AIMC Topic: Magnetoencephalography
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MEG Source Localization via Deep Learning.
Sensors (Basel, Switzerland)
Jun 22, 2021
We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned to single and multiple time point MEG data, and can estimate varying numbers of dipole s...
Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.
Seizure
May 4, 2021
OBJECTIVE: One barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both pathological and physiological HFBS. This study was to find specific biomarkers for localizing epileptogenic...
Reconstructing feedback representations in the ventral visual pathway with a generative adversarial autoencoder.
PLoS computational biology
Mar 24, 2021
While vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understoo...
Why do humans have unique auditory event-related fields? Evidence from computational modeling and MEG experiments.
Psychophysiology
Jan 21, 2021
Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic de...
Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury.
Human brain mapping
Jan 15, 2021
Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the sympto...
Neural dynamics of perceptual inference and its reversal during imagery.
eLife
Jul 20, 2020
After the presentation of a visual stimulus, neural processing cascades from low-level sensory areas to increasingly abstract representations in higher-level areas. It is often hypothesised that a reversal in neural processing underlies the generatio...
BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial.
Neurology
Jul 16, 2020
OBJECTIVE: To determine whether training with a brain-computer interface (BCI) to control an image of a phantom hand, which moves based on cortical currents estimated from magnetoencephalographic signals, reduces phantom limb pain.
Classification of cognitive reserve in healthy older adults based on brain activity using support vector machine.
Physiological measurement
Jul 7, 2020
OBJECTIVE: Cognitive reserve (CR) refers to the capacity of the brain to actively cope with damage via the implementation of remedial cognitive processes. Traditional CR measurements focus on static proxies, which may not be able to appropriately est...
Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.
Progress in neurobiology
May 22, 2020
Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study t...
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.
NeuroImage
May 18, 2020
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet, m...
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