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Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data (2023)
Journal Article
Tewarie, P. K., Hindriks, R., Lai, Y. M., Sotiropoulos, S. N., Kringelbach, M., & Deco, G. (2023). Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data. NeuroImage, 276, Article 120186. https://doi.org/10.1016/j.neuroimage.2023.120186

Characterising brain states during tasks is common practice for many neuroscientific experiments using electrophysiological modalities such as electroencephalography (EEG) and magnetoencephalography (MEG). Brain states are often described in terms of... Read More about Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data.

Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models (2021)
Journal Article
Tewarie, P., Prasse, B., Meier, J. M., Byrne, Á., De Domenico, M., Stam, C. J. (., …Van Mieghem, P. (2021). Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models. New Journal of Physics, 23(6), Article 063065. https://doi.org/10.1088/1367-2630/ac066d

Large-scale neurophysiological networks are often reconstructed from band-pass filtered time series derived from magnetoencephalography (MEG) data. Common practice is to reconstruct these networks separately for different frequency bands and to treat... Read More about Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models.

How Sensitive Are Conventional MEG Functional Connectivity Metrics With Sliding Windows to Detect Genuine Fluctuations in Dynamic Functional Connectivity? (2019)
Journal Article
Liuzzi, L., Quinn, A. J., O'Neill, G. C., Woolrich, M. W., Brookes, M. J., Hillebrand, A., & Tewarie, P. (2019). How Sensitive Are Conventional MEG Functional Connectivity Metrics With Sliding Windows to Detect Genuine Fluctuations in Dynamic Functional Connectivity?. Frontiers in Neuroscience, 13, Article 797. https://doi.org/10.3389/fnins.2019.00797

Despite advances in the field of dynamic connectivity, fixed sliding window approaches for the detection of fluctuations in functional connectivity are still widely used. The use of conventional connectivity metrics in conjunction with a fixed slidin... Read More about How Sensitive Are Conventional MEG Functional Connectivity Metrics With Sliding Windows to Detect Genuine Fluctuations in Dynamic Functional Connectivity?.

How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes (2018)
Journal Article
Tewarie, P., Abeysuriya, R., Byrne, Á., O'Neill, G. C., Sotiropoulos, S. N., Brookes, M. J., & Coombes, S. (2019). How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes. NeuroImage, 186, 211-220. https://doi.org/10.1016/j.neuroimage.2018.10.079

Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural networ... Read More about How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes.

Relationships Between Neuronal Oscillatory Amplitude and Dynamic Functional Connectivity (2018)
Journal Article
Tewarie, P., Hunt, B. A. E., O'Neill, G. C., Byrne, A., Aquino, K., Bauer, M., …Brookes, M. J. (2018). Relationships Between Neuronal Oscillatory Amplitude and Dynamic Functional Connectivity. Cerebral Cortex, 29(6), 2668-2681. https://doi.org/10.1093/cercor/bhy136

Event related fluctuations of neural oscillatory amplitude are reported widely in the context of cognitive processing and are typically interpreted as a marker of brain ‘activity’. However, the precise nature of these effects remains unclear; in part... Read More about Relationships Between Neuronal Oscillatory Amplitude and Dynamic Functional Connectivity.

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations (2017)
Journal Article
Mandke, K., Meier, J., Brookes, M. J., O'Dea, R. D., Van Mieghem, P., Stam, C. J., …Tewarie, P. K. (2018). Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations. NeuroImage, 166, https://doi.org/10.1016/j.neuroimage.2017.11.016

There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial... Read More about Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations.

Dynamics of large-scale electrophysiological networks: a technical review (2017)
Journal Article
O'Neill, G. C., Tewarie, P. K., Vidaurre, D., Liuzzi, L., Woolrich, M. W., & Brookes, M. J. (2017). Dynamics of large-scale electrophysiological networks: a technical review. NeuroImage, https://doi.org/10.1016/j.neuroimage.2017.10.003

For several years it has been argued that neural synchronisation is crucial for cognition. The idea that synchronised temporal patterns between different neural groups carries information above and beyond the isolated activity of these groups has ins... Read More about Dynamics of large-scale electrophysiological networks: a technical review.

Abnormal task driven neural oscillations in multiple sclerosis: a visuomotor MEG study (2017)
Journal Article
Barratt, E. L., Tewarie, P. K., Clarke, M. A., Hall, E. L., Gowland, P. A., Morris, P. G., …Brookes, M. J. (2017). Abnormal task driven neural oscillations in multiple sclerosis: a visuomotor MEG study. Human Brain Mapping, 38(5), 2441-2453. https://doi.org/10.1002/hbm.23531

Multiple sclerosis (MS) is a debilitating disease commonly attributed to degradation of white matter myelin. Symptoms include fatigue, as well as problems associated with vision and movement. Although areas of demyelination in white matter are observ... Read More about Abnormal task driven neural oscillations in multiple sclerosis: a visuomotor MEG study.

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.

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?.

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.

Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions (2016)
Journal Article
Tewarie, P. K., Bright, M. G., Hillebrand, A., Robson, S. E., Gascoyne, L. E., Morris, P. G., …Brookes, M. J. (2016). Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions. NeuroImage, 130, https://doi.org/10.1016/j.neuroimage.2016.01.053

Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typi... Read More about Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions.

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods (2015)
Journal Article
O'Neill, G. C., Barratt, E. L., Hunt, B. A. E., Tewarie, P. K., & Brookes, M. J. (2015). Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods. Physics in Medicine and Biology, 60(21), Article R271-R295. https://doi.org/10.1088/0031-9155/60/21/R271

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ab... Read More about Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods.