Created with Sketch. 0203 9500 830
We are currently open

Measurement of Language Processing and the Value of FMRI and EEG Techniques

Written by Rowan T.

 

1. Introduction

Investigations into language processesing have previously identified that different aspects of language may be localised to very specific cerebral areas of the brain (Friederici and Singer, 2015).  Specifically, speech production is located in what is known as Broca’s area, which is located in the frontal lobe and has been predominatley associated with speech production for many decades (Tate et al, 2014).  Comprehension of language however has been directly linked to an area in the superior temporal guyrus (STG) encircling the auditory cortex defined as Wernicke’s area, although as Binder (2017) notes, these distinctions may need revision as there is improvements in understanding of the way language is processed.  For example,  a third area has been identified in the inferior parietal lobule, known as Geschwind’s territory, which appears to act as an integral connector in transfering information between the two primary speech areas of the brain (Friederici, 2015). 

Improvements in technology and thus the ability to examine processing during language activity have further identified that language processing, as an activity, may follow a more integrated pattern in terms of neuronal activity than was previously considered.  These insights have developed through the use of techniques such as fMRI (functional magnetic resonance imaging) and EEG (electroencephalography) as noted by Friederici and Singer (2015). To understand how these techniques have contributed to understanding a brief overview of each is provided.

 

2. fMRI and EEG

In the case of EEG, the individual being assessed has electrodes placed on their scalp in order to record the signal emitted by dendritic currents.  These currents are created when neurons in the brain are stimulated, for example by language, music or images.  The subsequent output is highlighted on a screen allowing assessors to identify which areas of the brain are activated in response to the specified stimului (Weiss & Mueller, 2012). 

The fMRI approach is to measure changes in oxygen levels, volume and blood flow, a process which is defined as BOLD (blood-oxygen-level dependence); what this means, as noted in Ward (2015), is that when stimulated, there is an elevation in oxygen levels in the area of the brain being activated.  Tests have shown that when faced with a perceptual or cognitive task, there is an increase in the blood flow to specific areas, raising oxygen levels which in turn elevates the magnetic properties of subcutaneous tissue, (De Maeyne et al, 2015).  It is this process which makes the test highly efficient for psychological testing and responses.  In the case of language therefore, physiological changes in response to stimulii can be utilised and analysed to identify how language impacts on the structure and activity of the brain (Poeppel and Embick, 2017).

It appears from examination of a combination of fMRI and EEG testing that syntactic processes appear to activate the temporal cortex and inferior frontal cortex, but semantic processes activate the less lateralised temporo-frontal networks although the two areas communicate through the corpus callosum (Paulman, 2015; Cook, 2018). From a developmental and treatment perspective in language impairment therefore this can potentially mean targetting specific areas to encourage neuronal firing in previously under-used areas, when the neurons are not completely damaged or absent as noted by Cipollari et al, (2015).

These two processes (EEG and fMRI) have also been invaluable in delivering insights into the way that language is processed at the physical and cortical level, specifically in terms of emotional or psychological responses to particular types of language.  Humour, anger, and pragmatic inference along with the physiological responses in terms of brain activity have now been tested on live subjects. For example, an extensive work by Iaconboni (2007) identified that political words appeared to activate the amygdala, raising the feelings of anxiety, disgust, reward and connection, depending on the ideology of the individual being tested. Iaconboni’s work and that of Grass et al, (2016) underline the value of these testing processes in further understanding of the way that language is both processed and equally, felt, at an emotional level by humans.   

The challenge however is in recognising the advantages and disadvantages of both techniques and what these may mean for research into language processing and development (Ullman, 2015). For example, fMRIs are non-invasive and do not expose subjects to radiation.  As a result, the tests can be undertaken with young babies and children and vulnerable adults which has made a major contribution to understanding how language development and processing may change over time.  Crucial in this respect is that fMRI’s have allowed for practical investigation of the innateness of language, and the brain’s response to different communication approaches, as well as the development of different languages and sound systems (Huettal et al, 2004; Harley, 2013) . Furthermore, fMRI’s can be invaluable for assessing pre and post-operative language skills in the case of brain tumours and epilepsy (Tyndall et al, 2017).  In essence, and looking at the technique from neurolinguistic theory perspectives, fMRIs offer a means of mapping connections between motor and cognitive processing and a means of testing, in a practical way theories of language development and cognition.

The drawback when using an fMRI, however, is that the process is slow in practice, and less efficient in terms of temporal resolution.  Although the spatial resolution is excellent, the BOLD signals are actually an indirect indication of neuronal activity which means that there is a lack of distinct and direct measurement of neural connections when a task is being completed (Stokes et al, 2015).  Despite this limitation the technique has greatly contributed to understanding how the brain processes language at the neuronal level.

What is interesting however is that EEG’s have high temporal, but low spatial resolution. Indeed from a research perspective, EEG offers a number of strong advantages.  Not only are the sensors much more cost efficient than the large fMRI scanners required for effective testing, but the measurements of activity are made in milliseconds (Beres, 2017). This means that responses to language at the temporal level can be more accurately measured when compared to fMRI tests. A further advantage is that fMRI requires stillness for image capture, but EEG’s can be undertaken while the subject is moving (Beres, 2017). 

This does not mean that the EEG does not also have disadvantages.  The first of these is that accurate EEG testing requires similar paradigms, whilst fMRI’s can deliver a wider range of outcomes, due to their capacity to utilise block-design testing.  This flaw in the EEG process can be mitigated by the capacity of the process to use coherence testing, which has increased understanding and knowledge in the area of the dynamic processing of language in the brain (Weiss & Mueller, 2003; 2012).  Given that language is a living, evolving process that is ongoing during an interaction between interlocutors, EEG’s can be highly effective in understanding the connections and networks of language processing in the brain, and thus how language is processed overall.  The mechanisms by which this occur are still under investigation as there are suggestions that this may change during developmental processes as language ability matures. 

Overall therefore, it is the measurement of these mechanisms that underline of the value of using techniques such as fMRI and EEG to examine the neurobiological basis of language processing. In conclusion,  evaluating these two techniques and their benefits and flaws, it would appear that whilst individually they have made major contributions to understanding the nature of language processing, it is when they are used in a complementary way that the highest level of information and understanding can be achieved.   

 

References

Beres, A.M., 2017. Time is of the Essence: A Review of Electroencephalography (EEG) and Event-Related Brain Potentials (ERPs) in Language Research. Applied psychophysiology and biofeedback42(4), pp.247-255.

Binder, J.R., 2017. Current Controversies on Wernicke’s Area and its Role in Language. Current neurology and neuroscience reports17(8), p.58.

Cipollari, S., Veniero, D., Razzano, C., Caltagirone, C., Koch, G. and Marangolo, P., 2015. Combining TMS-EEG with transcranial direct current stimulation language treatment in aphasia. Expert review of neurotherapeutics15(7), pp.833-845.

Cook, N.D., 2018. The brain code: Mechanisms of information transfer and the role of the corpus callosum (Vol. 2). Routledge.

De Baene, W., Duyck, W., Brass, M. and Carreiras, M., 2015. Brain circuit for cognitive control is shared by task and language switching. Journal of cognitive neuroscience27(9), pp.1752-1765.

Friederici, A.D. and Singer, W., 2015. Grounding language processing on basic neurophysiological principles. Trends in cognitive sciences19(6), pp.329-338.

Friederici, A.D., 2015. White-matter pathways for speech and language processing. In Handbook of clinical neurology (Vol. 129, pp. 177-186). Elsevier.

Harley, T.A., 2013. The psychology of language: From data to theory. Psychology press.

Huettel, S.A., Song, A.W. and McCarthy, G., 2004. Functional magnetic resonance imaging (Vol. 1). Sunderland, MA: Sinauer Associates.

Paulmann, S., 2015. The neurocognition of prosody. In Neurobiology of language (pp. 1109-1120).

Poeppel, D. and Embick, D., 2017. Defining the relation between linguistics and neuroscience. In Twenty-first century psycholinguistics (pp. 103-118). Routledge.

Stokes, M.G., Wolff, M.J. and Spaak, E., 2015. Decoding rich spatial information with high temporal resolution. Trends in cognitive sciences19(11), pp.636-638.

Tate, M.C., Herbet, G., Moritz-Gasser, S., Tate, J.E. and Duffau, H., 2014. Probabilistic map of critical functional regions of the human cerebral cortex: Broca’s area revisited. Brain137(10), pp.2773-2782.

Tyndall, A.J., Reinhardt, J., Tronnier, V., Mariani, L. and Stippich, C., 2017. Presurgical motor, somatosensory and language fMRI: technical feasibility and limitations in 491 patients over 13 years. European radiology27(1), pp.267-278.

Ullman, M.T., 2015. The declarative/procedural model: a neurobiological model of language learning, knowledge, and use. In Neurobiology of language (pp. 953-968).

Ward, J., 2015. The student's guide to cognitive neuroscience. Psychology Press.

Weiss, S. and Mueller, H.M., 2003. The contribution of EEG coherence to the investigation of language. Brain and language85(2), pp.325-343.

Weiss, S. and Mueller, H.M., 2012. “Too many betas do not spoil the broth”: the role of beta brain oscillations in language processing. Frontiers in Psychology3, p.201.

Free dissertation
Free plan
Free extra topic
Extended amendments period
Free instalment plan
Free PhD Topic and Outline
£20 off next order
£30 off next order
Free draft
Free 2,000 word Essay
Free 15 Writers Bag
Priority booking
Get your chance to win a prize!
Enter your email address and spin the wheel. This is your chance to win amazing discounts!
Our in-house rules:
  • One game per user
  • Cheaters will be disqualified.