His scientific interests lie mostly in Magnetoencephalography, Neuroscience, Artificial intelligence, Neuroimaging and Functional magnetic resonance imaging. His Magnetoencephalography research is multidisciplinary, incorporating perspectives in Human brain, Spatial memory, Cortical Synchronization, Visual cortex and Brain mapping. His Brain mapping study which covers Electroencephalography that intersects with Coherence.
His study on Local field potential, Cerebral cortex and Stimulus is often connected to Subthalamic nucleus and Deep brain stimulation as part of broader study in Neuroscience. His research investigates the link between Artificial intelligence and topics such as Pattern recognition that cross with problems in Machine learning and Voxel. His research integrates issues of Resting state fMRI and Cognition in his study of Neuroimaging.
Gareth R. Barnes focuses on Magnetoencephalography, Neuroscience, Artificial intelligence, Pattern recognition and Electroencephalography. His Magnetoencephalography research integrates issues from Stimulus, Neuroimaging, Visual cortex and Brain mapping. His Neuroimaging research is multidisciplinary, relying on both Resting state fMRI and Human brain.
His Visual cortex research includes elements of Cerebral cortex, Spatial frequency and Premovement neuronal activity. The various areas that Gareth R. Barnes examines in his Artificial intelligence study include Covariance, Machine learning and Computer vision. His Pattern recognition study combines topics from a wide range of disciplines, such as Voxel and Bayesian probability.
Gareth R. Barnes spends much of his time researching Magnetoencephalography, Hippocampus, Artificial intelligence, Magnetometer and Neuroscience. His research in Magnetoencephalography intersects with topics in Cognitive psychology, Electrophysiology, Brain region, Neuroimaging and Scalp. Gareth R. Barnes interconnects Virtual reality and Visual cortex in the investigation of issues within Neuroimaging.
The Hippocampus study combines topics in areas such as Hippocampal formation, Temporal lobe and Cognition. His studies in Artificial intelligence integrate themes in fields like Electroencephalography, Computer vision and Pattern recognition. His biological study spans a wide range of topics, including Amplitude and Movement planning.
Gareth R. Barnes mainly investigates Magnetoencephalography, Neuroscience, Cognition, Hippocampus and Neuroimaging. Gareth R. Barnes has researched Magnetoencephalography in several fields, including Stimulus, Occipital lobe and Electrophysiology. His Neuroscience research includes themes of Amplitude and Movement planning.
His studies deal with areas such as Cognitive psychology, Episodic memory, Temporal lobe and Ventromedial prefrontal cortex as well as Hippocampus. His work deals with themes such as Virtual reality and Computer vision, which intersect with Neuroimaging. Gareth R. Barnes has included themes like Human–computer interaction, Visual Physiology, Immersion, Feeling and Visual cortex in his Functional neuroimaging study.
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Investigating the electrophysiological basis of resting state networks using magnetoencephalography
Matthew J. Brookes;Mark Woolrich;Henry Luckhoo;Darren Price.
Proceedings of the National Academy of Sciences of the United States of America (2011)
EEG and MEG data analysis in SPM8.
Vladimir Litvak;Jérémie Mattout;Stefan J. Kiebel;Christophe Phillips.
Computational Intelligence and Neuroscience (2011)
A new approach to neuroimaging with magnetoencephalography.
Arjan Hillebrand;Krish D Singh;Ian E Holliday;Paul Lawrence Furlong.
Human Brain Mapping (2005)
Good practice for conducting and reporting MEG research
Joachim Gross;Sylvain Baillet;Gareth R. Barnes;Richard N. A. Henson.
Measuring functional connectivity using MEG: methodology and comparison with fcMRI.
Matthew J. Brookes;Joanne R. Hale;Johanna M. Zumer;Claire M. Stevenson.
A quantitative assessment of the sensitivity of whole-head MEG to activity in the adult human cortex.
Arjan Hillebrand;Gareth R. Barnes.
Moving magnetoencephalography towards real-world applications with a wearable system.
Elena Boto;Niall Holmes;James Leggett;Gillian Roberts.
Frequency-dependent functional connectivity within resting-state networks: An atlas-based MEG beamformer solution
Arjan Hillebrand;Gareth R. Barnes;Johannes L. Bosboom;Henk W. Berendse.
Task-Related Changes in Cortical Synchronization Are Spatially Coincident with the Hemodynamic Response
Krish Devi Singh;Gareth R. Barnes;Arjan Hillebrand;Emer M.E Forde.
The cortical deficit in humans with strabismic amblyopia.
G. R. Barnes;R. F. Hess;S. O. Dumoulin;R. L. Achtman.
The Journal of Physiology (2001)
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