Matthew J. Brookes focuses on Magnetoencephalography, Neuroscience, Resting state fMRI, Neuroimaging and Artificial intelligence. His study with Magnetoencephalography involves better knowledge in Electroencephalography. His Default mode network, Nerve net and Cerebral cortex investigations are all subjects of Neuroscience research.
His studies in Resting state fMRI integrate themes in fields like Coherence and Functional connectivity. His Artificial intelligence study incorporates themes from Algorithm, Computer vision and Pattern recognition. His Pattern recognition research incorporates themes from Voxel, Multivariate statistics and Autoregressive model.
Matthew J. Brookes mainly focuses on Magnetoencephalography, Neuroscience, Artificial intelligence, Resting state fMRI and Neuroimaging. His work carried out in the field of Magnetoencephalography brings together such families of science as Cognition, Electrophysiology, Visual cortex and Human brain. His Artificial intelligence research is multidisciplinary, incorporating elements of Metric, Electroencephalography, Interference, Computer vision and Pattern recognition.
The various areas that Matthew J. Brookes examines in his Pattern recognition study include Voxel, Data mining and Speech recognition. The study incorporates disciplines such as Statistical physics, Connectome, Functional connectivity and Coherence in addition to Resting state fMRI. His research in Neuroimaging intersects with topics in Independent component analysis, Brain activity and meditation and Brain mapping.
Matthew J. Brookes spends much of his time researching Magnetoencephalography, Electrophysiology, Resting state fMRI, Magnetic potential and Neuroscience. His Magnetoencephalography research integrates issues from Detection theory and Neuroimaging. His work investigates the relationship between Neuroimaging and topics such as Hippocampus that intersect with problems in Coherence.
His Electrophysiology study combines topics from a wide range of disciplines, such as Alpha, Neurophysiology and Symptom severity. His Resting state fMRI research is multidisciplinary, relying on both Ketamine and Anesthesia. His research integrates issues of Beta, Rhythm and Isometric exercise in his study of Neuroscience.
The scientist’s investigation covers issues in Magnetoencephalography, Neuroscience, Resting state fMRI, Quadratic trend and White matter. His studies deal with areas such as Computer hardware, Lift, Detection theory, Alpha and Functional neuroimaging as well as Magnetoencephalography. His work deals with themes such as Rhythm and Isometric exercise, which intersect with Neuroscience.
His biological study spans a wide range of topics, including Ketamine and Anesthesia. His Quadratic trend study spans across into areas like Nuclear magnetic resonance, Magnetisation transfer and Age related.
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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)
Moving magnetoencephalography towards real-world applications with a wearable system.
Elena Boto;Niall Holmes;James Leggett;Gillian Roberts.
Measuring functional connectivity using MEG: methodology and comparison with fcMRI.
Matthew J. Brookes;Joanne R. Hale;Johanna M. Zumer;Claire M. Stevenson.
Fast transient networks in spontaneous human brain activity
Adam P. Baker;Matthew J. Brookes;Iead A. Rezek;Stephen M. Smith.
Broadband Cortical Desynchronization Underlies the Human Psychedelic State
Suresh D Muthukumaraswamy;Robin L Carhart-Harris;Rosalyn J Moran;Matthew J Brookes.
The Journal of Neuroscience (2013)
How reliable are MEG resting-state connectivity metrics?
Giles L. Colclough;Mark W. Woolrich;Prejaas Tewarie;Matthew J. Brookes.
A symmetric multivariate leakage correction for MEG connectomes.
Giles L. Colclough;Matthew J. Brookes;Stephen M. Smith;Mark W. Woolrich.
A new generation of magnetoencephalography: Room temperature measurements using optically-pumped magnetometers
Elena Boto;Sofie S. Meyer;Vishal Shah;Orang Alem.
Measuring functional connectivity in MEG: A multivariate approach insensitive to linear source leakage
Matthew J. Brookes;Mark William Woolrich;Gareth R. Barnes.
Water proton T1 measurements in brain tissue at 7, 3, and 1.5 T using IR-EPI, IR-TSE, and MPRAGE: results and optimization.
P. J. Wright;O. E. Mougin;J. J. Totman;A. M. Peters.
Magnetic Resonance Materials in Physics Biology and Medicine (2008)
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