Outputs (8)

Optimising experimental design for MEG resting state functional connectivity measurement (2016)
Journal Article
Liuzzi, L., Gascoyne, L. E., Tewarie, P. K., Barratt, E. L., Boto, E., & Brookes, M. J. (2017). Optimising experimental design for MEG resting state functional connectivity measurement. NeuroImage, 155, 565-576. https://doi.org/10.1016/j.neuroimage.2016.11.064

The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstra... Read More about Optimising experimental design for MEG resting state functional connectivity measurement.

Relationships between cortical myeloarchitecture and electrophysiological networks (2016)
Journal Article
Hunt, B. A. E., Tewarie, P. K., Mougin, O. E., Geades, N., Jones, D. K., Singh, K. D., …Brookes, M. J. (2016). Relationships between cortical myeloarchitecture and electrophysiological networks. Proceedings of the National Academy of Sciences, 113(47), 13510-13515. https://doi.org/10.1073/pnas.1608587113

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poo... Read More about Relationships between cortical myeloarchitecture and electrophysiological networks.

Measurement of dynamic task related functional networks using MEG (2016)
Journal Article
O’Neill, G. C., Tewarie, P. K., Colclough, G. L., Gascoyne, L. E., Hunt, B. A., Morris, P. G., …Brookes, M. J. (2017). Measurement of dynamic task related functional networks using MEG. NeuroImage, 146, 667-678. https://doi.org/10.1016/j.neuroimage.2016.08.061

The characterisation of dynamic electrophysiological brain networks, which form and dissolve in order to support ongoing cognitive function, is one of the most important goals in neuroscience. Here, we introduce a method for measuring such networks i... Read More about Measurement of dynamic task related functional networks using MEG.

On the potential of a new generation of magnetometers for MEG: A beamformer simulation study (2016)
Journal Article
Boto, E., Bowtell, R. W., Kruger, P., Fromhold, T. M., Morris, P. G., Meyer, S. S., …Brookes, M. J. (2016). On the potential of a new generation of magnetometers for MEG: A beamformer simulation study. PLoS ONE, 11(8), Article e0157655. https://doi.org/10.1371/journal.pone.0157655

Magnetoencephalography (MEG) is a sophisticated tool which yields rich information on the spatial, spectral and temporal signatures of human brain function. Despite unique potential, MEG is limited by a low signal-to-noise ratio (SNR) which is caused... Read More about On the potential of a new generation of magnetometers for MEG: A beamformer simulation study.

Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach (2016)
Journal Article
Van Mieghem, P., Tewarie, P., Hillebrand, A., van Dijk, B. W., Stam, C. J., O'Neill, G. C., …Brookes, M. J. (2016). Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach. NeuroImage, 142, 324-336. https://doi.org/10.1016/j.neuroimage.2016.07.057

Neuronal oscillations exist across a broad frequency spectrum, and are thought to provide a mechanism of interaction between spatially separated brain regions. Since ongoing mental activity necessitates the simultaneous formation of multiple networks... Read More about Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach.

How reliable are MEG resting-state connectivity metrics? (2016)
Journal Article
Colclough, G., Woolrich, M., Tewarie, P., Brookes, M., Quinn, A., & Smith, S. (2016). How reliable are MEG resting-state connectivity metrics?. NeuroImage, 138, 284-293. https://doi.org/10.1016/j.neuroimage.2016.05.070

MEG offers dynamic and spectral resolution for resting-state connectivity which is unavailable in fMRI. However, there are a wide range of available network estimation methods for MEG, and little in the way of existing guidance on which ones to emplo... Read More about How reliable are MEG resting-state connectivity metrics?.

Modulation of post-movement beta rebound by contraction force and rate of force development (2016)
Journal Article
Fry, A., Mullinger, K. J., O'Neill, G. C., Barratt, E. L., Morris, P. G., Bauer, M., …Brookes, M. J. (2016). Modulation of post-movement beta rebound by contraction force and rate of force development. Human Brain Mapping, 37(7), https://doi.org/10.1002/hbm.23189

Movement induced modulation of the beta rhythm is one of the most robust neural oscillatory phenomena in the brain. In the preparation and execution phases of movement, a loss in beta amplitude is observed (movement related beta decrease (MRBD)). Thi... Read More about Modulation of post-movement beta rebound by contraction force and rate of force development.

A multi-layer network approach to MEG connectivity analysis (2016)
Journal Article
Brookes, M. J., Tewarie, P. K., Hunt, B. A. E., Robson, S. E., Gascoyne, L. E., Liddle, E. B., …Morris, P. G. (2016). A multi-layer network approach to MEG connectivity analysis. NeuroImage, 132, 425-438. https://doi.org/10.1016/j.neuroimage.2016.02.045

© 2016 The Authors. Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of... Read More about A multi-layer network approach to MEG connectivity analysis.