notably, the modules S-TDA-P and ISRA operate in parallel within the S-Net.
In S-Net, the Welch method is first used to convert the EEG signals into power spectral density representations, measuring how signal power is distributed across different frequencies. This helps reduce noise and simplifies the data. Then, the S-TDA-P module leverages persistent homology—a powerful computational tool for studying the topology of data—to extract deep spectral-topological relationships between different EEG electrodes and capture persistent patterns within the signals. Meanwhile, the ISRA module models correlations between the different frequency bands, highlighting key spectral features while suppressing redundant information.
Finally, the SS-FF unit integrates topological, spectral, and spatiotemporal features across the network. Unlike traditional approaches, where features from different domains are simply concatenated, it utilizes a two-step fusion strategy, first merging topological and spectral features and then integrating them with spatiotemporal features. This approach captures deep dependencies across feature domains.
As a result of these innovative techniques, the TA-MFF network achieves excellent classification performance on MI-EEG decoding tasks, outperforming state-of-the-art methods.
“Our approach holds strong potential for robust and efficient EEG-based MI decoding,” remarks Prof. Namiki. “I was interested in understanding how the brain controls movement and how this knowledge could be utilized to help people who are immobile. This research could help people control computers, wheelchairs, or robotic arms just by thinking, helping those with movement difficulties to live more independently.”
Overall, this innovative technique represents a major step toward more accurate and robust MI-EEG decoding, making everyday technology respond more naturally to our brain signals, including thoughts and emotions.
To see more news from Chiba University, click here.
About Professor Akio Namiki from Chiba University, Japan
Dr. Akio Namiki is currently a Professor at the Department of Mechanical Engineering, Graduate School of Engineering, Chiba University, Japan. He obtained his Master’s and Ph.D. from the University of Tokyo in 1996 and 1999, respectively. At Chiba University, he also leads the Namiki Laboratory, which focuses on the development of advanced computer vision systems. His research work has received over 3,300 citations to date. His research interests include high-speed vision systems, sensor fusion, and robotic manipulators, among others.
END
Researchers have long established that hormones significantly affect the brain, creating changes in emotion, energy levels, and decision-making. However, the intricacies of these processes are not well understood.
A new study by a team of scientists focusing on the female hormone estrogen further illuminates the nature of these processes. In a series of experiments with laboratory rats, it finds that the neurological mechanisms underlying learning and decision-making naturally fluctuate over the ...
Earth scientists have discovered how continents are slowly peeled from beneath, fuelling volcanic activity in an unexpected place: the oceans.
The research, led by the University of Southampton, shows how slivers of continents are slowly stripped from below and swept into the oceanic mantle – the hot, mostly solid layer beneath the ocean floor that slowly flows. Here, the continental material fuels volcanic activity for tens of millions of years.
The discovery solves a long-standing geological mystery: why many ocean islands far from plate tectonic ...
Many oceanic islands far from active plate tectonic boundaries contain materials that clearly originate from continents, even though they are located in the middle of an oceanic plate. Where do the continental remnants come from? Are they sediments that are recycled when oceanic plates subduct into the mantle? Or do they originate from the depths of the Earth's mantle and are carried upward by hot currents, known as mantle plumes? Both explanations are being discussed, but they fall short. This is because some volcanic regions show little evidence of crustal recycling, while others are too cool to be driven by mantle plumes.
Researchers at the University of Southampton and the GFZ Helmholtz ...
The discovery of a new mechanism of resistance to common antibiotics could pave the way for improved treatments for harmful bacterial infections, a study suggests.
Targeting this defence mechanism could aid efforts to combat antimicrobial resistance (AMR), one of the world’s most urgent health challenges, researchers say.
Findings from the study reveal how a repair system inside some bacteria plays a pivotal role in helping them survive commonly-used antibiotics.
Many of these drugs work by targeting the production of proteins essential for bacterial growth and survival.
Now, researchers from the University of Edinburgh have identified ...
Reversed sex roles: In seahorses, it is the males who carry offspring to term. The females lay their eggs into a special brood pouch on the bellies of the males where they are fertilized by the male’s sperm. In the brood pouches, embryos are provided with nutrients and oxygen from the males' bodies until the males give live birth to small seahorses (viviparity). But how does this work? A German-Chinese research team led by evolutionary biologist Axel Meyer from the University of Konstanz and working in collaboration with Liu Yali and Lin Qiang from the South China Sea ...
Pore-forming proteins are found throughout nature. In humans, they play key roles in immune defense, while in bacteria they often act as toxins that punch holes in cell membranes. These biological pores allow ions and molecules to pass through membranes. Their unique ability to control molecular transport has also made them powerful nanopore tools in biotechnology, for example in DNA sequencing and molecular sensing.
Despite their importance and impact on biotechnology, biological nanopores can also ...
A new compound tested at the Miguel Hernández University of Elche (UMH) in Spain shows promising effects in reducing alcohol consumption and motivation to drink in mice, with marked sex-dependent differences in efficacy. Although MCH11 is not yet available for human use, it could pave the way for personalized treatments of alcohol use disorder.
The results, published in the journal Biomedicine & Pharmacotherapy, stem from four years of work by a team from the Institute of Neurosciences (a joint UMH–CSIC centre), the Institute for Health and Biomedical ...
A new study published in Environmental Research Letters finds that continued growth in artificial intelligence (AI) use across the United States could add approximately 900,000 tonnes of CO₂ annually. This is not a small amount but equates to a relatively minor increase when viewed in the context of nationwide emissions.
While AI adoption is expected to boost productivity and economic output, researchers note that its environmental footprint can be seen as relatively modest compared to other industrial activities. The study examined potential AI integration across various sectors, estimating ...
NEW YORK, New York, USA, 11 November 2025 -- Perhaps the most intriguing implication of recent breakthrough research lies in an unexpected connection: the most rigorous mechanistic dissection of rapid antidepressant action identifies adenosine as the critical mediator, yet adenosine receptors are the primary target of caffeine, the world's most widely consumed psychoactive substance.
A commentary published today in Brain Medicine by Drs. Julio Licinio and Ma-Li Wong explores this striking convergence. Is this merely coincidence, or ...
Only around 1.1% of the world's population is vegan, but this percentage is growing. For example, in Germany the number of vegans approximately doubled between 2016 and 2020 to 2% of the population, while a 2.4-fold increase between 2023 and 2025 to 4.7% of the population has been reported in the UK. Many people cite health benefits as their reason to go vegan: moving from a typical Western diet to a vegan one can lower the risk of premature mortality from noncommunicable diseases by an estimated 18% to 21%.
Another excellent reason is to reduce your ecological footprint. Now, a study in Frontiers in Nutrition has calculated precisely how ...
