Strengths and Weaknesses of Electroencephalography and Magnetic Resonance Imaging

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are both measures adopted to examine human brains’ activities. The former uses magnetic field to detect magnetic change in blood and the latter uses electrodes placed on human skull to detect electric potentials. The main advantages and disadvantages of these two measures present in what they measure, their temporal resolution, their spatial resolution and the effectiveness of their data. Comment by Emma Soneson: This is a good introduction paragraph: I can tell that you’ve followed the ‘funnel’ structure we’ve talked about, and have created a thesis sentence that overviews what you’ll write about in the essay. Well done.

Functional MRI (fMRI) measures hemodynamic changes after enhanced neural activity. “fMRI requires an MRI scanner, a high rate of image acquisition, and specialized pulse sequences to measure localized brain activity.” (Voos& Pelphrey, 2013, p.2) This describes the basic setting for a functional magnetic resonance imaging to operate, which includes an MRI scanner to detect the contrast of blood deoxyhaemoglobin, a fast acquisition of images produced, and programs called pulse sequences to send instructions to the scanner hardware to “turn on or off certain hardware at certain times” (Huettel, Song & McCarthy, 2009, p.42). Currently, the most common fMRI technique is the blood oxygenation level dependent (BOLD) technique, which uses magnetic resonance to detect the direction of blood flow through the change of oxygen content in blood. Ogawa, Lee, Nayak, and Glynn (1990) first discovered the BOLD intrinsic contrast mechanism. To describe the mechanism generally, when a brain region is active, the neurons in that region will communicate information with each other through electrical impulses – synaptic potentials and action potentials. This activity needs energy, which is supplied by glucose and oxygen. As a result, elevated levels of oxyhemoglobin occur in active areas, giving rise to an increase in the surrounding ratio of oxyhemoglobin to deoxyhemoglobin. To meet the energy and oxygen demand, oxygenated blood rushes to the area and displace the deoxygenated blood (Ogawa, Lee, Nayak, & Glynn, 1990). The principle of MRI is that when people lie in an MRI scanner, the protons in people’s bodies tend to line up with the magnetic field (Huettel, Song & McCarthy, 2009). These protons then spin around the axis of the field (Huettel, Song & McCarthy, 2009). In oxygenated blood, protons are organised and spin at the same rate (Bekinschtein, 2019). In contrast, protons in deoxygenate blood are not as organised, because deoxygenated haemoglobin molecules have magnetic field gradients that alter the rate of spin of nearby diffusion hydrogen nucle. The local magnetic field is thus affected, and the variation in the magnetic field can be detected by the long TE (time to echo) gradient echo pulse sequences used in fMRI. Thus the direction of oxygenated blood flow can be detected by MRI scanners through the difference in MR signals produced by oxygenated and deoxygenated blood. Comment by Emma Soneson: Since you clearly explain the quotation in the previous sentence here, you don’t have to include both Comment by Emma Soneson: Good understanding Comment by Emma Soneson: Almost word-for-word.

Electroencephalography (EEG) is a non-invasive method to detect the brain’s neural activities through measuring brain’s electric fields. Electrodes placed on humans’ scalp record voltage potentials, which result from current flow “in and around neurons” (Biasiucci, Franceschiello & Murray, 2019, p. R80). The main potential EEG measures is the electric activities associated with post-synaptic dendritic currents generated in cortical pyramid cells. This neural activity is called the 'primary current' (Denes Szucs, lecture notes). “An excitatory postsynaptic potential at an apical dendrite will result locally in an intracellular current source. At the soma, there will be an intracellular current sink and extracellular current source. These source–sink configurations are also known as current dipoles” (Biasiucci, Franceschiello & Murray, 2019, p. R80). Brain tissue, liquor and the skull act as conductive medium that electric waves propagate. This propagating electric activity is called the 'secondary current' (Denes Szucs, lecture notes). This current is also picked up by EEG electrodes placed on the human scalp. EEG can detect only a portion of all the varieties of electrical activity going on in the brain. Nevertheless, electric signals detected may include physiologic electrical activity, “such as cardiac, ocular, and other muscular activity” and environmental noise “such as computer screens and other electric equipment, power lines”. (Biasiucci, Franceschiello & Murray, 2019, p. R80).

After describing two methods separately, we will compare their weakness and strengths. A drawback of fMRI is that “the BOLD signal cannot provide information regarding directions of information flow.” (Voos& Pelphrey, 2013, p.3) That is to say, fMRI cannot identify the exact sequential neural activities in the process of information transmission, as BOLD is a neurometabolic signal and has a time delay from neural activities. Also because of the time delay, the temporal resolution of fMRI is coarse, on the order of seconds. (Shah，Anderson, Lee& WigginsIII，2010）In contrast, EEG directly measures neuronal activity in real time through “measuring the electrical activity of neuronal cell assemblies on a submillisecond time scale” (Michel, Murray, Lantz, Gonzalez, Spinelli, & Grave De Peralta, 2004). Therefore, EEG has a much higher temporal resolution than fMRI. Another limitation of fMRI is that because the BOLD signal relies upon a relatively slow vascular response, both inhibitory and excitatory inputs to a neuron from other neurons will sum up and consequently the BOLD signal within the neuro will appear to be zero, as the two input would cancel out (Voos& Pelphrey, 2013, p.3). Although EEG does not have such problem, unfortunately, EEG face the problem that the signals measured on the scalp surface do not directly indicate the location of the active neurons in the brain, as a result of the ambiguity of the underlying static electromagnetic inverse problem (Helmholtz, 1853; Michel, Murray, Lantz, Gonzalez, Spinelli, & Grave De Peralta, 2004 ). “Many different source configurations can generate the same distribution of potentials and magnetic fields on the scalp.” (Michel, Murray, Lantz, Gonzalez, Spinelli, & Grave De Peralta, 2004) Therefore, maximal activity at certain electrodes do not certainly mean that the generators were located in the area underlying them (Michel, Murray, Lantz, Gonzalez, Spinelli, & Grave De Peralta, 2004). The spatial resolution, which is the ability to distinguish differences between nearby spatial locations, determines how clear boundaries between neighbouring functional areas in the brain can be identified (Huettel, Song & McCarthy, 2009). The spatial resolution of fMRI is higher than that of EEG, as a result of EEG’s inverse problem. However, the spatial resolution of an fMRI study is influenced by the voxel size, the smaller the voxel size, the higher the spatial resolution. Due to the limitations of “reduced signal compared with noise and increased acquisition time” (Huettel, Song & McCarthy, 2009, p.244), pitifully, the voxel size and thus fMRI’s spatial resolution cannot be optimised. Comment by Emma Soneson: Almost word-for-word. Please be careful.

In conclusion, fMRI measures indirect nuerometabolic signals while EEG directly measure neural l activities; fMRI has higher spatial resolution but lower temporal resolution than EEG; fMRI may acquire meaningless result while EEG’s results cannot tell which brain region causes such responds. Both measures have their strengths and weaknesses and it is important to adopt them both while conducting researches to acquire a fuller picture of brain activities.

References

1. Voos A. and Pelphrey K. (2013) Functional Magnetic Resonance Imaging, Journal of Cognition and Development, 14:1, page 1-9, DOI: 10.1080/15248372.2013.747915
2. Bekinschtein T. (2019) lecture handout, Brain Imaging I: Measuring the brain’s mind, University of Cambridge
3. Biasiucci, A., Franceschiello, B., & Murray, M. M. (2019, February 4). Electroencephalography. Current Biology. Cell Press. https://doi.org/10.1016/j.cub.2018.11.052
4. Ogawa , S. , Lee , T. M. , Nayak , A. S. , & Glynn , P. ( 1990 ). Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magnetic Resonance in Medicine , 14 , 68 – 78 . 
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6. Huettel , S. A. , Song , A. W. , & McCarthy , G. (2009). Functional magnetic resonance imaging ( 2nd ed.). Sunderland , MA : Sinauer
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