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Evaluate the Current Usefulness and Future Potential of Functional Brain Imaging in Two Areas of Applied Psychology

Since I’m mad busy with revision at the moment I thought I’d share an essay I wrote in my first term of first year. This is probably my favourite of my essays, partly because it was a subject I was interested in and partly because I got a good grade for it – A* 😀

Evaluate the Current Usefulness and Future Potential of Functional Brain Imaging in Two Areas of Applied Psychology

Introduction

Functional brain imaging, Functional Magnetic Resonance Imaging (fMRI) in particular, has opened new avenues of applied psychology such as lie detection and detection of consciousness in patients with disorders of consciousness. After a brief and simplified explanation of how fMRI works the positives, negatives and ethical implications of lie detection will be discussed. This will be followed by a discussion of the progress, potential flaws and risks, and ethical implications of detection of consciousness in patients with disorders of consciousness. Concluding, it will be shown that while progress has been made in both areas, lie detection still remains controversial and unreliable, while detection of consciousness is progressing  toward methods for unambiguous classifications of states of consciousness.

How Functional Magnetic Resonance Imaging Works

Functional Magnetic Resonance Imaging (fMRI) is advancement on Magnetic Resonance Imaging (MRI) that allows rapid-detection of activation in areas of the brain. In simplistic terms, an fMRI scan consists of a magnetic pulse (often termed the Radio Frequency or RF Pulse) being transmitted to the brain, and a subsequent Nuclear Magnetic Resonance signal, caused by resonance induced in certain nuclei, being detected (Buxton 2002). Using Blood Oxygen Level Dependence (BOLD) the metabolism rate, and thus brain activation, can be measured. BOLD imaging works on the basis that unlike oxygenated blood, deoxygenated blood is paramagnetic and thus reduces the MR signal returned. As an area of the brain activates the level of deoxygenated blood decreases, and thus the MR signal increases. These signals can then be mapped onto an image of the brain.

 Lie Detection using fMRI

Research has shown that there is potential for fMRI techniques to be useful for detecting if a participant is attempting deceit. This works by looking at the areas of the brain that are activated when the participant is called to tell the truth, to establish a “base state”, and comparing this to the activation that is seen when the participant is attempting to deceive (Langleben 2008). This “cognitive subtraction” is then analysed to identify areas of the brain that are identified with deceit, such as the Pre-Frontal Cortex (PFC) as identified by Spence (2008), and more specific foci identified by Christ et al. (2009).

A review by Luber et al. (2009) showed that the research into detection of deceit using fMRI can also be put into use to inform research into use of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). Deceit-condition behaviour can be modified by stimulating areas of the brain involved in deceit, thus increasing the reaction time of participants or increasing the size of motor potentials after motor-cortex stimulation.

Studies have shown that fMRI lie detection has an accuracy of between 76% to over 90% (Langleben 2008). Techniques employing fMRI have inherent improvements in detection of deceit over current peripheral nervous system (PNS) exploiting techniques, such as the Skin Conductance Response (SCR), as fMRI is a more direct source and suffers less noise from other sources and less risk of countermeasure actions, such as controlling the autonomic system (Luber et al. 2009). Also SCR and Electroencephalography (EEG) tests are subject to countermeasures such as artificially increasing the salience of truth statements (Langleben 2009).

However fMRI techniques are still somewhat susceptible to the saliency issue (Langleben 2005), and critically suffer from a reliance on compliance of the participant. As mentioned above the technique relies on a comparison of truth and deceit states of the brain, and in order to collect this data the participant must give genuine truth responses when called to (Langleben 2008, Spence 2008). The participant also has to be physically compliant enough to remain still in the fMRI machine to allow accurate scans to be obtained, since it is highly sensitive to any movement during scanning (Spence 2008).

The validity of the experimental paradigm is also critical to accurate results. Luber (2009) and Spence (2008) have both discussed this concern, raising the issue of whether the participant is really called to deceive, and whether activation of different areas of the brain is a certain indicator of deception. The amount of processing required to arrive at a conclusion is also a source of potential error, with manual intervention and interpretation required and inferences drawn from correlational data (Luber 2009). The experimenter and imager must manipulate the images to fit the model, including realignment, normalisation, and smoothing, then choose a statistical model to apply and decide how much noise in the original scans to accept or ignore (Spence 2008). This may explain why there is a lack of replication in experimental results in this topic, with different areas of the PFC reported to have higher activation, and one study even showing higher PFC activation in the truth state (Langleben et al. 2005, Luber 2009, Spence 2008)

Ethically the use of functional brain imaging to detect deception is controversial for a number of reasons. Firstly there are concerns over how safe fMRI really is (Farah 2002). Privacy of the participant is another ethical issue that must be considered, since the imaged captured and the analysis performed could reveal information and opinions of the participant other than those intentionally under investigation, such as racial prejudices for example (Farah & Woolfe 2004). There are also concerns in application; it does not take a great leap to imagine how techniques for detection of deceit could be used in a forensic or national security setting to elicit information from a participant for legal or illegal use. Finally there are concerns over the public perception and media portrayal of fMRI that are especially relevant for a controversial issue such as lie detection that captures the public interest. Media portrayal of fMRI studies often lack a critical component, painting an optimistic interpretation of the studies which can mislead the public and create a false conception of the accuracy of the technique (Brown & Murphy 2010, Racine et al. 2005).

Although many advances have been made in fMRI lie detection it has not yet developed to a stage that provides results that are accurate and reliable enough for the uses for which it is hoped to be put to For example, as evidence in court for a variety of cases including “competence to waive Miranda rights, subjective experience of pain in tort cases, custody determinations, mens rea defenses for fraud, kidnapping, burglary, and even murder” (Brown & Murphy 2010:1132). However if the ethical issues are carefully considered by safeguarding the safety and strict confidentiality of the participant as well as ensuring that anyone interpreting or using the results of the analysis are well educated in the shortcomings of the technique; perhaps it can be used to supplement current approaches, both physiological and psychological, for voluntary participants.

Detection of Consciousness in Patients with Disorders of Consciousness

There are different disorders of consciousness which can be difficult to differentiate, such as coma, vegetative state, locked in syndrome, and minimally conscious state (Schnackers et al. 2009). Patients with consciousness impairments are currently misdiagnosed up to 43% of the time (Coleman 2009, Monti 2010). The diagnosis of a patient’s state carries important ethical implications. These include the options and choice of clinical treatment, the discussions removal of life support in cases of long term persistent vegetative state, and prognosis (Coleman 2009, Eickhoff et al. 2008, Vanhaudenhuyse et al. 2010).

Eickhoff et al. (2008) showed that a comatose woman with a rating of 4 on the Glasgow Coma Scale (GCS) exhibited the same brain activation to visual, auditory, and physical stimulus as healthy controls, as well as activation of Broca’s area (involved in comprehension of language) to speech stimulus. The study also indicated that emotional content of the speech, specifically familiarity of the speaker to the patient, was processed. Monti et al. (2010) found that four patients they assessed who had previously been classified as being in vegetative state showed responses to imaging and communication tasks, and on further testing one patient seemed to be able to respond to yes or no questions. There has also been promising research into the default mode network (DMN), a network of brain areas that are more active at rest than when the participant is involved in cognitive tasks. The research suggests that connectivity strength of the DMN correlates to levels of consciousness (Vanhaudenhuyse et al. 2010).  This recent research is particularly useful since it looks at passive brain activity and therefore does not require the cooperation of the patient (Vanhaudenhuyse et al. 2010).

While research has shown activation of certain areas that are distinct for deceit conditions against truth conditions, we must be careful how we interpret this. We must be wary of the unproven nature of neuro-essentialism; the assumption that subjective phenomenological inferences can be made directly from physiological activity (Brown & Murphy 2010, Eickhoff et al. 2008, Racine et al. 2005, Shamoo 2010). This is particularly relevant with fMRI since what is being measured is not neuronal activity but metabolism of oxygen, which is an indirect measurement (Brown & Murphy 2010, Buxton 2002). Despite progress and some success in detecting consciousness, there is still more work required to establish unambiguous classifications of the various consciousness-states (Riganello et al. 2009). As mentioned above, there are ethical and practical concerns over the safety of fMRI and the possibility of breaching the privacy of the participant. The issues of neuro-essentialism is obviously especially important in this area as the results of the imaging study could potentially be used in life-ending and withdrawal of care decisions, so there is even more need to be certain that the physiological activity does correlate to subjective consciousness (Racine et al. 2005). In addition to these concerns there is the extra concern of consent. Obviously patients with disorders of consciousness cannot give informed consent. (Farah 2002).

The issue of neuro-essentialism applies to the entire field of neuro-psychology, however within the area of disorders of consciousness it will be difficult to collect enough data to be able to confidently say that the neurological behaviour correlates to specific levels of consciousness, not least due to the relatively small number of patients available for this kind of study. However the uncertainty over neuro-essentialism could be argued to be outweighed by the potential benefits in terms of improved care and better informed decisions regarding end-of-life choices. Consent in this instance could be argued to fall ethically on the same ground as for critical medical treatment, since the results of the fMRI would be used for determining appropriate clinical care and whether to continue providing life-support.

In summary regarding detection of consciousness, the current methods of diagnosing levels of consciousness are fallible. The new fMRI techniques are still at an early stage and there is much work to be done before they can be put into clinical practice, however the current research is promising and looks like it is leading toward important new ways to determine levels of consciousness in patients with disorders of consciousness.

Conclusion

Lie detection and detection of consciousness in patients with disorders of consciousness using fMRI are still in early stages and require development before they are useful. Both suffer from ethical issues which have to be carefully considered and managed, such as privacy concerns (Farah & Woolfe 2004), safety (Farah 2002), and issues around accuracy and reliability of the analysis, particularly in relation to the issue of neuro-essentialism (Racine et al. 2005). The accuracy of fMRI lie-detection is uncertain (Luber 2009, Spence 2008), rendering the technique of questionable suitability for applied use, for example in court rooms (Brown & Murphy 2010). The techniques could potentially be used in conjunction with existing approaches to slightly improve overall reliability. On the other hand research into detection of consciousness has made significant progress by positively identifying consciousness in some patients previously described as being in vegetative state (Monti et al. 2010) and new research into the DMN looks promising (Vanhaudenhuyse et al. 2010).

References

Brown, T. & Murphy, E. (2010). Through A Scanner Darkly: Functional Neuroimaging As Evidence Of A Criminal Defendant’s Past Mental States, Stanford Law Review, 62(4), 1119-1209

Buxton, R. (2002). Introduction to Functional Magnetic Resonance Imaging Principles and Techniques, Cambridge University Press: Cambridge

Christ, S.E., Van Essen, D.C., Watson, J.M., Brubaker, L.E., McDermott, K.B.  (2009). The Contributions of Prefrontal Cortex and Executive Control to Deception: Evidence from Activation Likelihood Estimate Meta-analysis,  Cerebral Cortex 19 (7), 1557-1566

Coleman, M.R., Davis, M.H., Rodd, J.M., Robson, T., Ali, A., Owen, A.M., Pickard, J.D. (2009). Towards the routine use of brain imaging to aid the clinical diagnosis of disorders of consciousness, Brain: A Journal of Neurology 132 (9), 2541-2552

Eickhoff, S.B., Dafotakis, M., Grefkes, C., Stöcker, T., Shah, N.J., Schnitzler, A., Zilles, K., Siebler, M. (2008). fMRI Reveals cognitive and emotional processing in a long-term comatose patient, Experimental Neurology, 214 (2), 240-246

Farah, M. (2002). Emerging Ethical Issues in Neuroscience, Nature Neuroscience, 5 (11), 1123-1129

Farah, M., and Woolfe, P. (2004). Monitoring and Manipulating Brain Function, New Neuroscience Technologies and Their Ethical Implications, Defining right and wrong in brain science: Essential readings in neuroethics, 37-57. Washington, DC US: Dana Press, 2007. PsycINFO, EBSCOhost (accessed November 5, 2010).

Langleben, D., Loughead, J., Bilker, W., Ruparel, K., Childress, A., Busch, S., et al. (2005). Telling Truth From Lie in Individual Subjects With Fast Event-Related fMRI, Human Brain Mapping, 26(4), 262–272

Langleben, D (2008). Detection of deception with fMRI: Are We There Yet, Legal & Criminological Psychology, 13(1), 1-9

Luber, B., Fisher, C., Appelbaum, P., Ploesser, M., Lisanby, S., (2009). Non-invasive brain stimulation in the detection of deception: Scientific challenges and ethical consequences. Behavioral Sciences & the Law, 27(2), 191-208

Monti, M., Vanhaudenhuyse, A., et al. (2010). Willful modulation of brain activity in disorders of consciousness. The New England Journal of Medicine, 362(7), 579-589.

Riganello, F. & Sannita, W. (2009). Residual brain processing in the vegetative state, Journal of psychophysiology 23(1), 18-26

Racine, E., Bar-Ilan, O., & Illes, J. (2005). fMRI in the public eye. Nature Reviews Neuroscience, 6(2), 159-164

Schnackers, C., Vanhaudenhuyse, A., Giacino, J., Ventura, M., Boly, M., Majerus, S., Moonen, G., Laureys, S., (2009). Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment, BMC Neurology, (9) art. no. 35

Shamoo, Adil E. (2010) Ethical and Regulatory Challenges in Psychophysiology and Neuroscience-Based Technology for Determining Behaviour. Accountability in Research, 1(17), 8-29

Spence, Sean A.  (2008). Playing Devil’s Advocate, Legal and Criminological Psychology, 13(1), 11-25

Vanhaudenhuyse, A., Noirhomme, Q., Tshibanda, L., Bruno, M, Boveroux, P, Schnakers,P., Soddu, A., Perlbarg, V., Ledoux, D., Brichant, J., Moonen, G., Maquet P., Greicius, M., Laureys, S.,  and Boly, M. (2010). Default Network connectivity reflects the level of consciousness in non-communicative brain-damaged patients, Brain: A Journal of Neurology, 133(1), 161-171

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