Results 21 to 30 of about 30,896 (211)
An inversion method based on random sampling for real-time MEG neuroimaging [PDF]
, 2019 The MagnetoEncephaloGraphy (MEG) is a non-invasive neuroimaging technique with a high temporal resolution which can be successfully used in real-time applications, such as brain-computer interface training or neurofeedback rehabilitation.
Pascarella, Annalisa, Pitolli, Francesca
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Magnetoencephalography: Basic principles
Annals of Indian Academy of Neurology, 2014 Magnetoencephalography (MEG) is the measurement of the magnetic field generated by the electrical activity of neurons. It is usually combined with a magnetic resonance imaging to get what is called magnetic source imaging.
Sanjay P Singh
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OMMR: Co-registration toolbox of OPM-MEG and MRI
Frontiers in Neuroscience, 2022 Magnetoencephalography (MEG) based on optically pumped magnetometers (OPM-MEG) has shown better flexibility in sensor configuration compared with the conventional superconducting quantum interference devices-based MEG system while being better suited for
Fuzhi Cao +19 more
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Neuroelectric source localization by random spatial sampling [PDF]
, 2016 The magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from the measurements of the neuromagnetic field in the outer space.
PITOLLI, Francesca, POCCI, CRISTINA
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Proceedings, 2017 Magnetoencephalography (MEG) has revolutionized neuroscience, offering a tool with [...]
Daniela Moretti +6 more
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Cortical correlation structure of aperiodic neuronal population activity
NeuroImage, 2021 Electrophysiological population signals contain oscillatory and non-oscillatory aperiodic (1/frequency-like) components. So far research has largely focused on oscillatory activity, and only recently, interest in aperiodic population activity has gained ...
Andrea Ibarra Chaoul, Markus Siegel
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Sequential Monte Carlo samplers for semilinear inverse problems and application to magnetoencephalography [PDF]
, 2014 We discuss the use of a recent class of sequential Monte Carlo methods for solving inverse problems characterized by a semi-linear structure, i.e. where the data depend linearly on a subset of variables and nonlinearly on the remaining ones. In this type
Sommariva, Sara, Sorrentino, Alberto
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Magnetoencephalography in clinical practice
Arquivos de Neuro-Psiquiatria, 2022 Magnetoencephalography (MEG) is a neurophysiological technique that measures the magnetic fields associated with neuronal activity in the brain. It is closely related but distinct from its counterpart electroencephalography (EEG).
Mohamed HEGAZY, Jay GAVVALA
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Non-parametric statistical thresholding for sparse magnetoencephalography source reconstructions. [PDF]
, 2012 Uncovering brain activity from magnetoencephalography (MEG) data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources.
Nagarajan, Srikantan S +2 more
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Deep brain activities can be detected with magnetoencephalography
Nature Communications, 2019 Magnetoencephalography (MEG) is a non-invasive method of measuring neural activity but the hippocampus and amygdala are difficult to measure with MEG because of their deep localization. Here, the authors show with simultaneous MEG and invasive recordings
Francesca Pizzo +12 more
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