Understanding is important to development of more complex procedure and ensuring efficiency in any area of operations. One of the tools used to develop a proper understanding and therefore diagnosis of a situation is the image of the situation. Sciences, technology, medicine and engineering all need images to be able to develop structures and operate efficiently. In neuroscience, the development of an image of inner brain tissues is important to developing an understanding of a situation as it really is and therefore coming up with proper diagnostic and management approaches that will ensure the situation is addressed as it should. Life being what it is there are a number of choices that can be made in the approach that will be used for imaging. Each of these approaches has significant advantage and disadvantages and an understanding of the differences is important in making a decision on which one is best applicable depending on the parameters that define a condition (Kretschmann,& Weinrich, 2003). MEG is one of the most common imaging techniques and the development of an understanding of the differences that it exhibits relative to others is important to its use.
Magnetoencephalography (MEG) implements a system where magnetic fields are produced by the aid of electric activity in the brain through use of highly sensitive devices. MEG which is common in research situation and clinical settings is one of the most commonly used approaches to neuroimaging. Surgeons have especially found MEG important in localising pathologies and researchers have used it in determining the various functions of parts of the brain, neurofeedback and in many other activities relating to the central nervous system. Many of the advantages of MEG are a result of its nature and principles that it applies in operations. Compared to functional imaging techniques like EEG, IMG has a number of key features that makes it more desirable; these are often considered in determining what neuroimaging technique will be applicable in either research or clinical situations (Holodny, 2008).
MEG implements a system where the functions of the brain are directly measured. The main reason as to why imaging is necessary is to ensure a proper understanding of the state that the brain is and getting direct measures of the function is important and reduces the chance of error. Functional approaches like fMRI and SPECT use what can be best describes as functional measures to determine the state that the brain is in. Functional approaches which use variables that depict brain metabolisms to determine the functioning of the brain can be quite misleading for there are a number of variables that will have to be considered under such approaches. Moreover, errors can occur in translation of the metabolism variables to those that depict the state of the brain (Hillary,& DeLuca, 2007).
When developing an image the clarity of the image that will be developed is important. In neuroscience and many other areas where imaging has to be done in an environment that is highly controlled the ability to develop clear temporal images is important (Anschel, Mazumdar,& Romanelli, 2007). This is due to the nature of the brain which requires low exposure to external activities and thus the idea of testing or imaging is in fact risky to the brain. MEG is considered to be an approach that has one of the highest temporal resolution. Events that have a time scale of milliseconds can be resolved accurately. Functional approaches like SPECT have much longer time scales and therefore the resolution of activities and development of a clear picture of the state that the brain is in is not as easy in such methods. It is worth noting that the brain being the centre of the nervous system is important and has a number of activities or events that occur within any given instant. The high resolution provided by MEG comes in handy and is important in capturing such events is therefore a better diagnostic tool in assessing the functionality of the brain inn consideration of the nature of the brain. In addition to the excellent temporal resolution, MEG has high levels of spatial resolution in that sources or objects can be located with millimetre precision. The brain is a small organ and it is one of the busiest in the human person. Information about the brain should be clear and precise; the high levels of precision that MEG has comes in handy and is important in coming up with clear accurate information on the performance of the brain.
Neuroimaging is considered one of the most frightening event by people outside the medical fraternity. One reason as to why this is so is the invasive techniques used by functional imaging approaches. Isotopes and exposure to ray and magnetic field are used in other functional approaches and this is not only scary but also increases the health risks associated with neuroimaging and reduces the frequency of imaging allowed. MEG is unlike these functional techniques in this aspect in that EMG employs a system that is non-invasive. These property gives it an edge over other sin that it is even possible for children and infants to be studied repeatedly.
Experts in neuroimaging and science are of the view that the reason as to why MEG has been widely adopted is its ability to be used alongside other approaches as it adds on to the picture to develop a clear understanding of the brain (Martin,& Caramazza, 2003). While no one can dispute this fact practical application of MEG is quite easy as compared to functional approaches which could have also played a role in its development. Technology and the employment of aid in imaging are aimed at easing understanding of the brain functionalities (Gazzaniga, & Bizzi, 2004). The ease that comes with the use of MEG is important and could be an avenue through which future generations use to reduce the complexity that neuroscience as a discipline has traditionally been linked with.
The approach implemented by MEG makes it possible for its application in a variety of brain imaging processes. Sensory, language and memory cortex can all be imaged by use of MEG. An approach that is adaptable to multiple conditions is far much better that the ones that display low level of adaptability. This ability reduces the need to conduct multiple tests on individuals and therefore reduces the risk in imaging and costs in terms of finances and time associated with repainting imaging.
The modern society is highly health conscious and the risks that come with functional approaches and the invasive mechanism that they employ make them undesirable. Moreover, there is increase in the need for multiple brain testing due to an unexplained increase in the number of mental and neurological cases. Cancer is fast becoming a threat and one would rather implement a system that does not pose any risk of cancer if there is an alternative. Put plainly, MEG would be the method of choice against any functional approach in consideration of the mechanism employed and risk posed. The fact that MEG affords high levels of clarity without being invasive gives it an advantage over the most commonly employed functional approach, EMG which has the con of being invasive. It is worth noting that the levels of clarity that the two approaches attain are comparable.
MEG despite all the pros associated with its use has a number disadvantages that may make its use undesirable. Just like the advantages, the cons are resultant from the nature of mechanisms that MEG employs and are therefore internal to MEG as an approach to neuroimaging. These cons may affect the effectiveness of the approach and even increase the associated costs which may make it undesirable.
A key drawback in use of MEG stems from the fact that the signals that depict the state of the brain are small and are in a magnitude order that is smaller than typical signal in a clinical environment. It is highly probable that the normal clinic environment may obscure the signals thus most MEG systems employ a shielding to deal with the interference. This is an additional cost that comes on top of installation costs. The cost of shielding and installation makes MEG one of the costly approach to imaging. Anyone who has ever been involved with a medical case that involved the brain will always remember the ordeal due to its nature and cost. The cost of neurological care is high and the employment of costly approaches definitely has a bearing on this cost. In addition, the fact that there is risk of interference by outside forces calls for proper assessment of the environment and continued assessment to ensure accuracy of findings by monitoring interference. Such costs are undesirable in the modern context of healthcare where cost of provision is high due to the high costs of operations.
The brain being the centre of the nervous system engages in nearly all kinds of activities. Being a living organ, the brain metabolism is a variable that must be considered in any approach that seeks to determine the state that a brain is in. No full analysis or imaging of the brain can be done without considering its metabolic activity for it has a bearing on the state that brain is in. MEG employs a system that ensures direct measures of the brain activity and disregards any metabolic activity. This reduces the robustness of information that can be obtained by employment of this approach. Diagnosis of any clinical case and ones that involve the physiology of organs often take on an approach where direct measures and rate of metabolism are all determined and analysed (Barkovich, 2005). This is not the case in the implementation of MEG.
MEG is more technical than functional approaches, there is therefore need for neuroscientists and technicians to master the internal workings of the machine that provide them with MEG functionalities. In addition to the cost that maintenance of the system has, it puts pressure on the technicians to learn more on the system and this could temporarily infringe on their performance as professionals. This also puts the assessment and imaging at risk of wrong results due to errors arising from hardware or technological failure.
In its common application, MEG is used in association with other functional approaches. This is because of its failure to put into consideration the metabolic aspect on physiological assessment. Direct readings are a result of underlying metabolic activities and an understanding of both leads to development of robust analysis. When implemented with other functional approaches, MEG is employed as a secondary approach that brushes on findings from the functional approaches. Despite all its advantages, MEG cannot be used as a standalone approach to neuroimaging where a complete analysis of a condition is required. This is a disadvantage that reduces its effectiveness in application to medical conditions where there is no need for direct readings.
MEG has clear advantages and disadvantages. Its advantages provide it with high levels of adaptability, accuracy, precision and reduction of risk. All these are important if it is considered that any blunder in analysing the brain could lead to loss of life. The sensitiveness of the brain calls for approaches that are less risky and accurate. On the contrary, the disadvantages which include high cost of implementation; the fact that it cannot be implemented alone and its disregarding brain metabolism have a direct bearing on its advantages. The advantages are realisable but they have to be achieved at a cost which may be high for the ordinary person though a full analysis must often involve functional approaches. Despite this clear reduction in the impact of the advantages, the inclusion of functional approaches results in a robust analysis and a more serious approach to provision of healthcare services which is worth far much more than the cost involved.