Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

[1]  M. Bourguignon,et al.  Pushing the boundaries of MEG based on optically pumped magnetometers towards early human life , 2024, bioRxiv.

[2]  N. Holmes,et al.  Optimising the sensitivity of optically-pumped magnetometer magnetoencephalography to gamma band electrophysiological activity , 2024, Imaging Neuroscience.

[3]  Maciej J. Szul,et al.  Bursting with Potential: How Sensorimotor Beta Bursts Develop from Infancy to Adulthood , 2023, bioRxiv.

[4]  P. J. Hobson,et al.  Enabling ambulatory movement in wearable magnetoencephalography with matrix coil active magnetic shielding , 2023, NeuroImage.

[5]  R. Bowtell,et al.  Measurement of Frontal Midline Theta Oscillations using OPM-MEG , 2023, NeuroImage.

[6]  Jonathan D. Cohen,et al.  Test-Retest Reliability of the Human Connectome: An OPM-MEG study , 2022, bioRxiv.

[7]  R. Bowtell,et al.  Magnetoencephalography with optically pumped magnetometers (OPM-MEG): the next generation of functional neuroimaging , 2022, Trends in Neurosciences.

[8]  M. Brookes,et al.  On-Scalp Optically Pumped Magnetometers versus Cryogenic Magnetoencephalography for Diagnostic Evaluation of Epilepsy in School-aged Children. , 2022, Radiology.

[9]  I. Scheffer,et al.  International League Against Epilepsy classification and definition of epilepsy syndromes with onset in childhood: Position paper by the ILAE Task Force on Nosology and Definitions , 2022, Epilepsia.

[10]  R. Bowtell,et al.  Triaxial detection of the neuromagnetic field using optically-pumped magnetometry: feasibility and application in children , 2022, NeuroImage.

[11]  P. Ferrari,et al.  Detection and analysis of cortical beta bursts in developmental EEG Data , 2022, Developmental Cognitive Neuroscience.

[12]  G. Barnes,et al.  Spherical harmonic based noise rejection and neuronal sampling with multi-axis OPMs , 2021, NeuroImage.

[13]  J. Stephen,et al.  Cross-Axis projection error in optically pumped magnetometers and its implication for magnetoencephalography systems , 2021, NeuroImage.

[14]  Zelekha A. Seedat,et al.  Mild traumatic brain injury impairs the coordination of intrinsic and motor-related neural dynamics , 2021, NeuroImage: Clinical.

[15]  Brandon J. Lew,et al.  Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescence , 2021, NeuroImage.

[16]  E. Maguire,et al.  Modelling optically pumped magnetometer interference in MEG as a spatially homogeneous magnetic field , 2021, NeuroImage.

[17]  H. Rossiter,et al.  Understanding the Role of Sensorimotor Beta Oscillations , 2021, Frontiers in Systems Neuroscience.

[18]  Matthew J. Brookes,et al.  Theoretical advantages of a triaxial optically pumped magnetometer magnetoencephalography system , 2021, NeuroImage.

[19]  Zelekha A. Seedat,et al.  Motor-related oscillatory activity in schizophrenia according to phase of illness and clinical symptom severity , 2020, NeuroImage: Clinical.

[20]  T. Popov,et al.  Decomposing the role of alpha oscillations during brain maturation , 2020, bioRxiv.

[21]  M. Molteni,et al.  Altered neural oscillations and connectivity in the beta band underlie detail-oriented visual processing in autism , 2020, NeuroImage: Clinical.

[22]  Matthew J. Brookes,et al.  Measuring functional connectivity with wearable MEG , 2020, NeuroImage.

[23]  C. Elger,et al.  Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study , 2020, The Lancet Neurology.

[24]  Matthew J. Brookes,et al.  Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system , 2020, NeuroImage.

[25]  Mark W. Woolrich,et al.  Post-stimulus beta responses are modulated by task duration , 2020, NeuroImage.

[26]  Mark W. Woolrich,et al.  The role of transient spectral ‘bursts’ in functional connectivity: A magnetoencephalography study , 2020, NeuroImage.

[27]  G. Barnes,et al.  Human motor cortical beta bursts relate to movement planning and response errors , 2019, PLoS biology.

[28]  Mark W. Woolrich,et al.  A tool for functional brain imaging with lifespan compliance , 2019, Nature Communications.

[29]  Vince D. Calhoun,et al.  The developmental trajectory of sensorimotor cortical oscillations , 2019, NeuroImage.

[30]  Margot J. Taylor,et al.  Spatial and spectral trajectories in typical neurodevelopment from childhood to middle age , 2019, Network Neuroscience.

[31]  Lauri Parkkonen,et al.  Optical Co-registration of MRI and On-scalp MEG , 2018, Scientific Reports.

[32]  Matthew J. Brookes,et al.  Mapping the topological organisation of beta oscillations in motor cortex using MEG , 2018, NeuroImage.

[33]  Matthew J. Brookes,et al.  A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography , 2018, NeuroImage.

[34]  A. Nobre,et al.  Neural Oscillations: Sustained Rhythms or Transient Burst-Events? , 2018, Trends in Neurosciences.

[35]  Mark W. Woolrich,et al.  Altered temporal stability in dynamic neural networks underlies connectivity changes in neurodevelopment , 2018, NeuroImage.

[36]  Niall Holmes,et al.  Moving magnetoencephalography towards real-world applications with a wearable system , 2018, Nature.

[37]  C. Moore,et al.  The rate of transient beta frequency events predicts behavior across tasks and species , 2017, eLife.

[38]  J. Stephen,et al.  A 20-channel magnetoencephalography system based on optically pumped magnetometers , 2017, Physics in medicine and biology.

[39]  Matthew J. Brookes,et al.  Abnormal task driven neural oscillations in multiple sclerosis: A visuomotor MEG study , 2017, Human brain mapping.

[40]  S. Jones When brain rhythms aren't ‘rhythmic’: implication for their mechanisms and meaning , 2016, Current Opinion in Neurobiology.

[41]  C. Moore,et al.  Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice , 2016, Proceedings of the National Academy of Sciences.

[42]  Tony W. Wilson,et al.  Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task , 2016, Brain Topography.

[43]  Eleanor L. Barratt,et al.  Modulation of post‐movement beta rebound by contraction force and rate of force development , 2016, Human brain mapping.

[44]  C. Stam,et al.  Direction of information flow in large-scale resting-state networks is frequency-dependent , 2016, Proceedings of the National Academy of Sciences.

[45]  Mark W. Woolrich,et al.  Spectrally resolved fast transient brain states in electrophysiological data , 2016, NeuroImage.

[46]  Benjamin A. E. Hunt,et al.  Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods , 2015, Physics in medicine and biology.

[47]  Claudia D. Tesche,et al.  Aberrant development of post-movement beta rebound in adolescents and young adults with fetal alcohol spectrum disorders , 2015, NeuroImage: Clinical.

[48]  Karl J. Friston,et al.  Attentional Modulation of Alpha/Beta and Gamma Oscillations Reflect Functionally Distinct Processes , 2014, The Journal of Neuroscience.

[49]  Margot J. Taylor,et al.  Oscillations, networks, and their development: MEG connectivity changes with age , 2014, Human brain mapping.

[50]  Jens Haueisen,et al.  Comparison of three-shell and simplified volume conductor models in magnetoencephalography , 2014, NeuroImage.

[51]  Stephen M Smith,et al.  Fast transient networks in spontaneous human brain activity , 2014, eLife.

[52]  M. Burghoff,et al.  A magnetically shielded room with ultra low residual field and gradient. , 2014, The Review of scientific instruments.

[53]  A. Riehle,et al.  The ups and downs of beta oscillations in sensorimotor cortex , 2013, Experimental Neurology.

[54]  D. Cheyne MEG studies of sensorimotor rhythms: A review , 2013, Experimental Neurology.

[55]  Mark W. Woolrich,et al.  Measuring functional connectivity in MEG: A multivariate approach insensitive to linear source leakage , 2012, NeuroImage.

[56]  M. Corbetta,et al.  Large-scale cortical correlation structure of spontaneous oscillatory activity , 2012, Nature Neuroscience.

[57]  Darren Price,et al.  Investigating the electrophysiological basis of resting state networks using magnetoencephalography , 2011, Proceedings of the National Academy of Sciences.

[58]  Matthew J. Brookes,et al.  Measuring functional connectivity using MEG: Methodology and comparison with fcMRI , 2011, NeuroImage.

[59]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[60]  William Gaetz,et al.  Neuromagnetic imaging of movement-related cortical oscillations in children and adults: Age predicts post-movement beta rebound , 2010, NeuroImage.

[61]  E. Maris,et al.  Tactile expectation modulates pre-stimulus β-band oscillations in human sensorimotor cortex , 2010, NeuroImage.

[62]  Alan C. Evans,et al.  Age- and Gender-Related Differences in the Cortical Anatomical Network , 2009, The Journal of Neuroscience.

[63]  Moo K Chung,et al.  Estimating head circumference from pediatric imaging studies an improved method. , 2007, Academic radiology.

[64]  E. Whitham,et al.  Scalp electrical recording during paralysis: Quantitative evidence that EEG frequencies above 20Hz are contaminated by EMG , 2007, Clinical Neurophysiology.

[65]  E. Gordon,et al.  Brain maturation in adolescence: Concurrent changes in neuroanatomy and neurophysiology , 2007, Human brain mapping.

[66]  William Gaetz,et al.  Localization of sensorimotor cortical rhythms induced by tactile stimulation using spatially filtered MEG , 2006, NeuroImage.

[67]  R. Oostenveld,et al.  Tactile Spatial Attention Enhances Gamma-Band Activity in Somatosensory Cortex and Reduces Low-Frequency Activity in Parieto-Occipital Areas , 2006, The Journal of Neuroscience.

[68]  G. Nolte The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors. , 2003, Physics in medicine and biology.

[69]  F. Varela,et al.  Neuromagnetic imaging of cortical oscillations accompanying tactile stimulation. , 2003, Brain research. Cognitive brain research.

[70]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[71]  M. Romalis,et al.  High-sensitivity atomic magnetometer unaffected by spin-exchange relaxation. , 2002, Physical review letters.

[72]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[73]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[74]  Robert J Barry,et al.  Age and sex effects in the EEG: development of the normal child , 2001, Clinical Neurophysiology.

[75]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[76]  W. Drongelen,et al.  Localization of brain electrical activity via linearly constrained minimum variance spatial filtering , 1997, IEEE Transactions on Biomedical Engineering.

[77]  V. Jousmäki,et al.  Modulation of Human Cortical Rolandic Rhythms during Natural Sensorimotor Tasks , 1997, NeuroImage.

[78]  B. Chance,et al.  Cognition-activated low-frequency modulation of light absorption in human brain. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[79]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .

[80]  D. Tank,et al.  Brain magnetic resonance imaging with contrast dependent on blood oxygenation. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[81]  H. Berger Über das Elektrenkephalogramm des Menschen , 1929, Archiv für Psychiatrie und Nervenkrankheiten.

[82]  OUP accepted manuscript , 2022, Cerebral Cortex.

[83]  P. Brown,et al.  The functional role of beta oscillations in Parkinson's disease. , 2014, Parkinsonism & related disorders.

[84]  Paolo Cignoni,et al.  MeshLab: an Open-Source Mesh Processing Tool , 2008, Eurographics Italian Chapter Conference.