Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG

Background: The present study aims at evaluating and comparing electrical and magnetic distributed source imaging methods applied to high‐density Electroencephalography (hdEEG) and Magnetoencephalography (MEG) data. We used resolution matrices to characterize spatial resolution properties of Minimum Norm Estimate (MNE), dynamic Statistical Parametric Mapping (dSPM), standardized Low‐Resolution Electromagnetic Tomography (sLORETA) and coherent Maximum Entropy on the Mean (cMEM, an entropy‐based technique). The resolution matrix provides information of the Point Spread Functions (PSF) and of the Crosstalk functions (CT), this latter being also called source leakage, as it reflects the influence of a source on its neighbors. Methods: The spatial resolution of the inverse operators was first evaluated theoretically and then with real data acquired using electrical median nerve stimulation on five healthy participants. We evaluated the Dipole Localization Error (DLE) and the Spatial Dispersion (SD) of each PSF and CT map. Results: cMEM showed the smallest spatial spread (SD) for both PSF and CT maps, whereas localization errors (DLE) were similar for all methods. Whereas cMEM SD values were lower in MEG compared to hdEEG, the other methods slightly favored hdEEG over MEG. In real data, cMEM provided similar localization error and significantly less spatial spread than other methods for both MEG and hdEEG. Whereas both MEG and hdEEG provided very accurate localizations, all the source imaging methods actually performed better in MEG compared to hdEEG according to all evaluation metrics, probably due to the higher signal‐to‐noise ratio of the data in MEG. Conclusion: Our overall results show that all investigated methods provide similar localization errors, suggesting very accurate localization for both MEG and hdEEG when similar number of sensors are considered for both modalities. Intrinsic properties of source imaging methods as well as their behavior for well‐controlled tasks, suggest an overall better performance of cMEM in regards to spatial resolution and spatial leakage for both hdEEG and MEG. This indicates that cMEM would be a good candidate for studying source localization of focal and extended generators as well as functional connectivity studies. HighlightsEvaluation of intrinsic spatial resolution of EEG and MEG source imaging methods.Comparison of a novel entropy‐based technique (cMEM) to well‐established methods.cMEM showed similar localization error, lowest spatial spread and reduced crosstalk.MEG and high‐density EEG (256 sensors) presented a similar level of spatial accuracy.Theoretical results confirmed with real data of somatosensory evoked potentials.

[1]  Jeffery A Hall,et al.  Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy , 2016, Human brain mapping.

[2]  Olivier Faugeras,et al.  Generalized Head Models for MEG / EEG : BEM beyond Nested Volumes , 2022 .

[3]  Jean Gotman,et al.  Evaluation of EEG localization methods using realistic simulations of interictal spikes , 2006, NeuroImage.

[4]  M. S. Hämäläinen,et al.  Quantification of the benefit from integrating MEG and EEG data in minimum ℓ2-norm estimation , 2008, NeuroImage.

[5]  R. Ilmoniemi,et al.  Interpreting magnetic fields of the brain: minimum norm estimates , 2006, Medical and Biological Engineering and Computing.

[6]  Riitta Salmelin,et al.  Electromagnetic brain imaging , 2009, Human brain mapping.

[7]  John W Belliveau,et al.  Monte Carlo simulation studies of EEG and MEG localization accuracy , 2002, Human brain mapping.

[8]  Leeanne M. Carey,et al.  Fish Oil Diet Associated with Acute Reperfusion Related Hemorrhage, and with Reduced Stroke-Related Sickness Behaviors and Motor Impairment , 2014, Front. Neurol..

[9]  C. C. Wood,et al.  Localization of human sensorimotor cortex during surgery by cortical surface recording of somatosensory evoked potentials. , 1988, Journal of neurosurgery.

[10]  O. Faugeras,et al.  Generalized head models for MEG/EEG: boundary element method beyond nested volumes , 2006, Physics in medicine and biology.

[11]  Joseph R. Madsen,et al.  Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy , 2016, Journal of visualized experiments : JoVE.

[12]  Anders M. Dale,et al.  Dynamic Statistical Parametric Neurotechnique Mapping: Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity , 2000 .

[13]  C. Michel,et al.  Linear inverse solutions with optimal resolution kernels applied to electromagnetic tomography , 1997, Human brain mapping.

[14]  Bart Vanrumste,et al.  EEG/MEG Source Imaging: Methods, Challenges, and Open Issues , 2009, Comput. Intell. Neurosci..

[15]  Thomas R. Knösche,et al.  A guideline for head volume conductor modeling in EEG and MEG , 2014, NeuroImage.

[16]  B. He,et al.  Effect of EEG electrode number on epileptic source localization in pediatric patients , 2015, Clinical Neurophysiology.

[17]  Pierre Jolicoeur,et al.  A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings , 2014, Front. Neurosci..

[18]  Richard M. Leahy,et al.  Brainstorm: A User-Friendly Application for MEG/EEG Analysis , 2011, Comput. Intell. Neurosci..

[19]  K Zilles,et al.  Functional lateralization of face, hand, and trunk representation in anatomically defined human somatosensory areas. , 2008, Cerebral cortex.

[20]  Mahmoud Hassan,et al.  Identification of Interictal Epileptic Networks from Dense-EEG , 2016, Brain Topography.

[21]  Henson Richard.  Comparison of noise-normalized minimum norm estimates using multiple resolution metrics , 2010 .

[22]  H. Alkadhi,et al.  Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. , 1997, Brain : a journal of neurology.

[23]  Rolando Grave de Peralta Menendez,et al.  The Neuroelectromagnetic Inverse Problem and the Zero Dipole Localization Error , 2009, Comput. Intell. Neurosci..

[24]  R. Ilmoniemi,et al.  Signal-space projection method for separating MEG or EEG into components , 1997, Medical and Biological Engineering and Computing.

[25]  O Levrier,et al.  Location of hand function in the sensorimotor cortex: MR and functional correlation. , 1994, AJNR. American journal of neuroradiology.

[26]  Théodore Papadopoulo,et al.  OpenMEEG: opensource software for quasistatic bioelectromagnetics , 2010, Biomedical engineering online.

[27]  Anthony A. Grace.  Gilles de la Tourette’s and the Disruption of Interneuron-Mediated Synchrony , 2016, Brain Topography.

[28]  C. Michel,et al.  The Role of Functional Neuroimaging in Pre-Surgical Epilepsy Evaluation , 2014, Front. Neurol..

[29]  Gerald S. Russell,et al.  Geodesic photogrammetry for localizing sensor positions in dense-array EEG , 2005, Clinical Neurophysiology.

[30]  Andreas Galka,et al.  Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model , 2014, PloS one.

[31]  S. Morrison,et al.  Autonomic regulation of brown adipose tissue thermogenesis in health and disease: potential clinical applications for altering BAT thermogenesis , 2014, Front. Neurosci..

[32]  A. Dale,et al.  Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach , 1993, Journal of Cognitive Neuroscience.

[33]  Jean Gotman,et al.  Detection and Magnetic Source Imaging of Fast Oscillations (40–160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients , 2016, Brain Topography.

[34]  Magnetic source imaging , 2018, Zeitschrift für Epileptologie.

[35]  Christophe Grova,et al.  MEG Source Localization of Spatially Extended Generators of Epileptic Activity: Comparing Entropic and Hierarchical Bayesian Approaches , 2013, PloS one.

[36]  Per Christian Hansen,et al.  Analysis of Discrete Ill-Posed Problems by Means of the L-Curve , 1992, SIAM Rev..

[37]  Giovanni Pellegrino,et al.  Source localization of the seizure onset zone from ictal EEG/MEG data , 2016, Human brain mapping.

[38]  Karl J. Friston,et al.  Multiple sparse priors for the M/EEG inverse problem , 2008, NeuroImage.

[39]  E. Halgren,et al.  Dynamic Statistical Parametric Mapping Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity , 2000, Neuron.

[40]  Olaf Hauk,et al.  Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics , 2011, NeuroImage.

[41]  T Allison,et al.  Localization of functional regions of human mesial cortex by somatosensory evoked potential recording and by cortical stimulation. , 1996, Electroencephalography and clinical neurophysiology.

[42]  Younes Zerouali,et al.  MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy , 2015, Brain Topography.

[43]  Mahmoud Hassan,et al.  EEG Source Connectivity Analysis: From Dense Array Recordings to Brain Networks , 2014, PloS one.

[44]  J. Schoffelen,et al.  Source connectivity analysis with MEG and EEG , 2009, Human brain mapping.

[45]  Philippe Pouliot,et al.  Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity , 2016, Human brain mapping.

[46]  Seppo P. Ahlfors,et al.  Sensitivity of MEG and EEG to Source Orientation , 2010, Brain Topography.

[47]  David C. Alsop,et al.  The Sensory Somatotopic Map of the Human Hand Demonstrated at 4 Tesla , 1999, NeuroImage.

[48]  François Dubeau,et al.  Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy , 2015, Brain Topography.

[49]  Karl J. Friston,et al.  Selecting forward models for MEG source-reconstruction using model-evidence , 2009, NeuroImage.

[50]  Isabelle Peretz,et al.  Brain activity is related to individual differences in the number of items stored in auditory short-term memory for pitch: Evidence from magnetoencephalography , 2014, NeuroImage.

[51]  John S Ebersole,et al.  Combining MEG and EEG Source Modeling in Epilepsy Evaluations , 2010, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[52]  F Wendling,et al.  Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data , 2016, NeuroImage.

[53]  Isabelle Bloch,et al.  From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations , 1995, Journal of Mathematical Imaging and Vision.

[54]  Klaus Scheffler,et al.  Differences Between MEG and High-Density EEG Source Localizations Using a Distributed Source Model in Comparison to fMRI , 2014, Brain Topography.

[55]  Cécile Amblard,et al.  Biomagnetic source detection by maximum entropy and graphical models , 2004, IEEE Transactions on Biomedical Engineering.

[56]  Allen D. Malony,et al.  Localizing Movement-Related Primary Sensorimotor Cortices with Multi-Band EEG Frequency Changes and Functional MRI , 2014, PloS one.

[57]  Matti Stenroos,et al.  A framework for the design of flexible cross‐talk functions for spatial filtering of EEG/MEG data: DeFleCT , 2014, Human brain mapping.

[58]  I F Gorodnitsky,et al.  Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.

[59]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[60]  F. Mauguière,et al.  Short and middle-latency Median Nerve (MN) SEPs recorded by depth electrodes in human pre-SMA and SMA-proper , 2005, Clinical Neurophysiology.

[61]  E. Halgren,et al.  Cancellation of EEG and MEG signals generated by extended and distributed sources , 2009, Human brain mapping.

[62]  J Régis,et al.  Short-latency components of evoked potentials to median nerve stimulation recorded by intracerebral electrodes in the human pre- and postcentral areas , 2004, Clinical Neurophysiology.

[63]  R. Leahy,et al.  Mapping human brain function with MEG and EEG: methods and validation , 2004, NeuroImage.

[64]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.

[65]  Christophe Grova,et al.  Wavelet-Based Localization of Oscillatory Sources From Magnetoencephalography Data , 2014, IEEE Transactions on Biomedical Engineering.