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The Brain and Behavior: Limitations in the Legal Use of Functional Magnetic Resonance Imaging

Published online by Cambridge University Press:  06 January 2021

Laurence R. Tancredi  and
Jonathan D. Brodie
Laurence R. Tancredi
Affiliation:
New York University School of Medicine
Jonathan D. Brodie
Affiliation:
New York University School of Medicine
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Extract

Brain imaging is one of the most remarkable technological advances towards understanding the relationship of behavior to brain anatomy and physiology. Brain images provide insight to understanding behavior. Additionally, the images themselves carry great impact, particularly when used to show differences in either the anatomy or the biological functioning of two different brains. For these reasons, brain images have increasingly been used in both criminal and civil trials.

After describing some general features of brain imaging, we will focus on functional magnetic imaging (fMRI), as many believe this technology has the most potential for advancing our understanding of how parts of the brain function, including perhaps linking specific functions with cognition and behavior. Brain imaging as a field is vast and therefore our discussion will be limited. First, we will assess the advantages and limitations of fMRI, including research efforts towards standardizing equipment thereby assuring reliability and reproducibility.

Type
Article
Information
American Journal of Law & Medicine , Volume 33 , Issue 2-3 , June 2007 , pp. 271 - 294
Copyright
Copyright © American Society of Law, Medicine and Ethics and Boston University 2007

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References

1 Schmid, Michael C. et al., Simultaneous EEG and fMRI in the Macaque Monkey at 4.7 Tesla, 24 Magnetic Resonance Imaging 335, 335 (2006)CrossRefGoogle ScholarPubMed (pointing out that the simultaneous use of these technologies has the potential of identifying brain networks involved in the actual generation of a discrete EEG pattern); see also Niazy, R. K. et al., Removal of fMRI Environment Artifacts from EEG Data Using Optimal Basis Sets, 28 NeuroImage 720, 721 (2005).CrossRefGoogle ScholarPubMed

2 For a discussion of the benefits of EEG and MEG as supplements to fMRI because of their high temporal resolution, see Wikipedia, Functional Magnetic Resonance Imaging, http://en.wikipedia.org/wiki/functional_magnetic_resonance_imaging (last visited Mar. 2, 2007).

3 Reeves, Donald et al., Limitations of Brain Imaging in Forensic Psychiatry, 31 J. Am. Acad. Psychiatry L. 89, 89 (2003).Google ScholarPubMed

4 As with EEGs and computerized electroencephalography (CEEG). Schmid et al., supra note 1, at 335.

5 As with MRIs, fMRIs, and MEGs. See wikipedia, supra note 2.

6 As in the cases of positron emission tomography (PET) and single-photon emission computed tomography (SPECT). Brodie, Jonathan D., Imaging for the Clinical Psychiatrist: Facts, Fantasies and Other Musings, 153 Am. J. Psychiatry 145, 145 (1996)Google ScholarPubMed; Leenders, K. et al., Positron Emission Tomography of the Brain: New Possibilities for the Investigation of Human Cerebral Pathophysiology, 23 Progress In Neurobiology 1, 1 (1984).CrossRefGoogle ScholarPubMed

7 For a good discussion of the biological fidelity of imaging, see Brodie, supra note 6, at 145.

8 Leenders, supra note 6, at 15-16.

9 See id. at 1, 11.

10 A major conceptual problem with all imaging is that the differences in the tissue are usually small numerically. Reeves, supra note 3, at 90-92. The color coding “can be arbitrary” and set up by individual technicians so that small differences in brain activity among images “may present the illusion of huge differences” because the color can go from blue-green to yellow or red. Id. The significance of this becomes conspicuous in its influence in the courtroom. Id. at 89.

11 Note that anatomical imaging devices, such as computerized axial tomography (CT) and nuclear magnetic resonance (NMR) are important clinically for detecting well-localized brain abnormalities, such as hemorrhages, strokes, brain tumors, and vascular abnormalities.

12 See Brown, Gregory G. & Eyler, Lisa T., Methodological and Conceptual Issues in Functional Magnetic Resonance Imaging: Applications to Schizophrenia Research, 2 Ann. Rev. Clinical Psychol. 51, 51 (2006).CrossRefGoogle ScholarPubMed

13 See id.

14 See Weng, Xuchu et al., Imaging the Functioning Human Brain, 96 Proc. Nat’l Acad. Sci. 11073, 11073 (1999).CrossRefGoogle ScholarPubMed fMRI is being shown to have significant advantages for understanding both anatomy and function of the brain. See Weiller, Cornelius et al., Role of Functional Imaging in Neurological Disorders, 23 J. Magnetic Resonance Imaging 840, 840-41 (2006).CrossRefGoogle ScholarPubMed

15 Leenders et al., supra note 6, at 16.

16 Telephone Interview with Dean Wong, Professor, Johns Hopkins Univ. Sch. of Med., in Balt., Md. (Nov. 24, 2006). Dr. Wong's position regarding PET is that it is not diagnostic for anything but for the differential diagnosis of Alzheimer and perhaps other forms of memory loss. Dr. Wong also emphasized the value of PET for drug development (through the use of radiotracers etc.) Regarding the study of behavior with PET, he also emphasized PET is useful for establishing group differences, not for determining individual differences. It is therefore most useful in a research setting for establishing statistical correlations.

17 Volkow, Nora D. & Tancredi, Laurence R., Positron Emission Tomography: a Technology Assessment, 2 Int’l J. Tech. Assessment Health Care 577 (1986).CrossRefGoogle ScholarPubMed

18 Similar to PET, SPECT involves the use of radionuclides that are administered and detected, but these radionuclides are similar to those used in conventional nuclear medicine. They do not require the presence of a cyclotron for their production and therefore they have a longer half life. SPECT is used mostly for evaluating cerebral blood flow, though it has the potential of being used to obtain information about receptor-site concentration.

19 Volkow & Tancredi, supra note 17, at 578.

20 For a detailed discussion, see Raichle, Marcus E. et al., Blood Flow Measured with Intravenous H215O: II. Implementation and Validation, 24 J. Nuclear Med. 790, 790-91(1983).Google Scholar

21 See id.

22 In both the case of SPECT and PET, radiolabelled tracer molecules are used to define specific physiological measures, especially blood flow and consumption of substrates in tissues, or identified molecular interactions. Matthews, Paul M. et al., Applications of fMRI in Translational Medicine and Clinical Practice, 7 Nature Revs. Neuroscience 732, 732 (2006).CrossRefGoogle ScholarPubMed PET has distinct advantages over SPECT: greater sensitivity for detection of radiopharmaceuticals, the exposure to radiation for the patient is considerably less, and enhanced quality of the images, because of higher spatial and contrast resolution. For an examination of SPECT, see Volkow, Nora D. & Tancredi, Laurence R., Current and Future Applications of SPECT in Clinical Psychiatry, 53 J. Clinical Psychiatry (Supp.) 26 (1992).Google ScholarPubMed

23 Wintermark, Max et al., Comparative Overview of Brain Perfusion Imaging Techniques, 36 Stroke e83, e85 (2005), available at http://stroke.ahajournals.org/cgi/content/full/36/9/e83.CrossRefGoogle ScholarPubMed

24 See id.

25 Id. at e84.

26 See Roy, Charles S. & Sherrington, Charles S., On the Regulation of the Blood-Supply of the Brain, 11 J. Physiology 85, 100-108 (1890)CrossRefGoogle ScholarPubMed. As early as the latter part of the 19th Century investigators recognized the relationship between changes in blood flow and accompanying blood oxygenation of the brain and neural activity. Id. Active nerve cells consume oxygen, which requires increased flow of hemoglobin on red cells through local capillaries. Id. For an erudite discussion of the discovery and its implications, see Friedland, Robert P. and Constantino Iadecola, A Centennial Reexamination of On the Regulation of the Blood-Supply of the Brain, 41 Neurology 10 (1991).CrossRefGoogle Scholar

27 Detre, John A., Clinical Applicability of Functional MRI, 23 J. Magnetic Resonance Imaging 808, 808 (2006).CrossRefGoogle ScholarPubMed

28 E.g., Logothetis, Nikos K., The Underpinnings of the BOLD Functional Magnetic Resonance Imaging Signal, 23 J. Neuroscience 3963, 3963 (2003).CrossRefGoogle ScholarPubMed

29 Id.

30 Id.

31 Cacioppo, John T. et al., Just Because You’re Imaging the Brain Doesn't Mean You Can Stop Using Your Head: A Primer and Set of First Principles, 85 J. Personality & Soc. Psychol. 650, 651 (2003).CrossRefGoogle ScholarPubMed

32 Detre, supra note 27, at 809.

33 Id.

34 See Mintun, Mark A. et al., Blood Flow and Oxygen Delivery to Human Brain during Functional Activity: Theoretical Modeling and Experimental Data, 98 Proc. Nat’l Acad. Sci. U.S.A. 6859, 6863 (2001).CrossRefGoogle ScholarPubMed

35 Id. The accumulation of toxic wastes is related to some extent to glycogen metabolism, but perhaps that is not the whole explanation. This calls into question the nexus or pristine nature of the connection between Cerebral Blood Flow and energy metabolism.

36 See Logothetis, supra note 28, at 3967-69.

37 For a detailed discussion of functional localization, see Brett, Matthew et al., The Problem of Functional Localization in the Human Brain, 3 Nature Revs. Neuroscience 243, 243 (2002).CrossRefGoogle ScholarPubMed

38 Matthews et al., supra note 22, at 732.

39 See Sarter, Martin et al., Brain Imaging and Cognitive Neuroscience: Toward Strong Inference in Attributing Function to Structure, 51 Am. Psychologist 13, 13-21 (1996)CrossRefGoogle Scholar (discussing the on-going debate of the localization of cognitive functions).

40 Cacioppo et al., supra 31, at 654.

41 For a detailed discussion of localization, see Sarter et al., supra note 39, at 13-21.

42 Formisano, Elia & Goebel, Rainer, Tracking Cognitive Processes with Functional MRI Mental Chronometry, 13 Current Opinions Neurobiology 174, 174 (2003).CrossRefGoogle ScholarPubMed

43 See Nofzinger, Eric A. et al., Human Regional Cerebral Glucose Metabolism During Non-Rapid Eye Movement Sleep in Relation to Waking, 125 Brain 1105, 1105-1115 (2002)CrossRefGoogle ScholarPubMed (discussing temporal resolution differences in using PET compared to using CBF methods).

44 Formisano & Goebel, supra note 41, at 175.

45 Id. at 174.

46 See Scott A. Huettel et al., Functional Magnetic Resonance Imaging (2004).

47 Manns, John R. et al., Recognition Memory and the Human Hippocampus, 27 Neuron 171 (2003).CrossRefGoogle Scholar

48 It is estimated that there are over three times as many MRI sites than PET facilities in the U.S. For a more detailed discussion, see Brown & Eyler, supra note 12, at 53. Also, for a detailed examination of the use of fMRI in the legal system, see Thompson, Sean Kevin, Note: The Legality of the Use of Psychiatric Neuroimaging in Intelligence Interrogation, 90 Cornell L. Rev. 1601 (2005).Google Scholar

49 It has also been posited that fMRI has an advantage over PET in that it has higher sensitivity, thereby allowing for activation to be detected in individual subjects. See Machielsen, Willem C. M. et al., fMRI of Visual Encoding: Reproducibility of Activation, 9 Hum. Brain Mapping 156, 156-164 (2000).3.0.CO;2-Q>CrossRefGoogle Scholar

50 Matthews, Paul M. & Jezzard, Peter, Functional Magnetic Resonance Imaging, 75 J. Neurology, Neurosurgery, & Psychiatry 6, 6-12 (2004).Google ScholarPubMed Activation has been defined as a region showing statistically significant changes in BOLD signal. See Tjandra, Teddy et al., Quantitative Assessment of the Reproducibility of Functional Activation Measured with BOLD and MR Perfusion Imaging: Implications for Clinical Trial Design, 27 Neuroimage 393, 393-401 (2005).CrossRefGoogle Scholar

51 See Brown & Eyler, supra note 12, at 55.

52 Logothetis, Nikos K. & Pfeuffer, Josef, On the Nature of the BOLD fMRI Contrast Mechanism, 22 Magnetic Resonance Imaging 1517, 1524 (2004).CrossRefGoogle ScholarPubMed

53 Matthews et al., supra note 22, at 733 box 1.

54 Matthews and Jezzard, supra note 50, at 6-12; see also Brown & Eyler, supra note 12, at 55.

55 Brown & Eyler, supra note 12, at 55. Alternatives to the use of BOLD as a marker for neural activation exist for more direct Cerebral Blood Flow measurements using MRI. One method involves the use of arterial spin labeling (ASL) perfusion imaging. See Wang, Yihong et al., Simultaneous MRI Acquisition of Blood Volume, Blood Flow and Blood Oxygenation Information During Brain Activation, 52 Magnetic Resonance Med. 1407, 1407-1417 (2004).Google Scholar This technique is believed to provide greater sensitivity than BOLD, especially for tasks involving low-frequency. Id. It has also been shown to have lower inter-subject variability. Wang, Jiongjiong et al., Arterial Spin Labeling Perfusion fMRI with Very Low Task Frequency, 49 Magnetic Resonance Med. 796, 796-802 (2003)CrossRefGoogle ScholarPubMed; see also Tjandra, supra note 50, at 394.

56 Matthews et al., supra note 22, at 733.

57 Id.

58 Id.

59 Id.

60 Id.

61 Brown & Eyler, supra note 12, at 52.

62 Id.

63 Id.

64 For a discussion of the use of PET in the studies of monoamine oxidase (MAO), an important enzyme for regulating neurotransmitters such as dopamine, norepinephrine and serotonin, see Fowler, Joanna S. et al., Translational Neuroimaging: Positron Emission Tomography Studies of Monoamine Oxidase, 7 Molecular Imaging & Biology 377 (2005).CrossRefGoogle ScholarPubMed

65 Tomasi, Dardo et al., fMRI-Acoustic Noise Alters Brain Activation During Working Memory Tasks, 27 NeuroImage 377, 377 (2005).CrossRefGoogle ScholarPubMed

66 Brown & Eyler, supra note 12, at 56-57. This problem may become resolved in part with increasingly powerful Tesla magnets.

67 Jezzard, Peter & Clare, Stuart, Sources of Distortion in Functional MRI Data, 8 Human Brain Mapping 80, 80 (1999).3.0.CO;2-C>CrossRefGoogle ScholarPubMed

68 Id.

69 Id.

70 Id.

71 Id. at 80-81.

72 Id. at 81.

73 Id. at 81-82.

74 Signal Dropout occurs secondary to the differential magnetizability of the physiological compartments of the head. Boundaries involving air and tissue are particularly important as locations for magnetic field gradients that may offset precessing and diphase spin. The result is diminishing of the MR signal causing “dropout.” For a detailed discussion of this problem, see Brown & Eyler, supra note 12, at 57.

75 Distortions are also brought about by the effects of technical issues like gradient coil nonlinearities. The shape of images is affected by being selected over a curved rather than rectilinear surface. Added to this are the distortions brought about by so-called Nyquist ghost artifact seen with echo planar imaging. This apparently is due to differences between the echoes obtained from read-out gradients that are positive and negative. Again, methods exist to correct the ghosting effect. For a detailed discussion, see Jessard & Clare, supra note 67, at 84-85; see also Jovicich, Jorge et al., Biomedical Information Research Network: Characterization and Correction of Image Distortions in Multi-Site Structural MRI, 19 NeuroImage (Supp. Issue) 1666, 1666-7 (2003).Google Scholar

76 Jezzard & Clare, supra 67 at 83-84.

77 Brown & Eyler, supra note 12, at 56.

78 Id.

79 Id.

80 Id.

81 Id. (citing R.B. Buxton, Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques (Cambridge Univ. Press 2002)).

82 Tjandra et al., supra note 50, at 393.

83 See id. at 393-395 for a more detailed discussion of the impact of BOLD on signal location.

84 Id. at 393-394.

85 Id. at 393.

86 Id.

87 See, e.g., Murphy, Kevin et al., A Validation of Event-Related fMRI Comparisons Between Users of Cocaine, Nicotine, or Cannabis and Control Subjects, 163 Am. J. Psychiatry 1245 (2006).CrossRefGoogle ScholarPubMed

88 Tjandra et al., supra note 50, at 393.

89 See Murphy et al., supra note 87, at 1246.

90 See Wikipedia, Functional Magnetic Resonance Imaging, http://en.wikipedia.org/wiki/functional_magnetic_resonance_imaging (last visited Mar. 2, 2007).

91 Certainly whole-brain images provide a broader base for looking at the neural mechanisms underlying social, emotional and cognitive information processing, though the difficulty rests in the temporal relationships among parts of the brain impacted by a thought or an emotion. See Norris, Catherine J. et al., The Interaction of Social and Emotional Processes in the Brain, 16 J. Cognitive Neuroscience 1818 (2004).CrossRefGoogle Scholar

92 E-mail Dr. Bruce Rosen, Faculty Member, Harvard Medical School and Massachusetts General Hospital (October 4, 2006) (on file with author) (regarding the dearth of good research on issues of reliability and reproducibility of fMRI). Rosen emphasized that the BIRN project is making strides in this direction, but that there is a need for much more research on these sets of issues. Id.

93 For a discussion of inter-session variability, which according to the researchers is in fact not high, see Smith, Stephen M. et al., Variability in fMRI: A Re-Examination of Inter-Session Differences, 24 Hum. Brain Mapping 248 (2005).CrossRefGoogle ScholarPubMed

94 See Friedman, Lee et al., Reducing Inter-Scanner Variability of Activation in a Multi-Center fMRI Study: Role of Smoothness Equalization, 32 NeuroImage 1656, 1656-57 (2006).CrossRefGoogle Scholar See generally Leontiev, Oleg & Buxton, Richard B., Reproducibility of BOLD, Perfusion, and CMRO2 Measurements with Calibrated-BOLD fMRI, 35 NeuroImage 175 (2007).CrossRefGoogle ScholarPubMed

95 See Friedman, supra note 94, at 1657.

96 See id. at 1656.

97 See id. at 1657, 1664.

98 See Jorge Jovicich et al., Test-Retest Reliability Assessment for Longitudinal MRI Studies: An Intensity-Based Comparison of T1-Weighted Protocols and Field Strengths, 11th Annual Meeting of the Organization for Human Brain Mapping (2005), available at http://legacy-web.nbirn.net/Publications_rd/Presentations/OHBM_2005_Pfz_intens_final.pdf; Brian Quinn et al., Test-Retest Reliabity Assessment for Longitudinal MRI Studies: A comparison of the Effects of Different T1-Weighted Protocols, Scanner Platforms, and Field Strengths on Semi-Automated Hippocampal Volume Measures, 11th Annual Meeting of the Organization for Human Brain Mapping (2005), available at http://legacy-web.nbirn.net/Publications_rd/Presentations/OHBM_2005_Pfz_morph_final.pdf; Jorge Jovicich et al., Reliability in Multi-site Structural MRI Studies: Effects of Gradient Non-Linearity Correction on Volume and Displacement of Brain Subcortical Structures, 10th Annual Meeting of the Organization for Human Brain Mapping (2004), available at http://www.nbirn.net/publications/abstracts/pdf/Jovicich_HBM_2004.pdf.

99 Jovicich, Jorge et al., Reliability in Multi-Site Structural MRI Studies: Effects of Gradient Non-Linearity Correction on Phantom and Human Data, 30 NeuroImage 436, 436 (2006).CrossRefGoogle ScholarPubMed

100 See, e.g., Zou, Kelly H. et al., Reproducibility of Functional MR Imaging: Preliminary Results of Prospective Multi-institutional Study Performed by Biomedical Informatics Research Network, 237 Radiology 781, 785 (2005).CrossRefGoogle ScholarPubMed

101 Id. at 782.

102 Id.

103 Id.

104 Id.

105 Id.

106 Id. at 785.

107 Machielsen et al., supra note 49, at 156.

108 Studies 1 and 2 involved the same scanning session followed by a third session several days later. Id. at 157.

109 Id. at 159.

110 Id. at 163.

111 Id. at 164.

112 Fernandez, G. et al., Intrasubject Reproducibility of Presurgical Language Lateralization and Mapping Using fMRI, 60 Neurology 969, 969 (2003).CrossRefGoogle ScholarPubMed

113 Id.

114 Id.

115 Id. at 969-970.

116 Id. at 969.

117 Id.

118 Fernandez et al., supra note 112, at 970.

119 Id. at 970.

120 Id.

121 Id. at 974.

122 Id.

123 Id. at 973.

124 See Rutten, G.J.M. et al., Reproducibility of fMRI-Determined Language Lateralization in Individual Subjects, 80 Brain & Language 421, 431 (2002).CrossRefGoogle ScholarPubMed

125 Id. at 423-24.

126 See id. at 431.

127 Aron, Adam R. et al., Long-term Test-Retest Reliability of Functional MRI in a Classification Learning Task, 29 NeuroImage 1000 (2006).CrossRefGoogle Scholar

128 Id. at 1001-02.

129 Id. at 1004-05.

130 See Detre, supra note 27, at 812-813.

131 Id. at 812.

132 Killgore, William D.S. et al., Functional MRI and the Wada Test Provide Complementary Information for Predicting Post-Operative Seizure Control, 8 Seizure 450, 450 (1999)CrossRefGoogle ScholarPubMed; see also Sabsevitz, D.S. et al., Use of Preoperative Functional Neuroimaging to Predict Language Deficits from Epilepsy Surgery, 60 Neurology 1788 (2003).CrossRefGoogle ScholarPubMed

133 Id. at 450-51.

134 Id. at 451-53.

135 Id. at 453-454; see also Adcock, Jane E. et al., Quantitative fMRI Assessment of the Differences in Lateralization of Language-Related Brain Activation in Patients with Temporal Lobe Epilepsy, 18 NeuroImage, 423, 436 (2003)CrossRefGoogle ScholarPubMed (showing the importance of fMRI in determining language lateralization to minimize morbidity in the surgical treatment of temporal lobe epilepsy). Researchers concluded that non-invasive fMRI is a practical and reliable alternative to more invasive testing for language lateralization. Id. at 436. Following along the same line of research, see Sabbah, Patrick et al., Functional MR Imaging in Assessment of Language Dominance in Epileptic Patients, 18 NeuroImage 460 (2003)CrossRefGoogle ScholarPubMed and Woermann, Frederick G. et al., Language Lateralization by Wada Test and fMRI in 100 Patients with Epilepsy, 61 Neurology 699 (2003)CrossRefGoogle ScholarPubMed (finding in 100 patients that there was overall a 91 % concordance between fMRI and the Wada Test for determining language lateralization. Rate of false categorization was 9% with fMRI, ranging from 3% in the case of left sided temporal lobe epilepsy to as high as 25% in the case of left-sided “extratemporal” epilepsy).

136 Yetkin, F. Zerrin et al., Functional MR Activation Correlated With Intraoperative Cortical Mapping, 18 Am. J. Neuroradiology 1311, 1311-12 (1997).Google ScholarPubMed

137 Id. at 1312.

138 Id. at 1313-14.

139 Id. at 1312.

140 Id.

141 Id. at 1313-1315 (finding, of the forty-six functions studied, 100% correlated between the two methods within twenty millimeters and an 86% correlation within 10 millimeters).

142 Rabin, Marcie L. et al., Functional MRI Predicts Post-Surgical Memory Following Temporal Lobectomy, 127 Brain 2286, 2294-97 (2004).CrossRefGoogle ScholarPubMed

143 Id. at 2287.

144 Id. at 2286.

145 Id. at 2288.

146 Id. at 2289.

147 Id.

148 Id. at 2293.

149 Id. at 2297.

150 Constable, R. Todd et al., Investigation of the Human Hippocampal Formation Using a Randomized Event-Related Paradigm and Z-Shimmed Functional MRI, 12 NeuroImage 55, 55 (2000).CrossRefGoogle ScholarPubMed

151 Id. at 61.

152 Moradi, et al., Consistent and Precise Localization of Brain Activity in Human Primary Visual Cortex by MEG and fMRI, 18 NeuroImage 595, 595 (2003).CrossRefGoogle ScholarPubMed

153 Id.

154 Id. at 607-08.

155 Kober, Helmut et al., Correlation of Sensorimotor Activation with Functional Magnetic Resonance Imaging and Magnetoencephalography in Presugical Functional Imaging: A Spatial Analysis, 14 NeuroImage 1214, 1217-18 (2001).CrossRefGoogle ScholarPubMed

156 Id. at 1214.

157 Id.

158 Id.

159 ASL uses magnetically-labeled arterial blood water as a flow tracer. Detre, supra note 27, at 812; see also Feng, Ching-Mei et al., CBF Changes During Brain Activation: fMRI vs. PET, 22 NeuroImage 443, 443-44 (2004).CrossRefGoogle ScholarPubMed

160 This hypothetical is based on United States v. Eduardo Sandoval-Mendoza, a case decided by the Ninth Circuit on December 27, 2006. 472 F.3d 645 (9th Cir. 2006). In this case, a fMRI was not done for lie detection, but a structural MRI did reveal the presence of a large pituitary tumor. Id. at 653. The district court in this case found the medical expert opinion unreliable as it did not scientifically establish that the brain tumor caused the mental incompetency alleged. Id. at 652-55.

161 Reeves, supra note 3, at 90. Authors of this piece focus primarily on PET and SPECT, but there are similarities in the determination of abnormality with fMRI. See id.

162 See Brodie, supra note 6, at 145-46. Brodie stresses that images and their statistical representations of activations reflect complex assumptions and mathematical manipulations of data, all of which compromise the validity of the conclusions that are drawn by the researchers. Id.

163 Joseph Dumit, Picturing Personhood: Brain Scans and Biomedical Identity 8-9, 16-18 (2004).

164 Id. at 16-18.

165 Id. at 8-9.

166 Id. at 8.

167 Reeves, supra note 3, at 90.

168 See Dorothy Nelkin & Laurence Tancredi, Dangerous Diagnostics: The Social Power of Biological Information 37-50 (1994).

169 See id.

170 To begin with, functional neuroimages are generally not stable. They may change over time, reflective of improvement of blood flow or even the positive benefits of neuroplasticity.

171 See infra notes 172-173 and accompanying text.

172 The connectivity through complex neural networks can be studied with Diffusion Tensor Imaging. Mori, Susumu & Zhang, Jiangyang, Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research, 51 Neuron 527, 527 (2006).CrossRefGoogle ScholarPubMed

173 For an interesting article on brain imaging relevant to criminal responsibility, see Redding, Richard E., The Brain-Disordered Defendant: Neuroscience and Legal Insanity in the Twenty-First Century, 56 Am. U. L. Rev. 51 (2006).Google ScholarPubMed

174 See Rothschild, D. & Sharp, M. L., The Origin of Senile Psychosis: Neuropathic Factors and Factors of a More Personal Nature, 2 Diseases Nervous Sys. 49 (1941).Google Scholar

175 Id.

176 Id.

177 Robbins, Lee N., Epidemiology: Reflections on Testing the Validity of Psychiatric Interviews, 42 Archives Gen. Psychiatry 918, 918-20 (1985).CrossRefGoogle Scholar

178 Reeves, supra note 3, at 93-94.

179 Id. at 94.

180 See id.

181 See id. at 90.

182 See id. at 90-91.

183 See People v. Smith, 107 P. 3d 229, 234 (Cal. 2005) (where Dr. Buchsbaum testified that the PET scan showed brain damage to defendant); People v. Kraft, 5 P.3d 68, 98 (Cal. 2000) (where Dr. Buchsbaum testified that the PET scan showed a previous head injury consistent with obsessive compulsive disorder as part of a defensive strategy to show that the defendant would not cause problems in prison and that the death penalty would not be necessary); People v. Holt, 937 P.2d 213, 231 (Cal. 1997) (where Dr. Buchsbaum testified that PET Scan showed abnormalities of defendant's frontal and temporal lobes and claimed this revealed “emotional system damage”); see also People v. Protsman, 105 Cal. Rptr. 2d 819, 823-24 (Cal. Ct. App. Mar. 13, 2001) (upholding trial court's exclusion of PET scan evidence of brain damage).

184 Interview with Dr. Michael Hutchinson, Department of Neurology, New York University School of Medicine (July 20, 2006). Dr. Hutchinson discussed MRI and fMRI in injury cases, in which he testified as an expert. Id. He sees a growing role of fMRI in both civil and criminal cases. Id.; see People v. Combs, 101 P. 3d. 1007 (Cal. 2004) (upholding trial court finding of first degree murder and the death penalty where the defense hired an expert who did an EEG and MRI and claimed that the scan demonstrated brain lesions consistent with organic brain syndrome). Thus far, there are too many inconsistencies in the use of fMRI, certainly for relating structure to behavior. C.f. Mayberg, Helen S., Functional Brain Scans as Evidence in Criminal Court: An Argument for Caution, 33 J. Nuclear Med. 18n, 25n (1992)Google ScholarPubMed (arguing that the sensitivity and specificity of patterns from PET and SPECT are still too ambiguous for these technologies to be useful in the courtroom).

185 For a discussion of the legal implications of lie detection, see Keckler, Charles N. W., Cross-Examining the Brain: A Legal Analysis of Neural Imaging for Credibility Impeachment, 57 Hastings L.J. 509 (2006)Google Scholar (discussing the legal implication of using MRI for lie detection). See also Thompson, supra note 48, at 1601 (discussing the legality of using neuroimaging in interrogation).

186 Langleben, Daniel D. et al., Brain Activity During Stimulated Deception: An Event-Related Functional Magnetic Resonance Study, 15 NeuroImage 727 (2002).CrossRefGoogle Scholar

187 Id. at 727.

188 Id. at 731.

189 See Davatzikos, C. et al., Classifying Spatial Patterns of Brain Activity with Machine Learning Methods: Application to Lie Detection, 28 NeuroImage 663, 663 (2005)CrossRefGoogle ScholarPubMed (99% accurate discrimination was obtained for 22 of the subject but “predictive accuracy … was 88%”); Langleben, Daniel D. et al., Telling Truth from Lie in Individual Subjects with Fast Event-Related fMRI, 26 Human Brain Mapping 262, 262 (2005).CrossRefGoogle ScholarPubMed

190 See Phan, K. Luan et al, Neural Correlates of Telling Lies: a Functional Magnetic Resonance Imaging Study at 4 Tesla, 12 Academic Radiology 164-72 (2005).CrossRefGoogle ScholarPubMed See also Kozel, F. Andrew et al., Detecting Deception Using Functional Magnetic Resonance Imaging, 58 Biological Psychiatry 605, 610 (2005).CrossRefGoogle ScholarPubMed

191 Friedman et al., supra note 94, at 1656 (discussing an attempt to standardize fMRI scanning).

192 See Entertainment Software Ass’n v. Granholm, 404 F. Supp. 2d 978, 982 (2005) (where fMRI research was used to allege that medial violence exposure may be associated with alterations in brain functioning).

193 See Roper v. Simmons, 543 U.S. 551 (2005); Brief for the Am. Psychological Ass’n and the Mo. Psychological Ass’n as Amici Curiae Supporting Respondent at 11, Roper v. Simmons, 543 U.S. 551 (2005) (No. 03-633), 2004 WL 1636447.

194 Id.

195 Giedd, Jay, Brain Development, IX: Human Brain Growth, 156 Am. J. Psychiatry 4 (1999).CrossRefGoogle ScholarPubMed See also Giedd, Jay N. et al., Brain Development During Childhood and Adolescence: A Longitudinal MRI Study, 2 Nature Neuroscience 861, 861-862 (1999).CrossRefGoogle ScholarPubMed

196 See Brief for the Am. Psychological Ass’n and the Mo. Psychological Ass’n, supra note 193, at 2.

197 See supra notes 42-47, 131, 152-159 and accompanying text.

198 See supra notes 15-64 and accompanying text; see also Chorvat, Terrence et al., Law and Neuroeconomics, 13 Sup. Ct. Econ. Rev. 35, 45-46 (2005).Google Scholar

199 See Linda H. Lamb, New MRI has Enormous Potential: Rare Machine's Brain-Imaging Tests Can Find Clues on Stroke, State (Columbia, S.C.), April 6, 2006 at B1 (discussing the use of 3-tesla MRI).

200 Karen Sandrick, 3–Tesla MRI Bests 1.5–Tesla in Body and Brain, Advanced MR (Special Supplement to Diagnosticimaging), Dec. 2001, available at http://www.diagnosticimaging.com/advancedMR/3tmri.jhtml.

201 Id.

202 Id.

203 Id.

204 Id.

205 Id.

206 See id.

207 Stephan E. Maier et al., Diffusion MRI Explores New Indications, Advanced MR (Special Supplement to Diagnosticimaging), Dec. 2001, http://www.diagnosticimaging.com/advancedMR/diffusion.jhtml.

208 Sandrick, supra note 200.

209 See supra notes 185-188 and accompanying text.

210 See generally Keckler, supra note 185 (discussing various lie-detection methods); see also Bush, John C., Warping the Rules: How Some Courts Misapply Generic Evidentiary Rues to Exclude Polygraph Evidence, 59 Vand. L. Rev. 539 (2006)Google Scholar (discussing polygraph limitations).

211 See Laurence Tancredi, Neuroscience and the Law, in Neuroscience and the Law 193 (Brent Garland ed., 2004).

212 See id.

213 National Library of Medicine (U.S.), MedlinePlus Medical Enclyclopedia, MRI, http://www.nlm.nih.gov/medlineplus/print/ency/article/003335.htm (last visited May 22, 2007).

214 There needs to be more research into the variables that may alter the image over time. As pointed out earlier, these images are not free of environmental and other influences. In part this is good because it means we have a way of studying the impact of external influences on the brain as reflected in the images. On the other hand, the lack of stability of the image may cause us to doubt the validity of diagnoses based in part on these images.