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Matthew J. Brookes

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60 papers
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60

YNICL Journal 2025 Journal Article

OPM-MEG in multiple sclerosis: Proof of principle, and the effect of naturalistic posture

  • Benjamin J. Sanders
  • Christopher G.S. Gilmartin
  • Lukas Rier
  • Lauren Gascoyne
  • Emily McCann
  • Jorge Cabrera
  • James Leggett
  • Niall Holmes

Multiple Sclerosis (MS) is a common neurological disorder in which myelin damage affects neuronal signalling. Magnetoencephalography (MEG - the measurement of magnetic fields generated by neuronal currents) offers metrics of brain function that relate directly to electrophysiological signalling, making it a valuable tool for exploring how abnormal function relates to MS symptoms. However, conventional MEG requires participants to be seated or supine with limited head and body motion. This makes it hard to measure brain function whilst simultaneously asking patients to carry out tasks they find challenging - many of which relate to movement. Here, we used a newly developed OPM-MEG system, with a wearable helmet and a lightweight backpack-mounted control unit, to measure MEG signals in people with MS (pwMS), both at rest and during a visuo-motor task. Uniquely, our system enabled data collection in participants who were seated and standing. We found that established markers of MS - including delayed beta-band responses to finger movement and diminished gamma-band responses to visual stimulation - were measurable using OPM-MEG. Further, we showed that standing (compared to sitting) decreased beta-band connectivity (in patients and controls, but the effect was only significant in controls) and decreased oscillatory power (in patients but not controls). In summary, our paper confirms that OPM-MEG is a useful means to investigate MS; it also demonstrates the importance of investigating how changes in posture relate to oscillations and connectivity, and lays the groundwork for broader studies of movement.

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YNIMG Journal 2023 Journal Article

Enabling ambulatory movement in wearable magnetoencephalography with matrix coil active magnetic shielding

  • Niall Holmes
  • Molly Rea
  • Ryan M. Hill
  • James Leggett
  • Lucy J. Edwards
  • Peter J. Hobson
  • Elena Boto
  • Tim M. Tierney

The ability to collect high-quality neuroimaging data during ambulatory participant movement would enable a wealth of neuroscientific paradigms. Wearable magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) has the potential to allow participant movement during a scan. However, the strict zero magnetic field requirement of OPMs means that systems must be operated inside a magnetically shielded room (MSR) and also require active shielding using electromagnetic coils to cancel residual fields and field changes (due to external sources and sensor movements) that would otherwise prevent accurate neuronal source reconstructions. Existing active shielding systems only compensate fields over small, fixed regions and do not allow ambulatory movement. Here we describe the matrix coil, a new type of active shielding system for OPM-MEG which is formed from 48 square unit coils arranged on two planes which can compensate magnetic fields in regions that can be flexibly placed between the planes. Through the integration of optical tracking with OPM data acquisition, field changes induced by participant movement are cancelled with low latency (25 ms). High-quality MEG source data were collected despite the presence of large (65 cm translations and 270° rotations) ambulatory participant movements.

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YNIMG Journal 2023 Journal Article

Measurement of Frontal Midline Theta Oscillations using OPM-MEG

  • Natalie Rhodes
  • Molly Rea
  • Elena Boto
  • Lukas Rier
  • Vishal Shah
  • Ryan M. Hill
  • James Osborne
  • Cody Doyle

Optically pumped magnetometers (OPMs) are an emerging lightweight and compact sensor that can measure magnetic fields generated by the human brain. OPMs enable construction of wearable magnetoencephalography (MEG) systems, which offer advantages over conventional instrumentation. However, when trying to measure signals at low frequency, higher levels of inherent sensor noise, magnetic interference and movement artefact introduce a significant challenge. Accurate characterisation of low frequency brain signals is important for neuroscientific, clinical, and paediatric MEG applications and consequently, demonstrating the viability of OPMs in this area is critical. Here, we undertake measurement of theta band (4-8 Hz) neural oscillations and contrast a newly developed 174 channel triaxial wearable OPM-MEG system with conventional (cryogenic-MEG) instrumentation. Our results show that visual steady state responses at 4 Hz, 6 Hz and 8 Hz can be recorded using OPM-MEG with a signal-to-noise ratio (SNR) that is not significantly different to conventional MEG. Moreover, we measure frontal midline theta oscillations during a 2-back working memory task, again demonstrating comparable SNR for both systems. We show that individual differences in both the amplitude and spatial signature of induced frontal-midline theta responses are maintained across systems. Finally, we show that our OPM-MEG results could not have been achieved without a triaxial sensor array, or the use of postprocessing techniques. Our results demonstrate the viability of OPMs for characterising theta oscillations and add weight to the argument that OPMs can replace cryogenic sensors as the fundamental building block of MEG systems.

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YNIMG Journal 2022 Journal Article

The oscillatory effects of rhythmic median nerve stimulation

  • Mairi S. Houlgreave
  • Barbara Morera Maiquez
  • Matthew J. Brookes
  • Stephen R. Jackson

Entrainment of brain oscillations can be achieved using rhythmic non-invasive brain stimulation, and stimulation of the motor cortex at a frequency associated with sensorimotor inhibition can impair motor responses. Despite the potential for therapeutic application, these techniques do not lend themselves to use outside of a clinical setting. Here, the aim was to investigate whether rhythmic median nerve stimulation (MNS) could be used to entrain oscillations related to sensorimotor inhibition. MEG data were recorded from 20 participants during 400 trials, where for each trial 10 pulses of MNS were delivered either rhythmically or arrhythmically at 12 or 20 Hz. Our results demonstrate a frequency specific increase in relative amplitude in the contralateral somatosensory cortex during rhythmic but not arrhythmic stimulation. This was coupled with an increase in inter-trial phase coherence at the same frequency, suggesting that the oscillations synchronised with the pulses of MNS. The results show that 12 and 20 Hz rhythmic peripheral nerve stimulation can produce entrainment. Rhythmic MNS resulted in synchronous firing of neuronal populations within the contralateral somatosensory cortex meaning these neurons were engaged in processing of the afferent input. Therefore, MNS could prove therapeutically useful in disorders associated with hyperexcitability within the sensorimotor cortices.

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YNIMG Journal 2022 Journal Article

Triaxial detection of the neuromagnetic field using optically-pumped magnetometry: feasibility and application in children

  • Elena Boto
  • Vishal Shah
  • Ryan M. Hill
  • Natalie Rhodes
  • James Osborne
  • Cody Doyle
  • Niall Holmes
  • Molly Rea

Optically-pumped magnetometers (OPMs) are an established alternative to superconducting sensors for magnetoencephalography (MEG), offering significant advantages including flexibility to accommodate any head size, uniform coverage, free movement during scanning, better data quality and lower cost. However, OPM sensor technology remains under development; there is flexibility regarding OPM design and it is not yet clear which variant will prove most effective for MEG. Most OPM-MEG implementations have either used single-axis (equivalent to conventional MEG) or dual-axis magnetic field measurements. Here we demonstrate use of a triaxial OPM formulation, able to characterise the full 3D neuromagnetic field vector. We show that this novel sensor is able to characterise magnetic fields with high accuracy and sensitivity that matches conventional (dual-axis) OPMs. We show practicality via measurement of biomagnetic fields from both the heart and the brain. Using simulations, we demonstrate how triaxial measurement offers improved cortical coverage, especially in infants. Finally, we introduce a new 3D-printed child-friendly OPM-helmet and demonstrate feasibility of triaxial measurement in a five-year-old. In sum, the data presented demonstrate that triaxial OPMs offer a significant improvement over dual-axis variants and are likely to become the sensor of choice for future MEG systems, particularly for deployment in paediatric populations.

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YNIMG Journal 2022 Journal Article

Using OPM-MEG in contrasting magnetic environments

  • Ryan M. Hill
  • Jasen Devasagayam
  • Niall Holmes
  • Elena Boto
  • Vishal Shah
  • James Osborne
  • Kristina Safar
  • Frank Worcester

Magnetoencephalography (MEG) has been revolutionised by optically pumped magnetometers (OPMs). "OPM-MEG" offers higher sensitivity, better spatial resolution, and lower cost than conventional instrumentation based on superconducting quantum interference devices (SQUIDs). Moreover, because OPMs are small, lightweight, and portable they offer the possibility of lifespan compliance and (with control of background field) motion robustness, dramatically expanding the range of MEG applications. However, OPM-MEG remains nascent technology; it places stringent requirements on magnetic shielding, and whilst a number of viable systems exist, most are custom made and there have been no cross-site investigations showing the reliability of data. In this paper, we undertake the first cross-site OPM-MEG comparison, using near identical commercial systems scanning the same participant. The two sites are deliberately contrasting, with different magnetic environments: a "green field" campus university site with an OPM-optimised shielded room (low interference) and a city centre hospital site with a "standard" (non-optimised) MSR (higher interference). We show that despite a 20-fold difference in background field, and a 30-fold difference in low frequency interference, using dynamic field control and software-based suppression of interference we can generate comparable noise floors at both sites. In human data recorded during a visuo-motor task and a face processing paradigm, we were able to generate similar data, with source localisation showing that brain regions could be pinpointed with just ∼10 mm spatial discrepancy and temporal correlations of > 80%. Overall, our study demonstrates that, with appropriate field control, OPM-MEG systems can be sited even in city centre hospital locations. The methods presented pave the way for wider deployment of OPM-MEG.

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YNIMG Journal 2021 Journal Article

Differential classification of states of consciousness using envelope- and phase-based functional connectivity

  • Catherine Duclos
  • Charlotte Maschke
  • Yacine Mahdid
  • Kathleen Berkun
  • Jason da Silva Castanheira
  • Vijay Tarnal
  • Paul Picton
  • Giancarlo Vanini

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.

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YNICL Journal 2021 Journal Article

Magnetoencephalography abnormalities in adult mild traumatic brain injury: A systematic review

  • Christopher M. Allen
  • Lloyd Halsey
  • Gogem Topcu
  • Lukas Rier
  • Lauren E. Gascoyne
  • John W Scadding
  • Paul L. Furlong
  • Benjamin T. Dunkley

BACKGROUND: The global incidence of traumatic brain injuries is rising, with at least 80% being classified as mild. These mild injuries are not visible on routine clinical imaging. The potential clinical role of a specific imaging biomarker be it diagnostic, prognostic or directing and monitoring progress of personalised treatment and rehabilitation has driven the exploration of several new neuroimaging modalities. This systematic review examined the evidence for magnetoencephalography (MEG) to provide an imaging biomarker in mild traumatic brain injury (mTBI). METHODS: Our review was prospectively registered on PROSPERO: CRD42019151387. We searched EMBASE, MEDLINE, trial registers, PsycINFO, Cochrane Library and conference abstracts and identified 37 papers describing MEG changes in mTBI eligible for inclusion. Since meta-analysis was not possible, based on the heterogeneity of reported outcomes, we provide a narrative synthesis of results. RESULTS: The two most promising MEG biomarkers are excess resting state low frequency power, and widespread connectivity changes in all frequency bands. These may represent biomarkers with potential for diagnostic application, which reflect time sensitive changes, or may be capable of offering clinically relevant prognostic information. In addition, the rich data that MEG produces are well-suited to new methods of machine learning analysis, which is now being actively explored. INTERPRETATION: MEG reveals several promising biomarkers, in the absence of structural abnormalities demonstrable with either computerised tomography or magnetic resonance imaging. This review has not identified sufficient evidence to support routine clinical use of MEG in mTBI currently. However, verifying MEG's potential would help meet an urgent clinical need within civilian, sports and military medicine.

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YNIMG Journal 2021 Journal Article

Measuring functional connectivity with wearable MEG

  • Elena Boto
  • Ryan M. Hill
  • Molly Rea
  • Niall Holmes
  • Zelekha A. Seedat
  • James Leggett
  • Vishal Shah
  • James Osborne

Optically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that provide improved data quality, accommodate any subject group, allow data capture during movement and potentially reduce cost. However, OPM-MEG is a nascent technology and, to realise its potential, it must be shown to facilitate key neuroscientific measurements, such as the characterisation of brain networks. Networks, and the connectivities that underlie them, have become a core area of neuroscientific investigation, and their importance is underscored by many demonstrations of their disruption in brain disorders. Consequently, a demonstration of network measurements using OPM-MEG would be a significant step forward. Here, we aimed to show that a wearable 50-channel OPM-MEG system enables characterisation of the electrophysiological connectome. To this end, we measured connectivity in the resting state and during a visuo-motor task, using both OPM-MEG and a state-of-the-art 275-channel cryogenic MEG device. Our results show that resting-state connectome matrices from OPM and cryogenic systems exhibit a high degree of similarity, with correlation values >70%. In addition, in task data, similar differences in connectivity between individuals (scanned multiple times) were observed in cryogenic and OPM-MEG data, again demonstrating the fidelity of the OPM-MEG device. This is the first demonstration of network connectivity measured using OPM-MEG, and results add weight to the argument that OPMs will ultimately supersede cryogenic sensors for MEG measurement.

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YNIMG Journal 2021 Journal Article

Measuring the cortical tracking of speech with optically-pumped magnetometers

  • Paul de Lange
  • Elena Boto
  • Niall Holmes
  • Ryan M. Hill
  • Richard Bowtell
  • Vincent Wens
  • Xavier De Tiège
  • Matthew J. Brookes

During continuous speech listening, brain activity tracks speech rhythmicity at frequencies matching with the repetition rate of phrases (0.2-1.5 Hz), words (2-4 Hz) and syllables (4-8 Hz). Here, we evaluated the applicability of wearable MEG based on optically-pumped magnetometers (OPMs) to measure such cortical tracking of speech (CTS). Measuring CTS with OPMs is a priori challenging given the complications associated with OPM measurements at frequencies below 4 Hz, due to increased intrinsic interference and head movement artifacts. Still, this represents an important development as OPM-MEG provides lifespan compliance and substantially improved spatial resolution compared with classical MEG. In this study, four healthy right-handed adults listened to continuous speech for 9 min. The radial component of the magnetic field was recorded simultaneously with 45-46 OPMs evenly covering the scalp surface and fixed to an additively manufactured helmet which fitted all 4 participants. We estimated CTS with reconstruction accuracy and coherence, and determined the number of dominant principal components (PCs) to remove from the data (as a preprocessing step) for optimal estimation. We also identified the dominant source of CTS using a minimum norm estimate. CTS estimated with reconstruction accuracy and coherence was significant in all 4 participants at phrasal and word rates, and in 3 participants (reconstruction accuracy) or 2 (coherence) at syllabic rate. Overall, close-to-optimal CTS estimation was obtained when the 3 (reconstruction accuracy) or 10 (coherence) first PCs were removed from the data. Importantly, values of reconstruction accuracy (~0.4 for 0.2-1.5-Hz CTS and ~0.1 for 2-8-Hz CTS) were remarkably close to those previously reported in classical MEG studies. Finally, source reconstruction localized the main sources of CTS to bilateral auditory cortices. In conclusion, t his study demonstrates that OPMs can be used for the purpose of CTS assessment. This finding opens new research avenues to unravel the neural network involved in CTS across the lifespan and potential alterations in, e.g., language developmental disorders. Data also suggest that OPMs are generally suitable for recording neural activity at frequencies below 4 Hz provided PCA is used as a preprocessing step; 0.2-1.5-Hz being the lowest frequency range successfully investigated here.

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YNICL Journal 2021 Journal Article

Mild traumatic brain injury impairs the coordination of intrinsic and motor-related neural dynamics

  • Lukas Rier
  • Rouzbeh Zamyadi
  • Jing Zhang
  • Zahra Emami
  • Zelekha A. Seedat
  • Sergiu Mocanu
  • Lauren E. Gascoyne
  • Christopher M. Allen

Mild traumatic brain injury (mTBI) poses a considerable burden on healthcare systems. Whilst most patients recover quickly, a significant number suffer from sequelae that are not accompanied by measurable structural damage. Understanding the neural underpinnings of these debilitating effects and developing a means to detect injury, would address an important unmet clinical need. It could inform interventions and help predict prognosis. Magnetoencephalography (MEG) affords excellent sensitivity in probing neural function and presents significant promise for assessing mTBI, with abnormal neural oscillations being a potential specific biomarker. However, growing evidence suggests that neural dynamics are (at least in part) driven by transient, pan-spectral bursting and in this paper, we employ this model to investigate mTBI. We applied a Hidden Markov Model to MEG data recorded during resting state and a motor task and show that previous findings of diminished intrinsic beta amplitude in individuals with mTBI are largely due to the reduced beta band spectral content of bursts, and that diminished beta connectivity results from a loss in the temporal coincidence of burst states. In a motor task, mTBI results in diminished burst amplitude, altered modulation of burst probability during movement, and a loss in connectivity in motor networks. These results suggest that, mechanistically, mTBI disrupts the structural framework underlying neural synchrony, which impairs network function. Whilst the damage may be too subtle for structural imaging to see, the functional consequences are detectable and persist after injury. Our work shows that mTBI impairs the dynamic coordination of neural network activity and proposes a potent new method for understanding mTBI.

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YNICL Journal 2021 Journal Article

Motor-related oscillatory activity in schizophrenia according to phase of illness and clinical symptom severity

  • Lauren E. Gascoyne
  • Matthew J. Brookes
  • Mohanbabu Rathnaiah
  • Mohammad Zia Ul Haq Katshu
  • Loes Koelewijn
  • Gemma Williams
  • Jyothika Kumar
  • James T.R. Walters

Magnetoencephalography (MEG) measures magnetic fields generated by synchronised neural current flow and provides direct inference on brain electrophysiology and connectivity, with high spatial and temporal resolution. The movement-related beta decrease (MRBD) and the post-movement beta rebound (PMBR) are well-characterised effects in magnetoencephalography (MEG), with the latter having been shown to relate to long-range network integrity. Our previous work has shown that the PMBR is diminished (relative to controls) in a group of schizophrenia patients. However, little is known about how this effect might differ in patients at different stages of illness and degrees of clinical severity. Here, we extend our previous findings showing that the MEG derived PMBR abnormality in schizophrenia exists in 29 recent-onset and 35 established cases (i.e., chronic patients), compared to 42 control cases. In established cases, PMBR is negatively correlated with severity of disorganization symptoms. Further, using a hidden Markov model analysis, we show that transient pan-spectral oscillatory "bursts", which underlie the PMBR, differ between healthy controls and patients. Results corroborate that PMBR is associated with disorganization of mental activity in schizophrenia.

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YNIMG Journal 2021 Journal Article

Mouth magnetoencephalography: A unique perspective on the human hippocampus

  • Tim M. Tierney
  • Andrew Levy
  • Daniel N. Barry
  • Sofie S. Meyer
  • Yoshihito Shigihara
  • Matt Everatt
  • Stephanie Mellor
  • Jose David Lopez

Traditional magnetoencephalographic (MEG) brain imaging scanners consist of a rigid sensor array surrounding the head; this means that they are maximally sensitive to superficial brain structures. New technology based on optical pumping means that we can now consider more flexible and creative sensor placement. Here we explored the magnetic fields generated by a model of the human hippocampus not only across scalp but also at the roof of the mouth. We found that simulated hippocampal sources gave rise to dipolar field patterns with one scalp surface field extremum at the temporal lobe and a corresponding maximum or minimum at the roof of the mouth. We then constructed a fitted dental mould to accommodate an Optically Pumped Magnetometer (OPM). We collected data using a previously validated hippocampal-dependant task to test the empirical utility of a mouth-based sensor, with an accompanying array of left and right temporal lobe OPMs. We found that the mouth sensor showed the greatest task-related theta power change. We found that this sensor had a mild effect on the reconstructed power in the hippocampus (~10% change) but that coherence images between the mouth sensor and reconstructed source images showed a global maximum in the right hippocampus. We conclude that augmenting a scalp-based MEG array with sensors in the mouth shows unique promise for both basic scientists and clinicians interested in interrogating the hippocampus.

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YNIMG Journal 2021 Journal Article

Precision magnetic field modelling and control for wearable magnetoencephalography

  • Molly Rea
  • Niall Holmes
  • Ryan M. Hill
  • Elena Boto
  • James Leggett
  • Lucy J. Edwards
  • David Woolger
  • Eliot Dawson

Optically-pumped magnetometers (OPMs) are highly sensitive, compact magnetic field sensors, which offer a viable alternative to cryogenic sensors (superconducting quantum interference devices - SQUIDs) for magnetoencephalography (MEG). With the promise of a wearable system that offers lifespan compliance, enables movement during scanning, and provides higher quality data, OPMs could drive a step change in MEG instrumentation. However, this potential can only be realised if background magnetic fields are appropriately controlled, via a combination of optimised passive magnetic screening (i.e. enclosing the system in layers of high-permeability materials), and electromagnetic coils to further null the remnant magnetic field. In this work, we show that even in an OPM-optimised passive shield with extremely low (<2 nT) remnant magnetic field, head movement generates significant artefacts in MEG data that manifest as low-frequency interference. To counter this effect we introduce a magnetic field mapping technique, in which the participant moves their head to sample the background magnetic field using a wearable sensor array; resulting data are compared to a model to derive coefficients representing three uniform magnetic field components and five magnetic field gradient components inside the passive shield. We show that this technique accurately reconstructs the magnitude of known magnetic fields. Moreover, by feeding the obtained coefficients into a bi-planar electromagnetic coil system, we were able to reduce the uniform magnetic field experienced by the array from a magnitude of 1.3±0.3 nT to 0.29±0.07 nT. Most importantly, we show that this field compensation generates a five-fold reduction in motion artefact at 0‒2 Hz, in a visual steady-state evoked response experiment using 6 Hz stimulation. We suggest that this technique could be used in future OPM-MEG experiments to improve the quality of data, especially in paradigms seeking to measure low-frequency oscillations, or in experiments where head movement is encouraged.

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YNIMG Journal 2021 Journal Article

Theoretical advantages of a triaxial optically pumped magnetometer magnetoencephalography system

  • Matthew J. Brookes
  • Elena Boto
  • Molly Rea
  • Vishal Shah
  • James Osborne
  • Niall Holmes
  • Ryan M. Hill
  • James Leggett

The optically pumped magnetometer (OPM) is a viable means to detect magnetic fields generated by human brain activity. Compared to conventional detectors (superconducting quantum interference devices) OPMs are small, lightweight, flexible, and operate without cryogenics. This has led to a step change in instrumentation for magnetoencephalography (MEG), enabling a "wearable" scanner platform, adaptable to fit any head size, able to acquire data whilst subjects move, and offering improved data quality. Although many studies have shown the efficacy of 'OPM-MEG', one relatively untapped advantage relates to improved array design. Specifically, OPMs enable the simultaneous measurement of magnetic field components along multiple axes (distinct from a single radial orientation, as used in most conventional MEG systems). This enables characterisation of the magnetic field vector at all sensors, affording extra information which has the potential to improve source reconstruction. Here, we conduct a theoretical analysis of the critical parameters that should be optimised for effective source reconstruction. We show that these parameters can be optimised by judicious array design incorporating triaxial MEG measurements. Using simulations, we demonstrate how a triaxial array offers a dramatic improvement on our ability to differentiate real brain activity from sources of magnetic interference (external to the brain). Further, a triaxial system is shown to offer a marked improvement in the elimination of artefact caused by head movement. Theoretical results are supplemented by an experimental recording demonstrating improved interference reduction. These findings offer new insights into how future OPM-MEG arrays can be designed with improved performance.

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YNIMG Journal 2020 Journal Article

Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system

  • Ryan M. Hill
  • Elena Boto
  • Molly Rea
  • Niall Holmes
  • James Leggett
  • Laurence A. Coles
  • Manolis Papastavrou
  • Sarah K. Everton

Magnetoencephalography (MEG) is a powerful technique for functional neuroimaging, offering a non-invasive window on brain electrophysiology. MEG systems have traditionally been based on cryogenic sensors which detect the small extracranial magnetic fields generated by synchronised current in neuronal assemblies, however, such systems have fundamental limitations. In recent years, non-cryogenic quantum-enabled sensors, called optically-pumped magnetometers (OPMs), in combination with novel techniques for accurate background magnetic field control, have promised to lift those restrictions offering an adaptable, motion-robust MEG system, with improved data quality, at reduced cost. However, OPM-MEG remains a nascent technology, and whilst viable systems exist, most employ small numbers of sensors sited above targeted brain regions. Here, building on previous work, we construct a wearable OPM-MEG system with ‘whole-head’ coverage based upon commercially available OPMs, and test its capabilities to measure alpha, beta and gamma oscillations. We design two methods for OPM mounting; a flexible (EEG-like) cap and rigid (additively-manufactured) helmet. Whilst both designs allow for high quality data to be collected, we argue that the rigid helmet offers a more robust option with significant advantages for reconstruction of field data into 3D images of changes in neuronal current. Using repeat measurements in two participants, we show signal detection for our device to be highly robust. Moreover, via application of source-space modelling, we show that, despite having 5 times fewer sensors, our system exhibits comparable performance to an established cryogenic MEG device. While significant challenges still remain, these developments provide further evidence that OPM-MEG is likely to facilitate a step change for functional neuroimaging.

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YNICL Journal 2020 Journal Article

Multilayer MEG functional connectivity as a potential marker for suicidal thoughts in major depressive disorder

  • Allison C. Nugent
  • Elizabeth D. Ballard
  • Jessica R. Gilbert
  • Prejaas K. Tewarie
  • Matthew J. Brookes
  • Carlos A. Zarate

Major depressive disorder (MDD) is highly heterogeneous in its clinical presentation. The present exploratory study used magnetoencephalography (MEG) to investigate electrophysiological intrinsic connectivity differences between healthy volunteers and unmedicated participants with treatment-resistant MDD. The study examined canonical frequency bands from delta through gamma. In addition to group comparisons, correlational studies were conducted to determine whether connectivity was related to five symptom factors: depressed mood, tension, negative cognition, suicidal thoughts, and amotivation. The MDD and healthy volunteer groups did not differ significantly at baseline when corrected across all frequencies and clusters, although evidence of generalized slowing in MDD was observed. Notably, however, electrophysiological connectivity was strongly related to suicidal thoughts, particularly as coupling of low frequency power fluctuations (delta and theta) with alpha and beta power. This analysis revealed hub areas underlying this symptom cluster, including left hippocampus, left anterior insula, and bilateral dorsolateral prefrontal cortex. No other symptom cluster demonstrated a relationship with neurophysiological connectivity, suggesting a specificity to these results as markers of suicidal ideation.

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YNIMG Journal 2020 Journal Article

Post-stimulus beta responses are modulated by task duration

  • Daisie O. Pakenham
  • Andrew J. Quinn
  • Adam Fry
  • Susan T. Francis
  • Mark W. Woolrich
  • Matthew J. Brookes
  • Karen J. Mullinger

Modulation of beta-band neural oscillations during and following movement is a robust marker of brain function. In particular, the post-movement beta rebound (PMBR), which occurs on movement cessation, has been related to inhibition and connectivity in the healthy brain, and is perturbed in disease. However, to realise the potential of the PMBR as a biomarker, its modulation by task parameters must be characterised and its functional role determined. Here, we used MEG to image brain electrophysiology during and after a grip-force task, with the aim to characterise how task duration, in the form of an isometric contraction, modulates beta responses. Fourteen participants exerted a 30% maximum voluntary grip-force for 2, 5 and 10 s. Our results showed that the amplitude of the PMBR is modulated by task duration, with increasing duration significantly reducing PMBR amplitude and increasing its time-to-peak. No variation in the amplitude of the movement related beta decrease (MRBD) with task duration was observed. To gain insight into what may underlie these trial-averaged results, we used a Hidden Markov Model to identify the individual trial dynamics of a brain network encompassing bilateral sensorimotor areas. The rapidly evolving dynamics of this network demonstrated similar variation with task parameters to the ‘classical’ rebound, and we show that the modulation of the PMBR can be well-described in terms of increased frequency of beta events on a millisecond timescale rather than modulation of beta amplitude during this time period. Our results add to the emerging picture that, in the case of a carefully controlled paradigm, beta modulation can be systematically controlled by task parameters and such control can reveal new information as to the processes that generate the average beta timecourse. These findings will support design of clinically relevant paradigms and analysis pipelines in future use of the PMBR as a marker of neuropathology.

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YNIMG Journal 2020 Journal Article

The role of transient spectral ‘bursts’ in functional connectivity: A magnetoencephalography study

  • Zelekha A. Seedat
  • Andrew J. Quinn
  • Diego Vidaurre
  • Lucrezia Liuzzi
  • Lauren E. Gascoyne
  • Benjamin A.E. Hunt
  • George C. O’Neill
  • Daisie O. Pakenham

Neural oscillations dominate electrophysiological measures of macroscopic brain activity and fluctuations in these rhythms offer an insightful window on cortical excitation, inhibition, and connectivity. However, in recent years the ‘classical’ picture of smoothly varying oscillations has been challenged by the idea that many ‘oscillations’ may actually be formed from the recurrence of punctate high-amplitude bursts in activity, whose spectral composition intersects the traditionally defined frequency ranges (e. g. alpha/beta band). This finding offers a new interpretation of measurable brain activity, however neither the methodological means to detect bursts, nor their link to other findings (e. g. connectivity) have been settled. Here, we use a new approach to detect bursts in magnetoencephalography (MEG) data. We show that a time-delay embedded Hidden Markov Model (HMM) can be used to delineate single-region bursts which are in agreement with existing techniques. However, unlike existing techniques, the HMM looks for specific spectral patterns in timecourse data. We characterise the distribution of burst duration, frequency of occurrence and amplitude across the cortex in resting state MEG data. During a motor task we show how the movement related beta decrease and post movement beta rebound are driven by changes in burst occurrence. Finally, we show that the beta band functional connectome can be derived using a simple measure of burst overlap, and that coincident bursts in separate regions correspond to a period of heightened coherence. In summary, this paper offers a new methodology for burst identification and connectivity analysis which will be important for future investigations of neural oscillations.

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YNIMG Journal 2019 Journal Article

How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes

  • Prejaas Tewarie
  • Romesh Abeysuriya
  • Áine Byrne
  • George C. O'Neill
  • Stamatios N. Sotiropoulos
  • Matthew J. Brookes
  • Stephen Coombes

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 network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1–4 Hz) to the high gamma band (40–70 Hz). These predictions outperform predictions based from surrogate data, suggesting a genuine relationship between eigenmodes of the structural network and frequency specific MEG networks. We then show that the relevant set of eigenmodes can be excited in a network of neural mass models using linear stability analysis only by including delays. Excitation of an eigenmode in this context refers to a dynamic instability of a network steady state to a spatial pattern with a corresponding coherent temporal oscillation. Simulations verify the results from linear stability analysis and suggest that theta, alpha and beta band networks emerge very near to the bifurcation. The delta and gamma bands in the resting state emerges further away from the bifurcation. These results show for the first time how delayed interactions can excite the relevant set of eigenmodes that give rise to frequency specific functional connectivity patterns.

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YNIMG Journal 2019 Journal Article

Imaging human cortical responses to intraneural microstimulation using magnetoencephalography

  • George C. O'Neill
  • Roger H. Watkins
  • Rochelle Ackerley
  • Eleanor L. Barratt
  • Ayan Sengupta
  • Michael Asghar
  • Rosa Maria Sanchez Panchuelo
  • Matthew J. Brookes

The sensation of touch in the glabrous skin of the human hand is conveyed by thousands of fast-conducting mechanoreceptive afferents, which can be categorised into four distinct types. The spiking properties of these afferents in the periphery in response to varied tactile stimuli are well-characterised, but relatively little is known about the spatiotemporal properties of the neural representations of these different receptor types in the human cortex. Here, we use the novel methodological combination of single-unit intraneural microstimulation (INMS) with magnetoencephalography (MEG) to localise cortical representations of individual touch afferents in humans, by measuring the extracranial magnetic fields from neural currents. We found that by assessing the modulation of the beta (13–30 Hz) rhythm during single-unit INMS, significant changes in oscillatory amplitude occur in the contralateral primary somatosensory cortex within and across a group of fast adapting type I mechanoreceptive afferents, which corresponded well to the induced response from matched vibrotactile stimulation. Combining the spatiotemporal specificity of MEG with the selective single-unit stimulation of INMS enables the interrogation of the central representations of different aspects of tactile afferent signalling within the human cortices. The fundamental finding that single-unit INMS ERD responses are robust and consistent with natural somatosensory stimuli will permit us to more dynamically probe the central nervous system responses in humans, to address questions about the processing of touch from the different classes of mechanoreceptive afferents and the effects of varying the stimulus frequency and patterning.

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YNIMG Journal 2019 Journal Article

Imaging the human hippocampus with optically-pumped magnetoencephalography

  • Daniel N. Barry
  • Tim M. Tierney
  • Niall Holmes
  • Elena Boto
  • Gillian Roberts
  • James Leggett
  • Richard Bowtell
  • Matthew J. Brookes

Optically-pumped (OP) magnetometers allow magnetoencephalography (MEG) to be performed while a participant’s head is unconstrained. To fully leverage this new technology, and in particular its capacity for mobility, the activity of deep brain structures which facilitate explorative behaviours such as navigation, must be detectable using OP-MEG. One such crucial brain region is the hippocampus. Here we had three healthy adult participants perform a hippocampal-dependent task – the imagination of novel scene imagery – while being scanned using OP-MEG. A conjunction analysis across these three participants revealed a significant change in theta power in the medial temporal lobe. The peak of this activated cluster was located in the anterior hippocampus. We repeated the experiment with the same participants in a conventional SQUID-MEG scanner and found similar engagement of the medial temporal lobe, also with a peak in the anterior hippocampus. These OP-MEG findings indicate exciting new opportunities for investigating the neural correlates of a range of crucial cognitive functions in naturalistic contexts including spatial navigation, episodic memory and social interactions.

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YNIMG Journal 2019 Journal Article

Optically pumped magnetometers: From quantum origins to multi-channel magnetoencephalography

  • Tim M. Tierney
  • Niall Holmes
  • Stephanie Mellor
  • José David López
  • Gillian Roberts
  • Ryan M. Hill
  • Elena Boto
  • James Leggett

Optically Pumped Magnetometers (OPMs) have emerged as a viable and wearable alternative to cryogenic, superconducting MEG systems. This new generation of sensors has the advantage of not requiring cryogenic cooling and as a result can be flexibly placed on any part of the body. The purpose of this review is to provide a neuroscience audience with the theoretical background needed to understand the physical basis for the signal observed by OPMs. Those already familiar with the physics of MRI and NMR should note that OPMs share much of the same theory as the operation of OPMs rely on magnetic resonance. This review establishes the physical basis for the signal equation for OPMs. We re-derive the equations defining the bounds on OPM performance and highlight the important trade-offs between quantities such as bandwidth, sensor size and sensitivity. These equations lead to a direct upper bound on the gain change due to cross-talk for a multi-channel OPM system.

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YNIMG Journal 2019 Journal Article

Towards OPM-MEG in a virtual reality environment

  • Gillian Roberts
  • Niall Holmes
  • Nicholas Alexander
  • Elena Boto
  • James Leggett
  • Ryan M. Hill
  • Vishal Shah
  • Molly Rea

Virtual reality (VR) provides an immersive environment in which a participant can experience a feeling of presence in a virtual world. Such environments generate strong emotional and physical responses and have been used for wide-ranging applications. The ability to collect functional neuroimaging data whilst a participant is immersed in VR would represent a step change for experimental paradigms; unfortunately, traditional brain imaging requires participants to remain still, limiting the scope of naturalistic interaction within VR. Recently however, a new type of magnetoencephalography (MEG) device has been developed, that employs scalp-mounted optically-pumped magnetometers (OPMs) to measure brain electrophysiology. Lightweight OPMs, coupled with precise control of the background magnetic field, enables participant movement during data acquisition. Here, we exploit this technology to acquire MEG data whilst a participant uses a virtual reality head-mounted display (VRHMD). We show that, despite increased magnetic interference from the VRHMD, we were able to measure modulation of alpha-band oscillations, and the visual evoked field. Moreover, in a VR experiment in which a participant had to move their head to look around a virtual wall and view a visual stimulus, we showed that the measured MEG signals map spatially in accordance with the known organisation of primary visual cortex. This technique could transform the type of neuroscientific experiment that can be undertaken using functional neuroimaging.

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YNIMG Journal 2019 Journal Article

Tracking dynamic brain networks using high temporal resolution MEG measures of functional connectivity

  • Prejaas Tewarie
  • Lucrezia Liuzzi
  • George C. O'Neill
  • Andrew J. Quinn
  • Alessandra Griffa
  • Mark W. Woolrich
  • Cornelis J. Stam
  • Arjan Hillebrand

Fluctuations in functional interactions between brain regions typically occur at the millisecond time scale. Conventional connectivity metrics are not adequately time-resolved to detect such fast fluctuations in functional connectivity. At the same time, attempts to use conventional metrics in a time-resolved manner usually come with the selection of sliding windows of fixed arbitrary length. In the current work, we evaluated the use of high temporal resolution metrics of functional connectivity in conjunction with non-negative tensor factorisation to detect fast fluctuations in connectivity and temporally evolving subnetworks. To this end, we used the phase difference derivative, wavelet coherence, and we also introduced a new metric, the instantaneous amplitude correlation. In order to deal with the inherently noisy nature of magnetoencephalography data and large datasets, we make use of recurrence plots and we used pair-wise orthogonalisation to avoid spurious estimates of functional connectivity due to signal leakage. Firstly, metrics were evaluated in the context of dynamically coupled neural mass models in the presence and absence of delays and also compared to conventional static metrics with fixed sliding windows. Simulations showed that these high temporal resolution metrics outperformed conventional static connectivity metrics. Secondly, the sensitivity of the metrics to fluctuations in connectivity was analysed in post-movement beta rebound magnetoencephalography data, which showed time locked sensorimotor subnetworks that modulated with the post-movement beta rebound. Finally, sensitivity of the metrics was evaluated in resting-state magnetoencephalography, showing similar spatial patterns across metrics, thereby indicating the robustness of the current analysis. The current methods can be applied in cognitive experiments that involve fast modulations in connectivity in relation to cognition. In addition, these methods could also be used as input to temporal graph analysis to further characterise the rapid fluctuation in brain network topology.

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YNIMG Journal 2019 Journal Article

Wearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography

  • Elena Boto
  • Zelekha A. Seedat
  • Niall Holmes
  • James Leggett
  • Ryan M. Hill
  • Gillian Roberts
  • Vishal Shah
  • T. Mark Fromhold

One of the most severe limitations of functional neuroimaging techniques, such as magnetoencephalography (MEG), is that participants must maintain a fixed head position during data acquisition. This imposes restrictions on the characteristics of the experimental cohorts that can be scanned and the experimental questions that can be addressed. For these reasons, the use of ‘wearable’ neuroimaging, in which participants can move freely during scanning, is attractive. The most successful example of wearable neuroimaging is electroencephalography (EEG), which employs lightweight and flexible instrumentation that makes it useable in almost any experimental setting. However, EEG has major technical limitations compared to MEG, and therefore the development of wearable MEG, or hybrid MEG/EEG systems, is a compelling prospect. In this paper, we combine and compare EEG and MEG measurements, the latter made using a new generation of optically-pumped magnetometers (OPMs). We show that these new second generation commercial OPMs, can be mounted on the scalp in an ‘EEG-like’ cap, enabling the acquisition of high fidelity electrophysiological measurements. We show that these sensors can be used in conjunction with conventional EEG electrodes, offering the potential for the development of hybrid MEG/EEG systems. We compare concurrently measured signals, showing that, whilst both modalities offer high quality data in stationary subjects, OPM-MEG measurements are less sensitive to artefacts produced when subjects move. Finally, we show using simulations that OPM-MEG offers a fundamentally better spatial specificity than EEG. The demonstrated technology holds the potential to revolutionise the utility of functional brain imaging, exploiting the flexibility of wearable systems to facilitate hitherto impractical experimental paradigms.

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YNIMG Journal 2018 Journal Article

A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography

  • Niall Holmes
  • James Leggett
  • Elena Boto
  • Gillian Roberts
  • Ryan M. Hill
  • Tim M. Tierney
  • Vishal Shah
  • Gareth R. Barnes

Small, commercially-available Optically Pumped Magnetometers (OPMs) can be used to construct a wearable Magnetoencephalography (MEG) system that allows large head movements to be made during recording. The small dynamic range of these sensors however means that movement in the residual static magnetic field found inside typical Magnetically Shielded Rooms (MSRs) can saturate the sensor outputs, rendering the data unusable. This problem can be ameliorated by using a set of electromagnetic coils to attenuate the spatially-varying remnant field. Here, an array of bi-planar coils, which produce an open and accessible scanning environment, was designed and constructed. The coils were designed using a harmonic minimisation method previously used for gradient coil design in Magnetic Resonance Imaging (MRI). Six coils were constructed to null B x, B y and B z as well as the three dominant field gradients d B x / d z, d B y / d z and d B z / d z. The coils produce homogeneous (within ±5%) fields or field gradients over a volume of 40 × 40 × 40 cm3. This volume is sufficient to contain an array of OPMs, mounted in a 3D-printed scanner-cast, during basic and natural movements. Automated control of the coils using reference sensor measurements allows reduction of the largest component of the static field ( B x ) from 21. 8 ± 0. 2 nT to 0. 47 ± 0. 08 nT. The largest gradient ( d B x / d z ) was reduced from 7. 4 nT/m to 0. 55 nT/m. High precision optical tracking allowed experiments involving controlled and measured head movements, which revealed that a rotation of the scanner-cast by ±34° and translation of ±9. 7 cm of the OPMs in this field generated only a 1 nT magnetic field variation across the OPM array, when field nulling was applied. This variation could be further reduced to 0. 04 nT by linear regression of field variations that were correlated with the measured motion parameters. To demonstrate the effectiveness of the bi-planar coil field cancellation system in a real MEG experiment, a novel measurement of retinotopy was investigated, where the stimulus remains fixed and head movements made by the subject shift the visual presentation to the lower left or right quadrants of the field of view. Left and right visual field stimulation produced the expected responses in the opposing hemisphere. This simple demonstration shows that the bi-planar coil system allows accurate OPM-MEG recordings to be made on an unrestrained subject.

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YNIMG Journal 2018 Journal Article

Altered temporal stability in dynamic neural networks underlies connectivity changes in neurodevelopment

  • Matthew J. Brookes
  • Madeleine J. Groom
  • Lucrezia Liuzzi
  • Ryan M. Hill
  • Helen J.F. Smith
  • Paul M. Briley
  • Emma L. Hall
  • Benjamin A.E. Hunt

Network connectivity is an integral feature of human brain function, and characterising its maturational trajectory is a critical step towards understanding healthy and atypical neurodevelopment. Here, we used magnetoencephalography (MEG) to investigate both stationary (i. e. time averaged) and rapidly modulating (dynamic) electrophysiological connectivity, in participants aged from mid-childhood to early adulthood (youngest participant 9 years old; oldest participant 25 years old). Stationary functional connectivity (measured via inter-regional coordination of neural oscillations) increased with age in the alpha and beta frequency bands, particularly in bilateral parietal and temporo-parietal connections. Our dynamic analysis (also applied to alpha/beta oscillations) revealed the spatiotemporal signatures of 8 dynamic networks; these modulate on a ∼100 ms time scale, and temporal stability in attentional networks was found to increase with age. Significant overlap was found between age-modulated dynamic networks and inter-regional oscillatory coordination, implying that altered network dynamics underlie age related changes in functional connectivity. Our results provide novel insights into brain network electrophysiology, and lay a foundation for future work in childhood disorders.

Details DOI

YNICL Journal 2018 Journal Article

Changes in electrophysiological markers of cognitive control after administration of galantamine

  • Lauren E. Gascoyne
  • Karen J. Mullinger
  • Siân E. Robson
  • Jyothika Kumar
  • George C. O'Neill
  • Lena Palaniyappan
  • Peter G. Morris
  • Elizabeth B. Liddle

The healthy brain is able to maintain a stable balance between bottom-up sensory processing and top-down cognitive control. The neurotransmitter acetylcholine plays a substantial role in this. Disruption of this balance could contribute to symptoms occurring in psychosis, including subtle disruption of motor control and aberrant appropriation of salience to external stimuli; however the pathological mechanisms are poorly understood. On account of the role beta oscillations play in mediating cognitive control, investigation of beta oscillations is potentially informative about such mechanisms. Here, we used magnetoencephalography to investigate the effect of the acetylcholinesterase-inhibitor, galantamine, on beta oscillations within the sensorimotor region during both a sensorimotor task and a relevance-modulation task in healthy participants, employing a double blind randomized placebo controlled cross-over design. In the galantamine condition, we found a significant reduction in the post-movement beta rebound in the case of executed movements and also in a planned but not executed movement. In the latter case, the effect was significantly greater following task-relevant compared with irrelevant stimuli. The results suggest that the action of galantamine reduces the influence of top-down cognitive processing relative to bottom-up perceptual processing in a manner resembling changes previously reported in schizophrenia.

Details DOI

YNIMG Journal 2018 Journal Article

Cognitive neuroscience using wearable magnetometer arrays: Non-invasive assessment of language function

  • Tim M. Tierney
  • Niall Holmes
  • Sofie S. Meyer
  • Elena Boto
  • Gillian Roberts
  • James Leggett
  • Sarah Buck
  • Leonardo Duque-Muñoz

Recent work has demonstrated that Optically Pumped Magnetometers (OPMs) can be utilised to create a wearable Magnetoencephalography (MEG) system that is motion robust. In this study, we use this system to map eloquent cortex using a clinically validated language lateralisation paradigm (covert verb generation: 120 trials, ∼10 min total duration) in healthy adults (n = 3). We show that it is possible to lateralise and localise language function on a case by case basis using this system. Specifically, we show that at a sensor and source level we can reliably detect a lateralising beta band (15–30 Hz) desynchronization in all subjects. This is the first study of human cognition using OPMs and not only highlights this technology's utility as tool for (developmental) cognitive neuroscience but also its potential to contribute to surgical planning via mapping of eloquent cortex, especially in young children.

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YNIMG Journal 2018 Journal Article

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations

  • Kanad Mandke
  • Jil Meier
  • Matthew J. Brookes
  • Reuben D. O'Dea
  • Piet Van Mieghem
  • Cornelis J. Stam
  • Arjan Hillebrand
  • Prejaas Tewarie

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 interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison. We analyse how well-known biases for single layer networks, such as effects of group differences in link density and/or average connectivity, influence multilayer networks, and we compare four schemes that aim to correct for such biases: the minimum spanning tree (MST), effective graph resistance cost minimisation, efficiency cost optimisation (ECO) and a normalisation scheme based on singular value decomposition (SVD). These schemes can be applied to the layers independently or to the multilayer network as a whole. For correction applied to whole multilayer networks, only the SVD showed sufficient bias correction. For correction applied to individual layers, three schemes (ECO, MST, SVD) could correct for biases. By using generative models as well as empirical MEG and functional magnetic resonance imaging (fMRI) data, we further demonstrated that all schemes were sensitive to identify network topology when the original networks were perturbed. In conclusion, uncorrected multilayer network analysis leads to biases. These biases may differ between centres and studies and could consequently lead to unreproducible results in a similar manner as for single layer networks. We therefore recommend using correction schemes prior to multilayer network analysis for group comparisons.

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YNIMG Journal 2018 Journal Article

Dynamics of large-scale electrophysiological networks: A technical review

  • George C. O'Neill
  • Prejaas Tewarie
  • Diego Vidaurre
  • Lucrezia Liuzzi
  • Mark W. Woolrich
  • Matthew J. Brookes

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 inspired a shift in focus in the field of functional neuroimaging. Specifically, investigation into the activation elicited within certain regions by some stimulus or task has, in part, given way to analysis of patterns of co-activation or functional connectivity between distal regions. Recently, the functional connectivity community has been looking beyond the assumptions of stationarity that earlier work was based on, and has introduced methods to incorporate temporal dynamics into the analysis of connectivity. In particular, non-invasive electrophysiological data (magnetoencephalography/electroencephalography (MEG/EEG)), which provides direct measurement of whole-brain activity and rich temporal information, offers an exceptional window into such (potentially fast) brain dynamics. In this review, we discuss challenges, solutions, and a collection of analysis tools that have been developed in recent years to facilitate the investigation of dynamic functional connectivity using these imaging modalities. Further, we discuss the applications of these approaches in the study of cognition and neuropsychiatric disorders. Finally, we review some existing developments that, by using realistic computational models, pursue a deeper understanding of the underlying causes of non-stationary connectivity.

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YNIMG Journal 2018 Journal Article

Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures

  • J. Matias Palva
  • Sheng H. Wang
  • Satu Palva
  • Alexander Zhigalov
  • Simo Monto
  • Matthew J. Brookes
  • Jan-Mathijs Schoffelen
  • Karim Jerbi

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or “ghost” interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.

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YNIMG Journal 2018 Journal Article

Mapping the topological organisation of beta oscillations in motor cortex using MEG

  • Eleanor L. Barratt
  • Susan T. Francis
  • Peter G. Morris
  • Matthew J. Brookes

The spatial topology of the human motor cortex has been well studied, particularly using functional Magnetic Resonance Imaging (fMRI) which allows spatial separation of haemodynamic responses arising from stimulation of different body parts, individual digits and even spatially separate areas of the same digit. However, the spatial organisation of electrophysiological responses, particularly neural oscillations (rhythmic changes in electrical potential across cellular assemblies) has been less well studied. Mapping the spatial signature of neural oscillations is possible using magnetoencephalography (MEG), however spatial differentiation of responses induced by movement of separate digits is a challenge, because the brain regions involved are separated by only a few millimetres. In this paper we first show, in simulation, how to optimise experimental design and beamformer spatial filtering techniques to increase the spatial specificity of MEG derived functional images. Combining this result with experimental data, we then capture the organisation of the post-movement beta band (13–30 Hz) oscillatory response to movement of digits 2 and 5 of the dominant hand, in individual subjects. By comparing these MEG results to ultra-high field (7T) fMRI, we also show significant spatial agreement between beta modulation and the blood oxygenation level dependent (BOLD) response. Our results show that, when using an optimised inverse solution and controlling subject movement (using custom fitted foam padding) the spatial resolution of MEG can be of order 3–5 mm. The method described offers exciting potential to understand better the cortical organisation of oscillations, and to probe such organisation in patient populations where those oscillations are known to be abnormal.

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YNIMG Journal 2017 Journal Article

A new generation of magnetoencephalography: Room temperature measurements using optically-pumped magnetometers

  • Elena Boto
  • Sofie S. Meyer
  • Vishal Shah
  • Orang Alem
  • Svenja Knappe
  • Peter Kruger
  • T. Mark Fromhold
  • Mark Lim

Advances in the field of quantum sensing mean that magnetic field sensors, operating at room temperature, are now able to achieve sensitivity similar to that of cryogenically cooled devices (SQUIDs). This means that room temperature magnetoencephalography (MEG), with a greatly increased flexibility of sensor placement can now be considered. Further, these new sensors can be placed directly on the scalp surface giving, theoretically, a large increase in the magnitude of the measured signal. Here, we present recordings made using a single optically-pumped magnetometer (OPM) in combination with a 3D-printed head-cast designed to accurately locate and orient the sensor relative to brain anatomy. Since our OPM is configured as a magnetometer it is highly sensitive to environmental interference. However, we show that this problem can be ameliorated via the use of simultaneous reference sensor recordings. Using median nerve stimulation, we show that the OPM can detect both evoked (phase-locked) and induced (non-phase-locked oscillatory) changes when placed over sensory cortex, with signals ~4 times larger than equivalent SQUID measurements. Using source modelling, we show that our system allows localisation of the evoked response to somatosensory cortex. Further, source-space modelling shows that, with 13 sequential OPM measurements, source-space signal-to-noise ratio (SNR) is comparable to that from a 271-channel SQUID system. Our results highlight the opportunity presented by OPMs to generate uncooled, potentially low-cost, high SNR MEG systems.

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YNIMG Journal 2017 Journal Article

Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity

  • Jon M. Houck
  • Mustafa S. Çetin
  • Andrew R. Mayer
  • Juan R. Bustillo
  • Julia Stephen
  • Cheryl Aine
  • Jose Cañive
  • Nora Perrone-Bizzozero

Examination of intrinsic functional connectivity using functional MRI (fMRI) has provided important findings regarding dysconnectivity in schizophrenia. Extending these results using a complementary neuroimaging modality, magnetoencephalography (MEG), we present the first direct comparison of functional connectivity between schizophrenia patients and controls, using these two modalities combined. We developed a novel MEG approach for estimation of networks using MEG that incorporates spatial independent component analysis (ICA) and pairwise correlations between independent component timecourses, to estimate intra- and intern-network connectivity. This analysis enables group-level inference and testing of between-group differences. Resting state MEG and fMRI data were acquired from a large sample of healthy controls (n=45) and schizophrenia patients (n=46). Group spatial ICA was performed on fMRI and MEG data to extract intrinsic fMRI and MEG networks and to compensate for signal leakage in MEG. Similar, but not identical spatial independent components were detected for MEG and fMRI. Analysis of functional network connectivity (FNC; i. e. , pairwise correlations in network (ICA component) timecourses) revealed a differential between-modalities pattern, with greater connectivity among occipital networks in fMRI and among frontal networks in MEG. Most importantly, significant differences between controls and patients were observed in both modalities. MEG FNC results in particular indicated dysfunctional hyperconnectivity within frontal and temporal networks in patients, while in fMRI FNC was always greater for controls than for patients. This is the first study to apply group spatial ICA as an approach to leakage correction, and as such our results may be biased by spatial leakage effects. Results suggest that combining these two neuroimaging modalities reveals additional disease-relevant patterns of connectivity that were not detectable with fMRI or MEG alone.

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YNIMG Journal 2017 Journal Article

Measurement of dynamic task related functional networks using MEG

  • George C. O’Neill
  • Prejaas K. Tewarie
  • Giles L. Colclough
  • Lauren E. Gascoyne
  • Benjamin A.E. Hunt
  • Peter G. Morris
  • Mark W. Woolrich
  • Matthew J. Brookes

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 in the human brain using magnetoencephalography (MEG). Previous network analyses look for brain regions that share a common temporal profile of activity. Here distinctly, we exploit the high spatio-temporal resolution of MEG to measure the temporal evolution of connectivity between pairs of parcellated brain regions. We then use an ICA based procedure to identify networks of connections whose temporal dynamics covary. We validate our method using MEG data recorded during a finger movement task, identifying a transient network of connections linking somatosensory and primary motor regions, which modulates during the task. Next, we use our method to image the networks which support cognition during a Sternberg working memory task. We generate a novel neuroscientific picture of cognitive processing, showing the formation and dissolution of multiple networks which relate to semantic processing, pattern recognition and language as well as vision and movement. Our method tracks the dynamics of functional connectivity in the brain on a timescale commensurate to the task they are undertaking.

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YNIMG Journal 2017 Journal Article

Optimising experimental design for MEG resting state functional connectivity measurement

  • Lucrezia Liuzzi
  • Lauren E. Gascoyne
  • Prejaas K. Tewarie
  • Eleanor L. Barratt
  • Elena Boto
  • Matthew J. Brookes

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 demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of co-registration method and data recording duration. We show that the use of a foam head-cast, which is known to improve co-registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies.

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YNIMG Journal 2017 Journal Article

Using generative models to make probabilistic statements about hippocampal engagement in MEG

  • Sofie S. Meyer
  • Holly Rossiter
  • Matthew J. Brookes
  • Mark W. Woolrich
  • Sven Bestmann
  • Gareth R. Barnes

Magnetoencephalography (MEG) enables non-invasive real time characterization of brain activity. However, convincing demonstrations of signal contributions from deeper sources such as the hippocampus remain controversial and are made difficult by its depth, structural complexity and proximity to neocortex. Here, we demonstrate a method for quantifying hippocampal engagement probabilistically using simulated hippocampal activity and realistic anatomical and electromagnetic source modelling. We construct two generative models, one which supports neuronal current flow on the cortical surface, and one which supports neuronal current flow on both the cortical and hippocampal surface. Using Bayesian model comparison, we then infer which of the two models provides a more likely explanation of the dataset at hand. We also carry out a set of control experiments to rule out bias, including simulating medial temporal lobe sources to assess the risk of falsely positive results, and adding different types of displacements to the hippocampal portion of the mesh to test for anatomical specificity of the results. In addition, we test the robustness of this inference by adding co-registration error and sensor level noise. We find that the model comparison framework is sensitive to hippocampal activity when co-registration error is <3 mm and the sensor-level signal-to-noise ratio (SNR) is >−20 dB. These levels of co-registration error and SNR can now be achieved empirically using recently developed subject-specific head-casts.

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YNIMG Journal 2016 Journal Article

A multi-layer network approach to MEG connectivity analysis

  • Matthew J. Brookes
  • Prejaas K. Tewarie
  • Benjamin A.E. Hunt
  • Sian E. Robson
  • Lauren E. Gascoyne
  • Elizabeth B. Liddle
  • Peter F. Liddle
  • Peter G. Morris

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 the electrophysiological signal makes gaining a complete picture challenging. Specifically, connectivity can be calculated as statistical interdependencies between neural oscillations within a large range of different frequency bands. Further, connectivity can be computed between frequency bands. This pan-spectral network hierarchy likely helps to mediate simultaneous formation of multiple brain networks, which support ongoing task demand. However, to date it has been largely overlooked, with many electrophysiological functional connectivity studies treating individual frequency bands in isolation. Here, we combine oscillatory envelope based functional connectivity metrics with a multi-layer network framework in order to derive a more complete picture of connectivity within and between frequencies. We test this methodology using MEG data recorded during a visuomotor task, highlighting simultaneous and transient formation of motor networks in the beta band, visual networks in the gamma band and a beta to gamma interaction. Having tested our method, we use it to demonstrate differences in occipital alpha band connectivity in patients with schizophrenia compared to healthy controls. We further show that these connectivity differences are predictive of the severity of persistent symptoms of the disease, highlighting their clinical relevance. Our findings demonstrate the unique potential of MEG to characterise neural network formation and dissolution. Further, we add weight to the argument that dysconnectivity is a core feature of the neuropathology underlying schizophrenia.

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YNICL Journal 2016 Journal Article

Abnormal visuomotor processing in schizophrenia

  • Siân E. Robson
  • Matthew J. Brookes
  • Emma L. Hall
  • Lena Palaniyappan
  • Jyothika Kumar
  • Michael Skelton
  • Nikolaos G. Christodoulou
  • Ayaz Qureshi

Subtle disturbances of visual and motor function are known features of schizophrenia and can greatly impact quality of life; however, few studies investigate these abnormalities using simple visuomotor stimuli. In healthy people, electrophysiological data show that beta band oscillations in sensorimotor cortex decrease during movement execution (event-related beta desynchronisation (ERBD)), then increase above baseline for a short time after the movement (post-movement beta rebound (PMBR)); whilst in visual cortex, gamma oscillations are increased throughout stimulus presentation. In this study, we used a self-paced visuomotor paradigm and magnetoencephalography (MEG) to contrast these responses in patients with schizophrenia and control volunteers. We found significant reductions in the peak-to-peak change in amplitude from ERBD to PMBR in schizophrenia compared with controls. This effect was strongest in patients who made fewer movements, whereas beta was not modulated by movement in controls. There was no significant difference in the amplitude of visual gamma between patients and controls. These data demonstrate that clear abnormalities in basic sensorimotor processing in schizophrenia can be observed using a very simple MEG paradigm.

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YNIMG Journal 2016 Journal Article

Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach

  • Prejaas Tewarie
  • Arjan Hillebrand
  • Bob W. van Dijk
  • Cornelis J. Stam
  • George C. O'Neill
  • Piet Van Mieghem
  • Jil M. Meier
  • Mark W. Woolrich

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, it seems likely that the brain employs interactions within multiple frequency bands, as well as cross-frequency coupling, to support such networks. Here, we propose a multi-layer network framework that elucidates this pan-spectral picture of network interactions. Our network consists of multiple layers (frequency-band specific networks) that influence each other via inter-layer (cross-frequency) coupling. Applying this model to MEG resting-state data and using envelope correlations as connectivity metric, we demonstrate strong dependency between within layer structure and inter-layer coupling, indicating that networks obtained in different frequency bands do not act as independent entities. More specifically, our results suggest that frequency band specific networks are characterised by a common structure seen across all layers, superimposed by layer specific connectivity, and inter-layer coupling is most strongly associated with this common mode. Finally, using a biophysical model, we demonstrate that there are two regimes of multi-layer network behaviour; one in which different layers are independent and a second in which they operate highly dependent. Results suggest that the healthy human brain operates at the transition point between these regimes, allowing for integration and segregation between layers. Overall, our observations show that a complete picture of global brain network connectivity requires integration of connectivity patterns across the full frequency spectrum.

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YNIMG Journal 2015 Journal Article

Dynamic recruitment of resting state sub-networks

  • George C. O'Neill
  • Markus Bauer
  • Mark W. Woolrich
  • Peter G. Morris
  • Gareth R. Barnes
  • Matthew J. Brookes

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease.

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YNIMG Journal 2015 Journal Article

The effect of isocapnic hyperoxia on neurophysiology as measured with MRI and MEG

  • Paula L. Croal
  • Emma L. Hall
  • Ian D. Driver
  • Matthew J. Brookes
  • Penny A. Gowland
  • Susan T. Francis

The physiological effect of hyperoxia has been poorly characterize d, with studies reporting conflicting results on the role of hyperoxia as a vasoconstrictor. It is not clear whether hyperoxia is the primary contributor to vasoconstriction or whether induced changes in CO2 that commonly accompany hyperoxia are a factor. As calibrated BOLD fMRI based on hyperoxia becomes more widely used, it is essential to understand the effects of oxygen on resting cerebral physiology. This study used a RespirAct™ system to deliver a repeatable isocapnic hyperoxia stimulus to investigate the independent effect of O2 on cerebral physiology, removing any potential confounds related to altered CO2. T 1-independent Phase Contrast MRI was used to demonstrate that isocapnic hyperoxia has no significant effect on carotid blood flow (normoxia 201±11ml/min, −0. 3%±0. 8% change during hyperoxia, p =0. 8), while Look Locker ASL was used to demonstrate that there is no significant change in arterial cerebral blood volume (normoxia 1. 3%±0. 4%, −0. 5±5% change during hyperoxia). These are in contrast to significant changes in carotid blood flow observed for hypercapnia (6. 8%±1. 5%/mm Hg CO2). In addition, magnetoencephalography provided a method to monitor the effect of isocapnic hyperoxia on neuronal oscillatory power. In response to hyperoxia, a significant focal decrease in oscillatory power was observed across the alpha, beta and low gamma bands in the occipital lobe, compared to a more global significant decrease on hypercapnia. This work suggests that isocapnic hyperoxia provides a more reliable stimulus than hypercapnia for calibrated BOLD, and that previous reports of vasoconstriction during hyperoxia probably reflect the effects of hyperoxia-induced changes in CO2. However, hyperoxia does induce changes in oscillatory power consistent with an increase in vigilance, but these changes are smaller than those observed under hypercapnia. The effect of this change in neural activity on calibrated BOLD using hyperoxia or combined hyperoxia and hypercapnia needs further investigation.

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YNIMG Journal 2014 Journal Article

Measuring temporal, spectral and spatial changes in electrophysiological brain network connectivity

  • Matthew J. Brookes
  • George C. O'Neill
  • Emma L. Hall
  • Mark W. Woolrich
  • Adam Baker
  • Sofia Palazzo Corner
  • Siân E. Robson
  • Peter G. Morris

The topic of functional connectivity in neuroimaging is expanding rapidly and many studies now focus on coupling between spatially separate brain regions. These studies show that a relatively small number of large scale networks exist within the brain, and that healthy function of these networks is disrupted in many clinical populations. To date, the vast majority of studies probing connectivity employ techniques that compute time averaged correlation over several minutes, and between specific pre-defined brain locations. However, increasing evidence suggests that functional connectivity is non-stationary in time. Further, electrophysiological measurements show that connectivity is dependent on the frequency band of neural oscillations. It is also conceivable that networks exhibit a degree of spatial inhomogeneity, i. e. the large scale networks that we observe may result from the time average of multiple transiently synchronised sub-networks, each with their own spatial signature. This means that the next generation of neuroimaging tools to compute functional connectivity must account for spatial inhomogeneity, spectral non-uniformity and temporal non-stationarity. Here, we present a means to achieve this via application of windowed canonical correlation analysis (CCA) to source space projected MEG data. We describe the generation of time–frequency connectivity plots, showing the temporal and spectral distribution of coupling between brain regions. Moreover, CCA over voxels provides a means to assess spatial non-uniformity within short time–frequency windows. The feasibility of this technique is demonstrated in simulation and in a resting state MEG experiment where we elucidate multiple distinct spatio-temporal-spectral modes of covariation between the left and right sensorimotor areas.

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YNIMG Journal 2014 Journal Article

Multi-session statistics on beamformed MEG data

  • Henry T. Luckhoo
  • Matthew J. Brookes
  • Mark W. Woolrich

Beamforming has been widely adopted as a source reconstruction technique in the analysis of magnetoencephalography data. Most beamforming implementations incorporate a spatially-varying rescaling (which we term weights normalisation) to correct for the inherent depth bias in raw beamformer estimates. Here, we demonstrate that such rescaling can cause critical problems whenever analyses are performed over multiple sessions of separately beamformed data, for example when comparing effect sizes between different populations. Importantly, we show that the weights-normalised beamformer estimates of neural activity can even lead to a reversal in the inferred sign of the effect being measured. We instead recommend that no weights normalisation be carried out; any depth bias is instead accounted for in the calculation of multi-session (e. g. group) statistics. We demonstrate the severity of the weights normalisation confound with a 2-D simulation, and in real MEG data by performing a group statistical analysis to detect differences in alpha power in eyes-closed rest compared with continuous visual stimulation.

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YNIMG Journal 2014 Journal Article

The relationship between MEG and fMRI

  • Emma L. Hall
  • Siân E. Robson
  • Peter G. Morris
  • Matthew J. Brookes

In recent years functional neuroimaging techniques such as fMRI, MEG, EEG and PET have provided researchers with a wealth of information on human brain function. However none of these modalities can measure directly either the neuro-electrical or neuro-chemical processes that mediate brain function. This means that metrics directly reflecting brain ‘activity’ must be inferred from other metrics (e. g. magnetic fields (MEG) or haemodynamics (fMRI)). To overcome this limitation, many studies seek to combine multiple complementary modalities and an excellent example of this is the combination of MEG (which has high temporal resolution) with fMRI (which has high spatial resolution). However, the full potential of multi-modal approaches can only be truly realised in cases where the relationship between metrics is known. In this paper, we explore the relationship between measurements made using fMRI and MEG. We describe the origins of the two signals as well as their relationship to electrophysiology. We review multiple studies that have attempted to characterise the spatial relationship between fMRI and MEG, and we also describe studies that exploit the rich information content of MEG to explore differing relationships between MEG and fMRI across neural oscillatory frequency bands. Monitoring the brain at “rest” has become of significant recent interest to the neuroimaging community and we review recent evidence comparing MEG and fMRI metrics of functional connectivity. A brief discussion of the use of magnetic resonance spectroscopy (MRS) to probe the relationship between MEG/fMRI and neurochemistry is also given. Finally, we highlight future areas of interest and offer some recommendations for the parallel use of fMRI and MEG.

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YNIMG Journal 2013 Journal Article

The contribution of electrophysiology to functional connectivity mapping

  • Marieke L. Schölvinck
  • David A. Leopold
  • Matthew J. Brookes
  • Patrick H. Khader

A powerful way to probe brain function is to assess the relationship between simultaneous changes in activity across different parts of the brain. In recent years, the temporal activity correlation between brain areas has frequently been taken as a measure of their functional connections. Evaluating ‘functional connectivity’ in this way is particularly popular in the fMRI community, but has also drawn interest among electrophysiologists. Like hemodynamic fluctuations observed with fMRI, electrophysiological signals display significant temporal fluctuations, even in the absence of a stimulus. These neural fluctuations exhibit a correlational structure over a wide range of spatial and temporal scales. Initial evidence suggests that certain aspects of this correlational structure bear a high correspondence to so-called functional networks defined using fMRI. The growing family of methods to study activity covariation, combined with the diverse neural mechanisms that contribute to the spontaneous fluctuations, has somewhat blurred the operational concept of functional connectivity. What is clear is that spontaneous activity is a conspicuous, energy-consuming feature of the brain. Given its prominence and its practical applications for the functional connectivity mapping of brain networks, it is of increasing importance that we understand its neural origins as well as its contribution to normal brain function.

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YNIMG Journal 2013 Journal Article

Using variance information in magnetoencephalography measures of functional connectivity

  • Emma L. Hall
  • Mark W. Woolrich
  • Carlos E. Thomaz
  • Peter G. Morris
  • Matthew J. Brookes

The use of magnetoencephalography (MEG) to assess long range functional connectivity across large scale distributed brain networks is gaining popularity. Recent work has shown that electrodynamic networks can be assessed using both seed based correlation or independent component analysis (ICA) applied to MEG data and further that such metrics agree with fMRI studies. To date, techniques for MEG connectivity assessment have typically used a variance normalised approach, either through the use of Pearson correlation coefficients or via variance normalisation of envelope timecourses prior to ICA. Here, we show that the use of variance information (i. e. data that have not been variance normalised) in source space projected Hilbert envelope time series yields important spatial information, and is of significant functional relevance. Further, we show that employing this information in functional connectivity analyses improves the spatial delineation of network nodes using both seed based and ICA approaches. The use of variance is particularly important in MEG since the non-independence of source space voxels (brought about by the ill-posed MEG inverse problem) means that spurious signals can exist in areas of low signal variance. We therefore suggest that this approach be incorporated into future studies.

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YNIMG Journal 2011 Journal Article

Changes in brain network activity during working memory tasks: A magnetoencephalography study

  • Matthew J. Brookes
  • Jonathan R. Wood
  • Claire M. Stevenson
  • Johanna M. Zumer
  • Thomas P. White
  • Peter F. Liddle
  • Peter G. Morris

In this study, we elucidate the changes in neural oscillatory processes that are induced by simple working memory tasks. A group of eight subjects took part in modified versions of the N-back and Sternberg working memory paradigms. Magnetoencephalography (MEG) data were recorded, and subsequently processed using beamformer based source imaging methodology. Our study shows statistically significant increases in θ oscillations during both N-back and Sternberg tasks. These oscillations were shown to originate in the medial frontal cortex, and further to scale with memory load. We have also shown that increases in θ oscillations are accompanied by decreases in β and γ band oscillations at the same spatial coordinate. These decreases were most prominent in the 20–40Hz frequency range, although spectral analysis showed that γ band power decrease extends up to at least 80Hz. β/γ Power decrease also scales with memory load. Whilst θ increases were predominately observed in the medial frontal cortex, β/γ decreases were associated with other brain areas, including nodes of the default mode network (for the N-back task) and areas associated with language processing (for the Sternberg task). These observations are in agreement with intracranial EEG and fMRI studies. Finally, we have shown an intimate relationship between changes in β/γ band oscillatory power at spatially separate network nodes, implying that activity in these nodes is not reflective of uni-modal task driven changes in spatially separate brain regions, but rather represents correlated network activity. The utility of MEG as a non-invasive means to measure neural oscillatory modulation has been demonstrated and future studies employing this technology have the potential to gain a better understanding of neural oscillatory processes, their relationship to functional and effective connectivity, and their correspondence to BOLD fMRI.

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YNIMG Journal 2011 Journal Article

Measuring functional connectivity using MEG: Methodology and comparison with fcMRI

  • Matthew J. Brookes
  • Joanne R. Hale
  • Johanna M. Zumer
  • Claire M. Stevenson
  • Susan T. Francis
  • Gareth R. Barnes
  • Julia P. Owen
  • Peter G. Morris

Functional connectivity (FC) between brain regions is thought to be central to the way in which the brain processes information. Abnormal connectivity is thought to be implicated in a number of diseases. The ability to study FC is therefore a key goal for neuroimaging. Functional connectivity (fc) MRI has become a popular tool to make connectivity measurements but the technique is limited by its indirect nature. A multimodal approach is therefore an attractive means to investigate the electrodynamic mechanisms underlying hemodynamic connectivity. In this paper, we investigate resting state FC using fcMRI and magnetoencephalography (MEG). In fcMRI, we exploit the advantages afforded by ultra high magnetic field. In MEG we apply envelope correlation and coherence techniques to source space projected MEG signals. We show that beamforming provides an excellent means to measure FC in source space using MEG data. However, care must be taken when interpreting these measurements since cross talk between voxels in source space can potentially lead to spurious connectivity and this must be taken into account in all studies of this type. We show good spatial agreement between FC measured independently using MEG and fcMRI; FC between sensorimotor cortices was observed using both modalities, with the best spatial agreement when MEG data are filtered into the β band. This finding helps to reduce the potential confounds associated with each modality alone: while it helps reduce the uncertainties in spatial patterns generated by MEG (brought about by the ill posed inverse problem), addition of electrodynamic metric confirms the neural basis of fcMRI measurements. Finally, we show that multiple MEG based FC metrics allow the potential to move beyond what is possible using fcMRI, and investigate the nature of electrodynamic connectivity. Our results extend those from previous studies and add weight to the argument that neural oscillations are intimately related to functional connectivity and the BOLD response.

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YNIMG Journal 2011 Journal Article

The effect of hypercapnia on resting and stimulus induced MEG signals

  • Emma L. Hall
  • Ian D. Driver
  • Paula L. Croal
  • Susan T. Francis
  • Penny A. Gowland
  • Peter G. Morris
  • Matthew J. Brookes

The effect of hypercapnia (an increase in CO2 concentration in the blood) on the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) haemodynamic response has been well characterised and is commonly used for BOLD calibration. However, relatively little is known of the effect of hypercapnia on the electrical brain processes that underlie the BOLD response. Here, we investigate the effect of hypercapnia on resting and stimulus induced changes in neural oscillations using a feed-forward low gas flow system to deliver a reliable and repeatable level of hypercapnia. Magnetoencephalography (MEG) is used in conjunction with beamformer source localisation algorithms to non-invasively image changes in oscillatory amplitude. At rest, we find robust oscillatory power loss in the alpha (8Hz–13Hz), beta (13Hz–30Hz) and low gamma (30Hz–50Hz) frequency bands in response to hypercapnia. Further, we show that the spatial signature of this power loss differs across frequency bands, with the largest effect being observed for the beta band in sensorimotor cortices. We also measure changes in oscillatory activity induced by visual and motor events, and the effect of hypercapnia on these changes; whilst the percentage change in oscillatory activity on activation was largely unaffected by hypercapnia, the absolute change in oscillatory amplitude differed between normocapnia and hypercapnia. This work supports invasive recordings made in animals, and the results have potential implications for calibrated BOLD studies.

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YNIMG Journal 2010 Journal Article

Investigating spatial specificity and data averaging in MEG

  • Matthew J. Brookes
  • Johanna M. Zumer
  • Claire M. Stevenson
  • Joanne R. Hale
  • Gareth R. Barnes
  • Jiri Vrba
  • Peter G. Morris

This study shows that the spatial specificity of MEG beamformer estimates of electrical activity can be affected significantly by the way in which covariance estimates are calculated. We define spatial specificity as the ability to extract independent timecourse estimates of electrical brain activity from two separate brain locations in close proximity. Previous analytical and simulated results have shown that beamformer estimates are affected by narrowing the time frequency window in which covariance estimates are made. Here we build on this by both experimental validation of previous results, and investigating the effect of data averaging prior to covariance estimation. In appropriate circumstances, we show that averaging has a marked effect on spatial specificity. However the averaging process results in ill-conditioned covariance matrices, thus necessitating a suitable matrix regularisation strategy, an example of which is described. We apply our findings to an MEG retinotopic mapping paradigm. A moving visual stimulus is used to elicit brain activation at different retinotopic locations in the visual cortex. This gives the impression of a moving electrical dipolar source in the brain. We show that if appropriate beamformer optimisation is applied, the moving source can be tracked in the cortex. In addition to spatial reconstruction of the moving source, we show that timecourse estimates can be extracted from neighbouring locations of interest in the visual cortex. If appropriate methodology is employed, the sequential activation of separate retinotopic locations can be observed. The retinotopic paradigm represents an ideal platform to test the spatial specificity of source localisation strategies. We suggest that future comparisons of MEG source localisation techniques (e. g. beamformer, minimum norm, Bayesian) could be made using this retinotopic mapping paradigm.

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YNIMG Journal 2010 Journal Article

Relating BOLD fMRI and neural oscillations through convolution and optimal linear weighting

  • Johanna M. Zumer
  • Matthew J. Brookes
  • Claire M. Stevenson
  • Susan T. Francis
  • Peter G. Morris

The exact relationship between neural activity and BOLD fMRI is unknown. However, several recent findings, recorded invasively in both humans and monkeys, show a positive correlation of BOLD to high-frequency (30–150 Hz) oscillatory power changes and a negative correlation to low-frequency (8–30 Hz) power changes arising from cortical areas. In this study, we computed the time series correlation between BOLD GE-EPI fMRI at 7 T and neural activity measures from noninvasive MEG, using a time–frequency beam former for source localisation. A sinusoidal drifting grating was presented visually for 4 s followed by a 20 s rest period in both recording modalities. The MEG time series were convolved with either a measured or canonical haemodynamic response function (HRF) for comparison with the measured BOLD data, and the BOLD data were deconvolved with either a measured or a canonical HRF for comparison with the measured MEG. In the visual cortex, the higher frequencies (mid-gamma=52–75 Hz and high-gamma=75–98 Hz) were positively correlated with BOLD whilst the lower frequencies (alpha=8–12 Hz and beta=12–25 Hz) were negatively correlated with BOLD. Furthermore, regression including all frequency bands predicted BOLD better than stimulus timing alone, although no individual frequency band predicted BOLD as well as stimulus timing. For this paradigm, there was, in general, no difference between using the SPM canonical HRF compared to the subject-specific measured HRF. In conclusion, MEG replicates findings from invasive recordings with regard to time series correlations with BOLD data. Conversely, deconvolution of BOLD data provides a neural estimate which correlates well with measured neural effects as a function of neural oscillation frequency.

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YNIMG Journal 2009 Journal Article

Source localisation in concurrent EEG/fMRI: Applications at 7T

  • Matthew J. Brookes
  • Jiri Vrba
  • Karen J. Mullinger
  • Gerða Björk Geirsdóttir
  • Winston X. Yan
  • Claire M. Stevenson
  • Richard Bowtell
  • Peter G. Morris

This paper investigates the application of source reconstruction methodologies to EEG data recorded in concurrent EEG/fMRI experiments at 7T. An EEG phantom containing a dipolar current source is described and used to investigate the accuracy of source localisation. Both dipole fitting and beamformer algorithms are shown to yield accurate locations for the dipole within the phantom. Source reconstruction methodologies are also shown to reduce significantly the level of interference in the recorded EEG, caused by the MR scanner. A comparison between beamformer and dipole fitting approaches is made and it is shown that, due to its adaptive weighting parameters, the beamformer provides better suppression of interference when compared to the dipole fit. In addition it is shown that, in the case of the beamformer, use of a high EEG channel density improves the level of interference reduction, and the ratio of measured signal to interference can be improved by a factor of ∼1. 6 if the number of EEG electrodes is increased from 32 to 64. The interference reduction properties of source localisation are shown theoretically, in simulation, and in phantom data. Finally, in-vivo experiments conducted at 7T show that effects in the gamma band can be recorded using simultaneous EEG/fMRI. These results are achieved by application of beamformer methodology to 64 channel EEG data.

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YNIMG Journal 2008 Journal Article

Optimising experimental design for MEG beamformer imaging

  • Matthew J. Brookes
  • Jiri Vrba
  • Stephen E. Robinson
  • Claire M. Stevenson
  • Andrew M. Peters
  • Gareth R. Barnes
  • Arjan Hillebrand
  • Peter G. Morris

In recent years, the use of beamformers for source localisation has significantly improved the spatial accuracy of magnetoencephalography. In this paper, we examine techniques by which to optimise experimental design, and ensure that the application of beamformers yields accurate results. We show that variation in the experimental duration, or variation in the bandwidth of a signal of interest, can significantly affect the accuracy of a beamformer reconstruction of source power. Specifically, power will usually be underestimated if covariance windows are made too short, or bandwidths too narrow. The accuracy of spatial localisation may also be reduced. We conclude that for optimum accuracy, experimenters should aim to collect as much data as possible, and use a bandwidth spanning the entire frequency distribution of the signal of interest. This minimises distortion to reconstructed source images, time courses and power estimation. In the case where experimental duration is short, and small covariance windows are therefore used, we show that accurate power estimation can be achieved by matrix regularisation. However, large amounts of regularisation cause a loss in the spatial resolution of the MEG beamformer, hence regularisation should be used carefully, particularly if multiple sources in close proximity are expected.

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YNIMG Journal 2008 Journal Article

Simultaneous EEG source localisation and artifact rejection during concurrent fMRI by means of spatial filtering

  • Matthew J. Brookes
  • Karen J. Mullinger
  • Claire M. Stevenson
  • Peter G. Morris
  • Richard Bowtell

The simultaneous application of functional MRI and EEG represents an attractive, non-invasive technique for the combined measurement of electrical and haemodynamic activity in the human brain. Simultaneous EEG/fMRI provides a brain imaging modality with millimeter spatial accuracy, and millisecond temporal resolution. However, simultaneously acquired measurements are difficult due to the artifacts that are induced in the EEG by both the temporally varying field gradients used in MRI, and also blood flow effects. In this paper we apply an EEG beamformer spatial filter to EEG data recorded simultaneously with fMRI. We show, using this technique, that it is possible to localise accurately electrical effects in the brain, and that the localisation of driven oscillatory responses in the human visual cortex are spatially co-incident with the fMRI BOLD response. We also show how the beamformer can be used to extract timecourses of electrical activity from areas of interest in the brain. Such timecourses have millisecond time resolution. Finally, we show that in addition to source localisation, the beamformer spatial filter acts to reject interference in EEG signals, thus increasing the effective signal to noise ratio of electrical measurements. We show that the EEG-beamformer can eliminate effectively the ballistocardiogram artifact as well as residual gradient artifacts that remain in EEG data following correction using averaged artifact subtraction techniques.

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YNIMG Journal 2007 Journal Article

Beamformer reconstruction of correlated sources using a modified source model

  • Matthew J. Brookes
  • Claire M. Stevenson
  • Gareth R. Barnes
  • Arjan Hillebrand
  • Michael I.G. Simpson
  • Susan T. Francis
  • Peter G. Morris

This paper introduces a lead field formulation for use in beamformer analysis of MEG data. This ‘dual source beamformer’ is a technique to image two temporally correlated sources using beamformer methodology. We show that while the standard, single source beamformer suppresses the reconstructed power of two spatially separate but temporally correlated sources, the dual source beamformer allows for their accurate reconstruction. The technique is proven to be accurate using simulations. We also show that it can be used to image accurately the auditory steady state response, which is correlated between the left and right auditory cortices. We suggest that this technique represents a useful way of locating correlated sources, particularly if a seed location can be defined a priori for one of the two sources. Such a priori information could be based on previous studies using similar paradigms, or from other functional neuroimaging techniques.

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YNIMG Journal 2005 Journal Article

GLM-beamformer method demonstrates stationary field, alpha ERD and gamma ERS co-localisation with fMRI BOLD response in visual cortex

  • Matthew J. Brookes
  • Andrew M. Gibson
  • Stephen D. Hall
  • Paul L. Furlong
  • Gareth R. Barnes
  • Arjan Hillebrand
  • Krish D. Singh
  • Ian E. Holliday

Recently, we introduced a new ‘GLM-beamformer’ technique for MEG analysis that enables accurate localisation of both phase-locked and non-phase-locked neuromagnetic effects, and their representation as statistical parametric maps (SPMs). This provides a useful framework for comparison of the full range of MEG responses with fMRI BOLD results. This paper reports a ‘proof of principle’ study using a simple visual paradigm (static checkerboard). The five subjects each underwent both MEG and fMRI paradigms. We demonstrate, for the first time, the presence of a sustained (DC) field in the visual cortex, and its co-localisation with the visual BOLD response. The GLM-beamformer analysis method is also used to investigate the main non-phase-locked oscillatory effects: an event-related desynchronisation (ERD) in the alpha band (8–13 Hz) and an event-related synchronisation (ERS) in the gamma band (55–70 Hz). We show, using SPMs and virtual electrode traces, the spatio-temporal covariance of these effects with the visual BOLD response. Comparisons between MEG and fMRI data sets generally focus on the relationship between the BOLD response and the transient evoked response. Here, we show that the stationary field and changes in oscillatory power are also important contributors to the BOLD response, and should be included in future studies on the relationship between neuronal activation and the haemodynamic response.

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YNIMG Journal 2004 Journal Article

A general linear model for MEG beamformer imaging

  • Matthew J. Brookes
  • Andrew M. Gibson
  • Stephen D. Hall
  • Paul L. Furlong
  • Gareth R. Barnes
  • Arjan Hillebrand
  • Krish D. Singh
  • Ian E. Holliday

A new general linear model (GLM) beamformer method is described for processing magnetoencephalography (MEG) data. A standard nonlinear beamformer is used to determine the time course of neuronal activation for each point in a predefined source space. A Hilbert transform gives the envelope of oscillatory activity at each location in any chosen frequency band (not necessary in the case of sustained (DC) fields), enabling the general linear model to be applied and a volumetric T statistic image to be determined. The new method is illustrated by a two-source simulation (sustained field and 20 Hz) and is shown to provide accurate localization. The method is also shown to locate accurately the increasing and decreasing gamma activities to the temporal and frontal lobes, respectively, in the case of a scintillating scotoma. The new method brings the advantages of the general linear model to the analysis of MEG data and should prove useful for the localization of changing patterns of activity across all frequency ranges including DC (sustained fields).

Details DOI
v2026.09.13