Articles tagged with Electroencephalography
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Researchers found that bilinguals process linguistic information in their second language automatically and simultaneously, using left temporo-parietal neural regions. The study uses EEG data to show that Russian primes increase reaction times for English targets, indicating cross-language activation.
By using the brain's visual response as feedback, researchers can reconstruct images of simple objects in real-time. The technique has potential applications in augmenting human capabilities and could one day be used to bring together human and artificial intelligence.
Researchers at University of Tokyo used machine learning-based analysis of scalp-recorded EEG to see when and where odors are processed in the brain. Unpleasant odors were found to be processed earlier than pleasant ones, suggesting potential early warning system against dangers.
Researchers at Eötvös Loránd University found that dogs with higher attachment scores spend more time in deep sleep and relax better in new environments. The study suggests a similarity between dog-owner relationships and human-child relationships.
Researchers create a new method for detecting diagnostic markers of epilepsy using EEG and MEG, enabling precise localisation of epileptogenic cortical structures. The biomimetic algorithm improves the effectiveness of neurosurgical interventions for epilepsy patients with resistant treatment.
Researchers found that dogs process human and canine vocalizations differently in their brains, responding to emotional content and distinct neural pathways. This groundbreaking study provides new insights into the neural functions of canine auditory perception.
Researchers developed personalised brain models to simulate patient response to deep brain stimulation for depression, improving efficacy by 50%. The models use individual EEG and MRI data to replicate brain response and pave the way for tailored treatment approaches.
A team of researchers from KAIST has developed a mind-reading system that can interpret arm movement directions from neural signals in the brain. The new system, based on a machine-learning algorithm and mathematical probability model, successfully classified arm movements in 24 directions in three-dimensional space.
Research finds that subconcussive head impacts in youth football can impair cognitive brain function, particularly in attention and processing sensitivity. The study used brain vital signs to track changes in brain function over time, providing a predictive relationship between head impact exposure and cognitive impairment.
Researchers at the University of Tsukuba investigated the effect of sevoflurane on sleep disturbance caused by systemic inflammation. Sevoflurane preconditioning promoted significant increases in REM sleep after LPS injection, while postconditioning had no effect.
Researchers at University of Gothenburg discover a link between micro-stress and increased blood pressure, identifying a brain area controlling conscious motor skills. The study opens the door to influencing BP spikes and preventing hypertension through training.
Neurobiologists demonstrated that humans can unconsciously distinguish between even very similar sounds, but often don't recognize these differences. The study used EEG to measure brain responses to stimuli and found that the brain reacts differently to local and global irregularities in sound sequences.
Researchers at the University of Eastern Finland have developed simpler measurement technologies for diagnosing sleep disorders, enabling more accurate analyses. The new methods use reusable sensors in home environments, reducing costs and increasing patient comfort.
Research reveals SARS-CoV-2 can enter the brain and affect neural function, leading to symptoms like headache, depression, and fatigue. Many people experience lingering cognitive or neurological problems months after initial recovery.
A team of neuroscientists at the Beckman Institute developed safety standards for multiband EEG-fMRI imaging, reducing heating risks and maintaining data quality. By establishing protocols to mitigate artifacts, they enabled the use of accelerated fMRI sequences with EEG recordings.
A new wearable brain-machine interface system allows users to imagine actions and wirelessly control wheelchairs, robotic arms, or other devices. The soft and comfortable wearable device offers improved signal acquisition and accuracy compared to existing BMI systems.
AI is transforming various aspects of life, such as road safety with EEG-based driver state estimation techniques and automatic image captioning for indexing large datasets. It also enhances surveillance tasks with cognitive memory-augmented networks, improving accuracy and reliability.
A new wearable electroencephalogram device gathers reliable sleep data from the ear, measuring neural signature stability over time. The study found a 90.1% classification accuracy for individualized signatures.
A deep neural network model accurately predicts brain age with a mean absolute error of 4.6 years based on EEG data, and its results show correlations with diseases such as epilepsy, stroke, and sleep-disordered breathing. The study suggests that these conditions are associated with deviations in predicted age from chronological age.
Researchers developed a method to localize epileptic tissue using EEG fast oscillations, differentiating pathological from nonepileptiform signals. High-frequency oscillations riding spikes provide a potential tool for presurgical diagnosis and postsurgical evaluation.
Researchers created an AI that understands individual notions of face attractiveness by analyzing brain signals and generating new portraits tailored to each person's preferences. The device demonstrated accuracy in matching personal taste with over 80% correctness.
Researchers from India and the UK developed a new brain-computer interface that uses EEG signals to control a robot arm with reduced positional error. The system achieves this by utilizing the P300 signal, which allows the robotic arm to make finer adjustments and reduce errors.
Researchers identify distinct functional connectivity patterns in brain circuits using EEG, enabling subtyping of patients independent of clinical diagnosis. These patterns can predict treatment outcomes, with some subtypes responding better to psychotherapy or medication while others benefit from non-invasive TMS treatment.
Researchers have found that EEG-based BCI speller output can be easily manipulated by tiny adversarial noise, exposing a critical security concern. This manipulation can lead to user frustration or severe misdiagnosis in clinical applications.
A CHOP study demonstrates that remote continuous EEG monitoring can detect seizures in at-risk neonates, impacting clinical care and guiding treatment decisions. The study showed that seizures occurred in about one-quarter of the records, with CEEG impacting outcomes in three-quarters of cases.
A new deep learning model can identify sleep stages with high accuracy, opening up new avenues for diagnostics and treatment of sleep disorders like obstructive sleep apnea. The model's accuracies are equivalent to those of experienced physicians, but it has the benefit of being systematic and faster.
A new study by Massachusetts General Hospital researchers has identified slowing brain rhythms as a biomarker for detecting delirium and predicting poor clinical outcomes. The study found that generalized EEG slowing was associated with longer patient hospitalizations, worse functional outcomes, and increased mortality.
A proposed working group would study and monitor poorly regulated products, addressing potential health risks and efficacy concerns. The group aims to provide guidance and back up or refute claims made by companies, ultimately protecting consumers from harm.
A study at the University of Göttingen found that people learn positive associations with words much faster than neutral or negative associations. The researchers used electroencephalography to analyze brain activity, revealing specific neuronal reactions after just 100 milliseconds for words associated with loss.
Researchers at the University of Oregon used EEG to capture how the brain builds complex sequences from basic elements. The study found that individuals with strong working memory had a clearer record of current chunks, enabling them to reconstruct sequential patterns.
Researchers found that preschool children (2-5 years old) can recognize sounds heard during naps, even when they're asleep. The study uses EEG and tested individual children in a quiet room, playing nonsense words to assess their auditory processing.
KAUST researchers develop efficient method for collective estimation of brain signal spectral densities, enabling detection of correlations among brain regions. The approach uses clustering to reduce data dimensionality and visualizes similarity among time series.
Recent advances in EEG technology could enable earlier diagnoses of common mental and neurological disorders like autism and dementia. Non-invasive portable devices make functional brain measurement possible during primary care check-ups.
Researchers found α-band power reduction and decreased EEG complexity in mild cognitive impairment (MCI) and subjective cognitive impairment (SCI). Nonlinear EEG analysis during cognitive tasks highlights potential early markers of Alzheimer's disease (AD).
Researchers have found that the left hemisphere of the brain processes auditory speech information more rapidly than the right, thanks to a higher number of densely packed neurites in planum temporale. This microstructure is crucial for linguistic superiority.
Researchers at Vanderbilt University have developed an ultrasound helmet that can create real-time images of the brain during surgery, allowing for more precise control over software and robotics using only thoughts. The technology uses machine learning to account for distortion and integrate electroencephalogram (EEG) technology to pr...
A Carnegie Mellon University team has received a three-year grant to refine a custom EEG system that can identify early markers for worsening brain injuries. The team will use the high-density EEG to detect cortical spreading depolarizations, or brain tsunamis, which are biomarkers for worsening brain injuries.
Researchers found that a brief test can predict which patients will respond better to cognitive behavioral therapy (CBT) or antidepressant medication. Participants with enhanced error-related negativity (ERN) signals in their brain responded better to CBT, suggesting it may be more effective for them.
Researchers developed a multivariate method for predicting behavioral response to a stimulus using information about the phase of preceding neuronal oscillations. The study found that reaction speed depends on the phase of low-frequency neuronal oscillations preceding the stimulus.
Researchers have deciphered the mechanism of general anesthesia using statistical analysis, revealing oscillations that disrupt brain communication. The discovery enables real-time brain state monitoring and may lead to new recovery methods for elderly patients experiencing cognitive dysfunction after anesthesia.
A Massachusetts General Hospital study found that fMRI and EEG can identify covert consciousness in ICU patients, allowing families to make informed decisions about care. The tests detected activity in higher-order cortex areas of the brain, which could have implications for patient recovery.
Experts say international variation in brain death definition must be cleared up to improve management of patients at end-of-life and increase successful organ donation. A universal definition and procedure are needed to reduce confusion and restore professional and public trust.
A new computational approach developed at Boston Children's Hospital uses Granger causality analysis to identify the brain regions responsible for seizures. This technology enables surgeons to plan surgeries more accurately and reduce the risk of complications.
A new study suggests that the ability to assess group size is processed in the ancient brain structure of the subcortex, which is shared across humans, birds, and fish. This finding has implications for understanding mathematical thinking and education.
A study by Aalto University and the Helsinki Institute for Information Technology used EEG to model user interest in Wikipedia articles, predicting search intentions and recommending relevant documents. This technology has potential to assist humans by automatically monitoring and gathering information through wearable EEG sensors.
Two mouse mutants, Sleepy and Dreamless, have been identified with excessive and reduced rapid eye movement (REM) sleep, respectively. The mutations have been linked to specific genes, offering a new perspective on the regulation of sleep and wakefulness.
Mount Sinai researchers used EEG to study cue-induced craving in cocaine addicts and found that vulnerability to relapse peaks between one and six months of abstinence. This period coincides with patients' release from treatment programs, highlighting the need for alternative interventions to prevent relapse.
Researchers have developed a noninvasive method to measure cortical spreading depression, a brainwave linked to migraines and epilepsy, using scalp electrodes and specialized amplifier. This breakthrough could lead to better diagnosis and treatment of these conditions.
Researchers found a correspondence between a patient's ability to generate an EEG marker of attention and their ability to produce the critical clinical marker of awareness. This relationship existed for patients who could only follow commands with fMRI, making EEG a potential diagnostic tool for disorders of consciousness.
A study by Massachusetts General Hospital researchers reveals a distinctive EEG pattern associated with high-dose nitrous oxide anesthesia. This finding may help explain the drug's mechanisms and provide insights into the development of new anesthetics.
Research on face perception in Japanese children aged 8-13 years reveals that it almost matures by age 13, significantly earlier than previously observed in Western children. This study utilized EEG to analyze the N170 component and found significant differences between Japanese and Western children in terms of latency and peak detection.
A study by Ruhr-University Bochum scientists and colleagues identifies specific brain regions responsible for spatial memory. The researchers found that suppressing irrelevant activities improves spatial navigation accuracy.
Researchers at ETH Zurich have developed a novel gene regulation method that enables thought-specific brainwaves to control the conversion of genes into proteins. The system uses EEG headsets to transmit brainwaves wirelessly to an implant, which regulates gene expression through light-sensitive optogenetic modules.
A new study suggests that measuring how fast the brain responds to sights and sounds can help classify people on the autism spectrum and diagnose the condition earlier. The study found a strong correlation between the speed of processing auditory signals and the severity of autistic symptoms.
Researchers found that repeated-pulse transcranial magnetic stimulation at the Guangming point induces distinct electroencephalogram signal patterns compared to other stimulation points. The study also revealed changes in visual response complexity in parietal, central, and temporal regions following this stimulation.
Researchers found that frontal EEG lateralization is a key indicator of emotional flexibility, with left-sided lateralization associated with flexible responses and right-sided lateralization linked to inflexible ones. The study suggests that training can improve left-sided lateralization and enhance emotional flexibility.
A significant genetic component of Idiopathic Generalized Epilepsy (IGE) has been discovered, implicating a mutation in the gene for protein cotransporter KCC2. The study found a clear association between two variants of KCC2 and severe IGE in French-Canadian patients.
A new study by University of Cincinnati researchers found that only a small proportion of seizure patients receive electroencephalograms (EEGs) in the emergency department, which can lead to delayed or inaccurate diagnoses. The study suggests that this may impact admission decisions and hospital care for these patients.
Researchers found that repeated-pulse transcranial magnetic stimulation at the Guangming point evokes distinct patterns in electroencephalogram signals compared to other nearby points. This study suggests a potential therapeutic application of this stimulation technique for modulating brain activity.
A UT Arlington assistant professor has developed a computational model that can accurately predict when an epileptic seizure will occur next. The model analyzes EEG readings to provide early warnings, allowing patients to use medicine to combat an oncoming seizure.