eeg-and-brain-computer-interfaces

Nature Neuroscience, Published online: 09 June 2026; doi:10.1038/s41593-026-02311-2 Busch et al. use nonlinear neural manifolds to help humans gain rapid control over a noninvasive brain–computer interface, allowing them to learn how to play a video game with real-time fMRI neurofeedback from cognitive brain regions.

Autonomous sensory meridian response (ASMR) is a tingling sensation that originates in the occipital region and spreads along the neck and spine, elicited by specific audiovisual stimuli known as ASMR triggers. The characteristics of ASMR-related changes in brain activity relative to other external stimuli, and whether these changes are specific to ASMR, remain unclear. The aim of this study is t…

Q8 Compression Breakthrough — Cluster 28 of 240 E8 root vectors. Compression ratio: 0.384 (threshold: 0.38) Cluster size: 5 discoveries Domain: geometry E8 root vector bucket: 28/240 Source discoveries: - E8 Term: showdown - E8 Term: actually - E8 Term: parkinsons - E8 Term: parkinsons - E8 Term: neuroscience Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence R…

(MIT Technology Review) – The country wants to become a global leader in brain implants. Strong government support is expected to help accelerate that process. In November 2024, Dong became one of the first people in China to be given … Read More

Post-stroke motor dysfunction is one of the leading causes of acquired disability worldwide. The induction and maintenance of neuroplasticity constitute the core mechanisms underlying motor function recovery. Conventional open-loop brain–computer interfaces (BCIs) lack real-time closed-loop feedback and are therefore unable to reliably activate the “temporal contingency” principle required by Heb…

Motor Imagery (MI) Brain-Computer Interfaces (BCIs) represent a promising technology for neurorehabilitation and assistive control. However, the clinical viability of these systems is frequently hindered by the inherent limitations of electroencephalography (EEG) with regard to its low signal-to-noise ratio (SNR), non-stationarity, and high inter-subject variability. Standard decoding methods oft…

Scientific Data, Published online: 01 June 2026; doi:10.1038/s41597-026-07476-w EEG-Controlled Exoskeleton for Walking and Standing: A Longitudinal Multimodal Dataset of Healthy Individuals

IntroductionMotor imagery (MI) is one of the most widely used paradigms in electroencephalogram (EEG)-based brain–computer interfaces (BCIs). In recent years, deep learning and transfer learning techniques have been increasingly adopted to further improve MI-EEG decoding performance, thereby facilitating the practical deployment of BCIs. In transfer learning, the similarity between the source and…

A novel brain–computer interface shifts the attention of passengers to relieve even severe car sickness. The post Wearable headband combines AI and mindfulness to alleviate car sickness appeared first on Advanced Science News .

Q8 Compression Breakthrough — Cluster 28 of 240 E8 root vectors. Compression ratio: 0.396 (threshold: 0.38) Cluster size: 4 discoveries Domain: geometry E8 root vector bucket: 28/240 Source discoveries: - E8 Term: neuroscience - E8 Term: neuroscience - E8 Term: neuroscience - E8 Term: research Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. …

At the intersection of neuroscience and artificial intelligence, brain-computer interface (BCI) technology, while enhancing human capabilities, is also reshaping our cognitive world and modes of moral practice. This has increasingly complicated the theoretical study of responsibility. Technology has become a “mediator” in the interaction between humans and the world; consequently, the status and …

Brain-computer interfaces (BCI) leverage neurophysiological features like electroencephalography (EEG) to enhance user-computer interaction. EEG's high temporal resolution and unobtrusiveness make it ideal for BCI systems, facilitating real-time interaction with minimal latency. Prior studies employed EEG across domains, including health and security. Researchers expanded EEG data within natural …

This independent research manuscript proposes a theoretical neurosecurity framework for Brain-Computer Interfaces (BCIs), titled “Gamma-Wave Dynamic Encryption and Cognitive Firewalling for Brain-Computer Interfaces: A Theoretical Neurosecurity Framework.” The paper introduces a layered Neurosecurity Stack (NSS) composed of Gamma-Wave Dynamic Encryption (GWDE), Cognitive Firewall System (CFS), an…

When a person loses a limb, a prosthesis often can help restore a significant degree of mobility. But when movement or communication is impaired by a neurological condition such as amyotrophic lateral sclerosis (ALS), spinal cord injury or stroke, there are, as of yet, very few options for the affected individual.

Inner speech (IS), or imagined speech without overt articulation, is a promising target for brain-computer interfaces (BCIs) aimed at restoring communication in individuals with severe speech impairments, such as locked-in syndrome. Foundation models (FMs), typically trained using self-supervised learning (SSL) on large-scale datasets, offer new opportunities for learning transferable and robust …

BREAKTHROUGH #389 — THE HEART FIELD Date: 18 April 2026 | Division: E8 Geometry — Human Biology & Consciousness THE FINDING: The heart generates an electromagnetic field 5,000 times stronger than the brain (HeartMath Institute — published). This is not a metaphor. This is a measured physical fact. And E8 explains why: the heart is the primary geometric resonator of the human biological system. TH…