AIMC Topic: Magnetoencephalography

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Supervised learning for neural manifold using spatiotemporal brain activity.

Journal of neural engineering Nov 18, 2015
OBJECTIVE: Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli.
Female Young Adult Adult Supervised Machine Learning Photic Stimulation Male Magnetoencephalography Time Factors Orientation Humans Brain
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A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

Biomedical engineering online Aug 20, 2015
BACKGROUND: A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although in...
Magnetoencephalography Humans Hand Brain Arm Female Brain-Computer Interfaces Hand Strength Young Adult Robotics Electroencephalography Adult Signal Processing, Computer-Assisted Male
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Attentional Enhancement of Auditory Mismatch Responses: a DCM/MEG Study.

Cerebral cortex (New York, N.Y. : 1991) Jan 16, 2015
Despite similar behavioral effects, attention and expectation influence evoked responses differently: Attention typically enhances event-related responses, whereas expectation reduces them. This dissociation has been reconciled under predictive codin...
Auditory Perception Electroencephalography Contingent Negative Variation Attention Magnetoencephalography Young Adult Healthy Volunteers Humans Adult Nonlinear Dynamics Male Acoustic Stimulation Neural Networks, Computer Female Auditory Cortex Evoked Potentials, Auditory
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Multimodal personalization of transcranial direct current stimulation for modulation of sensorimotor integration.

NeuroImage Aug 15, 2025
Transcranial direct current stimulation (tDCS) for the modulation of smooth pursuit eye movements provides an ideal model for investigating sensorimotor integration. Within neural networks subserving smooth pursuit, visual area V5 is a core hub where...
Humans Female Young Adult Adult Visual Cortex Magnetoencephalography Motion Perception Pursuit, Smooth Male Magnetic Resonance Imaging Transcranial Direct Current Stimulation
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Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.

Neuroscience and biobehavioral reviews Jul 1, 2025
Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reduc...
Humans Neural Networks, Computer Machine Learning Magnetoencephalography Biomarkers Depressive Disorder, Major Electroencephalography
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Artificial neural networks for magnetoencephalography: a review of an emerging field.

Journal of neural engineering Jun 12, 2025
. Magnetoencephalography (MEG) is a cutting-edge neuroimaging technique that measures the intricate brain dynamics underlying cognitive processes with an unparalleled combination of high temporal and spatial precision. While MEG data analytics have t...
Machine Learning Brain Magnetoencephalography Humans Neural Networks, Computer
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Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories.

IEEE journal of biomedical and health informatics Jun 1, 2025
Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neurodegenerative disorders, such as Alzheimer's disease. In this study, we developed a Fully Hyperbolic...
Humans Neural Networks, Computer Brain Aging Middle Aged Signal Processing, Computer-Assisted Nerve Net Magnetoencephalography Young Adult Female Adult Aged Male Aged, 80 and over
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Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition.

eLife May 13, 2025
Traditional models of reading lack a realistic simulation of the early visual processing stages, taking input in the form of letter banks and predefined line segments, making them unsuitable for modeling early brain responses. We used variations of t...
Reading Pattern Recognition, Visual Magnetoencephalography Neural Networks, Computer Brain Female Male Models, Neurological Young Adult Adult Humans
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χ-sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation.

Human brain mapping Feb 1, 2025
Magnetic susceptibility source separation (χ-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of paramagnetic and diamagnetic susceptibility source distributions in the brain. Similar to QSM, ...
Magnetic Resonance Imaging Magnetoencephalography Male Humans Deep Learning Image Processing, Computer-Assisted Female Adult Neural Networks, Computer Brain
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Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning.

Cerebral cortex (New York, N.Y. : 1991) Jul 5, 2023
Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging tech...
Brain-Computer Interfaces Magnetoencephalography Algorithms Gestures Humans Deep Learning Electroencephalography
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