Evaluating the Advantages and Limitations of EEG - Case Study Example

Evaluating the Advantages and Limitations of EEG Total Number of Words 501 Introduction Electroencephalogram (EEG) is commonly used in studying how the brain circuit works. By firing between the neurons, the main purpose of using the EEG technique is to “record continuous electrical brain activity” or brainwaves (Stolerman, 2010, p. 462). Since the electrodes is capable of recording fast or slow oscillatory brain movements, the use of EEG enables neurologists to observe the actual movements of the brain neurons especially those with a high temporal resolution. Despite the benefits of using EEG, it will remain a fact that there are some advantages and limitations when it comes to the use of this particular brain monitoring device. After discussing the advantages and limitations of EEG devices, a list of recommendations will be presented at the end of this study. Advantages of EEG Devices When studying the main characteristics of chronic pain and the effects of pharmacological drug intervention, an accurate frequency measurement is very important. As compared to other monitoring devices, one of the main advantages of using the EEG devices is its high temporal (time) resolution which enables the EEG technicians to capture sample rates of a little more than 20 kHz within sub-millisecond (Agrawal and Mane, 2009, p. 19-12). Given that EEG is characterized by having a high temporal resolution, this particular brain monitoring device can detect changes in the brain’s electrical activity on a millisecond-level (Agrawal and Mane, 2009, p. 19-2). Likewise, it is possible for the end-users to analyse the brain centres that are activated in parallel and sequentially within the 1st 500 ms after the onset of the stimulus (i.e. chronic pain, reading activities, etc.) (Staahl et al., 2009). Because of the high temporal resolution, EEG can be used each time the doctors need to answer questions pertaining to the time differences in the patients’ cognitive brain activation. Brain recordings take a longer time interval in order to detect sings of abnormalities. Since EEG tests are non-invasive (Agrawal and Mane, 2009, p. 19-2), the use of this particular monitoring device is said to be save to use over a long period of time. Furthermore, most of the EEG machines that are available in the market are designed with amplifiers which make it possible to convert brain signals or brainwaves as images on a large computer monitor that can either be printed out on a piece of paper or saved on a computer’s hard drive (Agrawal and Mane, 2009, p. 19-2). These options make it possible for the EEG technicians to clearly monitor the brain activity of the patients. According to Agrawal and Mane (2009, p. 19-12), the EEG brain monitoring device is capable of showing abnormal brain signals from a normal brain structure. For this reason, EEG is considered one of the most important test when diagnosing and treating patients with epilepsy. By simply recording the electrical brain activity of the patient during seizures and between seizures, the doctors can predict the type of epilepsy the patient has aside from detecting specific part of the brain that is responsible in causing the seizure. Eventually, based on the EEG chart, the doctor can either prescribed the best and most appropriate pharmacological drug to treat the patient’s seizure or suggest that the patient should undergo a neurosurgical treatment procedure. In general, EEG is commonly known as a useful tool when diagnosing patients with epilepsy and syncope (fainting issues), sleep disorders, coma and brain death, and/or seizure disorders (Agrawal and Mane, 2009, p. 19-11). Likewise, this particular EEG device can also be used in the study of psychopharmacology. According to Galderisi and Sannita (2006), “neuroactive drugs affect the brain function (i.e. cognition, sensory information processing, and behaviour)”. Since neuroactive drugs can alter the normal functioning of the brain, Stolerman (2010, p. 463) explained that a pharmaco-EEG can be used each time there is a need to examine the effect of a specific drug on the electrical brain activity of the patients. Psychotropic drugs a.k.a. psychoactive drugs can affect the CNS which causes a sudden change in the patients’ cognitive, behaviour or sensory perception. In most cases, psychotropic drugs are classified into four major groups known as the antipsychotics, anti-depressants, hallucinogens, and stimulants. Drug toxicity can lead to liver failure and other more serious health complications (Begriche et al., 2011). In case the pharmaceutical companies are interested in knowing the impact of psychotropic drug toxicity on the cognitive, behavioural, or senses of the patients, a pharmaco-EEG can be used to monitor and predict the clinical responses of the patient to a given drug (Mucci et al., 2006). For example, after conducting a study which aims to identify the EEG biomarkers for analgesic effects of pregabalin on patients with chronic visceral pain, Graversen et al. (2012) found out that a significant change in the spectral indices was noted due to the slowing of the brain oscillations. Based on this study, pharmaceutical companies, doctors, and pharmacists would know that the analgesic effect of pregabalin is to slow-down the brain oscillations. Therefore, through the use of a pharmaco-EEG device, pharmaceutical companies can obtain evidence-based research findings. Limitations of EEG Devices Despite the advantages of EEG devices in monitoring electrical brain activity, there are also some limitations with regards to the use of this particular monitoring device. As compared to a functional magnetic resonance imaging (fMRI), the spatial resolution of EEG is known to be poor in terms of accurately locating the activated brain sources (Staahl et al., 2009; Liu and He, 2008). In line with this, Agrawal and Mane (2009, p. 19-12) explained that the scalp electrodes of EEG brain monitoring devices are “not sensitive enough to pick out individual action potentials”. In fact, EEG signals can only pick-up small surface electrodes of 50 micro volts peak-to-peak as compared to other monitoring devices such as the ECG (Agrawal and Mane, 2009, p. 19-2). Since EEG technicians or the doctors will not be able to accurately tell if the electrical brain activity results are caused by the release of excitatory, inhibitory, or modulatory neurotransmitters, there is a risk wherein EEG devices that show abnormal signs of high voltage brain activity can make the doctors perform wrong diagnosis on the patients. According to Ullsperger and Debener (2010, p. 25), a high resolution specificity is very important when it comes to visualizing the brain structures like layers, columns, or patches whereas a low resolution specificity increases the functional signal which could increase the accuracy of the mapping. In line with this, Agrawal and Mane (2009, p. 19-12) pointed out that EEG brain monitoring devices have “limited anatomical specificity” as compared to functional magnetic resonance imaging (fMRI). It means that EEG devices are not capable of producing 2D or 3D brain anatomical images which are useful in studying the brain functioning of the patients. For this reason, the use of EEG brain monitoring devices is not effective in terms of locating specific parts of the brain that causes seizures or chronic pain. For example, even though it is possible to use pharmco-EEG devices in tracing the negative effects of antipsychotic drug toxicity to the patients, Mucci et al. (2006) revealed that the use of EEG in studying recreational drugs was never been successful in terms of identifying reliable indices of CNS toxicity. Since EEG has a very weak spatial resolution, the use of this particular brain monitoring device is not effective in terms of accurately locating the activated brain sources (Staahl et al., 2009; Liu and He, 2008). Therefore, EEG failed to identify accurate indices of CNS toxicity. Conclusion and Recommendations EEG is a safe and effective way of recording the long-term continuous electrical brain activity or brainwaves of the patients. EEG is characterized by having a high temporal and time resolution. Since EEG has a high temporal and time resolution, EEG technicians can capture sample rates of a little more than 20 kHz within sub-millisecond (Agrawal and Mane, 2009, p. 19-12). Although EEG is characterized by having a high temporal and time resolution, this particular brain monitoring device does not have a “high spatial resolution” and/or “unlimited anatomical specificity” which is common in fMRI (Agrawal and Mane, 2009, p. 19-12; Staahl et al., 2009; Liu and He, 2008). Because of these limitations, the use of EEG is not effective in terms of accurately locating the activated brain sources nor does it clearly identify whether or not the sources of electrical brain activity is caused by the release of excitatory, inhibitory, and/or modulatory neurotransmitters (Agrawal and Mane, 2009, p. 19-2). Since one of the limitations of EEG is a “high spatial resolution” and “unlimited anatomical specificity” (Agrawal and Mane, 2009, p. 19-12; Staahl et al., 2009; Liu and He, 2008), this study highly recommends the need to incorporate the use of EEG with other brain monitoring devices such as the fMRI (Whittingstall et al., 2010; Liu and He, 2008). By integrating these two brain imaging devices, the doctors can have a better and more accurate brain activity records which can be used in the diagnosis and treatment of the patients. References Agrawal, S. and Mane, V. (2009). Bio-medical Electronics. 2nd Edition. Pune: Nirali Prakashanarihant Printers. Begriche, K., Massart, J., Robin, M., Borgne-Sanchez, A. and Fromenty, B. (2011). Drug-induced toxicity on mitochondria and lipid metabolism: mechanistic diversity and deleterious consequences for the liver. Journal of Hepatology, 54(4), pp. 773-94. Galderisi, S., and Sannita, W. (2006). Pharmaco-EEG: A History of Progress and a Missed Opportunity. Clin EEG Neurosci, 37(2), pp. 61-65 . Graversen, C., Olesen, S., Olesen, A., Steimie, K., Farina, D., Wilder-Smith, O., et al. (2012). The analgesic effect of pregabalin in patients with chronic pain is reflected by changes in pharmaco-EEG spectral indices. British Journal of Clinical Pharmacology, 73(3), pp. 363-372. Liu, Z. and He, B. (2008). fMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints. Neuroimage, 39(3), pp.1198-214. Mucci, A., Volpe, U., Merlotti, E., Bucci, P. and Galderisi, S. (2006). Pharmaco-EEG in Psychiatry. Clin EEG Neurosci, 37(2), pp. 81-98 . 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