Analysis of the MRI Controversy

The basis of Magnetic resonance imaging (MRI) is that a more active area of the brain will require a greater blood flow, therefore a scan of relative blood flow will indicate regions of greatest activity.  BOLD fMRI (blood oxygen level-dependent functional magnetic resonance imaging) measures the local concentration of deoxygenated haemoglobin, as a result of the increase in blood flow and influx of oxygenated haemoglobin (Mayhew, 2003 p.1023).  Deoxygenated haemoglobin acts as a paramagnetic contrast agent (Kim & Ugurbil, 1997 p.59) but the quantitative relationship between observed BOLD and physiological changes is not precise (Kim, Tsekos, & Ashe, 1997 p.191).  Assuming that the activities of an individual are being carefully monitored a comparison can be made between the scans afforded from different times in which different behaviours are manifest or activities are performed.  The local increase in deoxygenated haemoglobin, together with measurable blood flow changes are assumed to be due to greater neuronal activity.  A neuroimage is a computer generated representation of numerical data, so not in fact like a photograph, but more a fancy chart or graph (Kulynych, 1997 p.1254).

MRI, in essence, assumes that a neural correlate of consciousness (NCC) can be definitively identified for the behaviour or activity being investigated.  In order for activity to be known and an NCC identified then it has to be accepted that a behaviour is wholly attributable to activity within a specific brain region (Datta, 2006).  Hence the use of a functional imaging scan within legal situations is reliant on the assumption that it is an accurate representation of the brain and has a definitive medical basis (Kulynych, 1997 p.1252).  However the majority of psychologists, with the exception of staunch reductionists, would agree that activity is distributed (Dobbs, 2005).  Indeed MRI overlooked this networked activity, and ignores the fact that localized activity could be solely to do with communication between regions that are in themselves critical.  Thus the lighting up of the central executive area on fMRI may not be due to that specific area being solely involved in an activity but because it is jointly involved in so many (Dobbs, 2005).  Conversely the activity of a brain region in response to a query might be due to a brand effect, such as when individuals are asked about a bran preference (Narasimhan, 2004).

The use of MRI has been investigated within lie detection, on the basis that the anterior cingulate cortex and superior frontal gyrus will become more active when the subject lies, when compared to truthful situations (Tancredi, 2005).   Activity has also been shown in the left and right ventrolateral prefrontal cortex (Bell & Grubin, 2010).   A controversy over this is that the anterior cingulate cortex is involved in straightforward decision making.  Much lie detection requires answering of questions, which can involve decision making, even if that is the decision about whether to answer or not.  The univariate processing algorithms that are used to calculate fMRI scans are gross and vague methods of measuring detail, not least because the reason for the activity in each voxel is not given. Each voxel encompasses thousands of neurons, any combination of which could be firing, for a whole spectrum of reasons (Dobbs, 2005).  The ventrolateral prefrontal cortices are areas associated with response inhibition (Bell & Grubin, 2010) suggesting that there needs to be a disinhibition in order to tell a lie.  Therefore the dominant response of telling the truth is [apparently] inhibited when lying.  This of course also assumes that the dominant response is telling the truth.

The amount of oxygen supplied to activated neural tissue by the increase in blood flow is far more than the metabolic needs of that tissue (Mayhew, 2003 p.1023).  Likewise the fact that it is the inference of the of the oxygen level to activity (Thompson, Peterson, & Freeman, 2003 p.1070) that needs to be borne in mind as an inference is not a definitive association.  Furthermore abnormality is only a deviation from an averaged normality, and in terms of brain scans such as fMRI, the average is not made up of identical results anyway, it is very much an average of sometimes wildly disparate results. 

The fact that fMRI presented a problem was highlighted as early as the mid 1990s, when an article within the Stanford Law Review emphasized the illusions that could be generated with fMRI, particularly in terms of an assumption that it provides a window; a direct, unmediated view into internal biological processes (Kulynych, 1997 p.1257).  Likewise in a detailed account about how BOLD signals reflect activity it was stated that ‘positive signal changes may reflect an increased in [neural] spike activity’ commensurate for the functional activity of the given area (Harel, Lee, Nagaoka, Kim, & Kim, 2002 p.908).  Further Harel’s findings indicated that a reduction in BOLD could be due to redistribution of blood to other [more active] areas, rather than in fact due to a new blood flow in the area of focus.

The redistribution of blood flow is one of the cited reasons for caution in interpretation of fMRI results, according to Dobbs.  Neuronal action takes a matter of milliseconds but changes in blood flow are measured in seconds, a factor out for comparisons (Dobbs, 2005).  Therefore the claim that one particular aspect of neuronal activity is the cause of a much larger blood surge, is illogical and could be incorrect.  The blood changes could be the result of the neuronal activity but also other associated activities that would have been the result of that activity.  Hence the chain of inferences are all closely linked and if one was to be disproven then the whole chain could fall down as a result. It is not to say that all of the inferences are necessary inaccurate and untrue, just that the evidence for each of them is not as robust as might be hoped, and in many cases may be sparse in nature (Brammer, 2004). 

 

References                                                                                

Bell, B. G., & Grubin, D. (2010). Functional magnetic resonance imaging may promote theoretical understanding of the polygraph test. Journal of Forensic Psychiatry & Psychology, 21(1), 52.

Brammer, M. (2004). Brain scam? Nature Neuroscience, 7(10), 1015-1015.

Datta, S. (2006). Understanding the mind. In S. Datta, et al. (Eds.), From cells to consciousness (2nd ed., pp. 139-180). Milton Keynes: The Open University.

Dobbs, D. (2005). Fact or phrenology? Scientific American Mind, 16(1), 24-31.

Harel, N., Lee, S. P., Nagaoka, T., Kim, D. S., & Kim, S. G. (2002). Origin of negative blood oxygenation level–dependent fMRI signals. Journal of Cerebral Blood Flow & Metabolism, 22(8), 908-917.

Kim, S. G., Tsekos, N. V., & Ashe, J. (1997). Multi-slice perfusion-based functional MRI using the FAIR technique: Comparison of CBF and BOLD effects. NMR in Biomedicine, 10(45), 191-196.

Kim, S. G., & Ugurbil, K. (1997). Comparison of blood oxygenation and cerebral blood flow effects in fMRI: Estimation of relative oxygen consumption change. Magnetic Resonance in Medicine, 38(1), 59-65.

Kulynych, J. (1997). Psychiatric neuroimaging evidence: A high-tech crystal ball? Stanford Law Review, 49(5), 1249-1270.

Mayhew, J. E. W. (2003). A measured look at neuronal oxygen consumption. Science, 299, 1023-1024.

Narasimhan, K. (2004). Brain scam? Nature Neuroscience, 7(7), 683-683.

Tancredi, L. R. (2005). The new lie detectors. Scientific American Mind, 16(1), 46-47.

Thompson, J. K., Peterson, M. R., & Freeman, R. D. (2003). Single-neuron activity and tissue oxygenation in the cerebral cortex. Science, 299(5609), 1070-1072.

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~ by alanbrrtn on April 25, 2010.

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