Introduction

Magnetoencephalography (MEG) is the technique of measuring the magnetic fields generated by brain activity. In general, an important asset of MEG/EEG is the ability to record signals generated by the brain in relation to distinct states of activity, whether determined by intrinsic processes, e.g. different states of sleep and alertness, or in relation to motor acts and sensory events. Here we will focus on the core of clinical applications with respect to neurosurgical isssues. In this context three fields of application will be reviewed: (i) Presurgical functional localization of somatomotor eloquent cortex; (ii) Presurgical evaluation of epileptic patients. (iii) Functional localization of speech relevant brain areas.

The implementation of the MEG in clinical settings has had a relatively slow start, after the pioneering studies of Cohen (1968), in comparison with the amazingly rapid development of other brain imaging techniques such as Magnetic Resonance Imaging (MRI). It should be stressed that by no means are MEG and MRI really competitors. Rather, the two techniques are complementary, since MRI provides precise static information about brain anatomy, while MEG allows the study of the dynamic properties of cortical activity. MRI yields unrivalled images of brain structures at all levels, whereas MEG gives information about dynamics of the activities of large populations of neurons of the cerebral cortex. Nevertheless MEG has a more direct competitor in the more recently developed functional MRI (fMRI) technique that is based on measurements of changes of the ratio between oxy- and reduced-haemoglobin, which are related to neuronal activity. Be as it may the time resolution of MEG is unrivalled. Below we analyse more specifically the comparison between MEG and fMRI regarding the problem of localizing cortical areas bordering the central sulcus.

A basic limitation of MEG, as much as of Electroencephalography (EEG), is that the neuronal signals are recorded from the scalp and that there is no unique solution to the question of where, within the brain, are localized the sources of those signals. This means that there is no solution to what is called the inverse problem. The common approach to overcome the non-uniqueness of the inverse problem in MEG/EEG is to introduce constraints in the solutions, in order to exclude all solutions except that one that is most suitable to describe the data. Thus the functional localization of brain sources of MEG/EEG signals depends on the models used and on the corresponding assumptions, and it always has a certain degree of uncertainty. This contrasts with the accuracy of MRI brain scans. It explains partly why the development of clinical applications of MEG has been slow, since the research on how to optimise the solutions of the inverse problem has been arduous and only recently it is reaching the stage at which consensual strategies may be advanced. These inherent difficulties, along with the fact that MEG needs rather costly facilities, account for the restraint of medical specialists in promoting this new methodology and the hesitation of hospital administrators in supporting the necessary investments in material and human resources.

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