From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery

Abstract

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.

Neonatal brain resting-state functional connectivity imaging modalities

“…5 MEG data acquisition and processing: (1) MEG time series are recorded by sensors [ 111 ] and after a (2) filtering procedure, (3) transformed to source-space time series by a beamformer algorithm [ 112 ]. (4) The resulting time series is then filtered in the alpha-band (8–12 Hz) and its phase and amplitude is extracted via Hilbert-envelope computation, resulting in 90 alpha-power time series [ 113 ]. (5) The model is constructed by taking the same AAL brain parcellation used for source-reconstruction of the MEG signal, and putting a model node in the centre of each brain area and construction an adjacency matrix for the FC.…”

Effect of stress on human biology: Epigenetics, adaptation, inheritance, and social significance

“…Pang and Snead () have analyzed brain connectivity changes in response to various neurological insults. MEG is based on the principle that that an electrical current (ion flow) generates a magnetic field that can be localized and quantified in short time (millisecond) frames.…”

Removal of Interictal MEG-Derived Network Hubs Is Associated With Postoperative Seizure Freedom

“…Functional brain networks derived from magnetoencephalography (MEG) data can be inferred by computing the pairwise similarity of brain regions. Several studies have shown increased MEG functional connectivity in patients with epilepsy compared to controls, even in inter-ictal periods (2)(3)(4)(5)(6). In two separate studies, Jin et al (7) showed altered MEG network "hubs" -those regions with high network connectivity-in temporal areas in patients with hippocampal sclerosis, and increased network efficiency in patients with focal cortical dysplasia (8).…”