Ethics, Genetics, and Autism: A Conversation with Dr. Joseph Cubells

Dr. Joseph Cubells

Dr. Joseph Cubells is an Emory psychiatrist who focuses on working with adults with developmental and behavioral disorders, especially Autism Spectrum Disorders (ASD). He is on the cutting edge of using molecular genetics to identify genetic anomalies in his patients with the aim of improving and refining treatment packages. I spoke with Dr. Cubells about his work and the ethical implications of the use of genetic microarray tests with patients. After providing more details about how he uses molecular genetics in his practice, I will focus on our discussion of two primary issues related to his work: (1) the communication of genetic testing procedures and results to families and, (2) the role of health care systems in the widespread use of these tests. 

Dr. Cubells is primarily engaged in clinic work. He has over 200 cases and works exclusively with adults (he does not see patients under the age of 16). Molecular genetics is one technique used in his patient management strategies: “I am very interested in the role of molecular genetic testing in the care of people with neurodevelopmental disabilities. Not so much establishing a diagnosis of autism though because autism is a behavioral diagnosis.” In other words, because there is no genetic or otherwise biologically based test currently available for autism, Dr. Cubells and his team are interested in diagnosing other genetic differences, such as Phelan McDermid Syndrome which occurs when a chromosome is deleted after conception (de novo) and can lead to a variety of physical and developmental disabilities. This condition, and many other genetic anomalies, may contribute or directly lead to the development of autistic characteristics. Most professionals, including myself and Dr. Cubells, now agree that there is not a single ‘autism’ but, rather, many different ‘autisms’ with many different causal pathways, both genetic and environmental.

Last November, Dr. Cubells and his team presented a paper on their use of molecular genetics in direct patient care at the American Society for Human Genetics. They sent chromosomal microarray tests¹ to be analyzed for 44 of their patients. Seven of these tests “came back with definitely clinically relevant differences that had not been previously diagnosed.” This is a rate of 16%, which, for Dr. Cubells, is “a substantial and important rate.” This rate may seem small but the impact of these findings are critical. For example, among those seven, one adult male’s test showed a deletion of the monoamine oxidase (MAO) A and B gene. This effects of this deletion are similar to the effects of taking a MAO inhibitor (MAOI), a type of pharmacological treatment for depression. Both this medication and this genetic deletion can lead to a fatal hypertensive crises if a person consumes tyramine (found in many aged or fermented foods, foods high in protein, and some alcoholic beverages) or in the presence of sympathomimetic drugs, which mimic transmitters such as catecholamines (i.e., epinephrine, norepinephrine, and dopamine). Because this genetic deletion was identified, the patient now wears a medic alert bracelet stating that he must be treated as a patient on a MAOI to avoid unexpected drug reactions. This knowledge is potentially life-saving.

These microarray genetic analyses can help refine patient management; however, the actual purpose and results of tests are difficult to accurately communicate to families. Dr. Cubells related another story of an adult who has significant autistic characteristics for whom his team identified another type of anomaly: a 15q13.3 deletion for which a small part chromosome 15 is deleted in each cell. They discovered that this participant’s mother has the same deletion, however, unlike her son, does not show any of the developmental delays. The man’s grandmother, however, also has the deletion and exhibits some developmental delays. This patient’s cousin is recently married and is wondering if he should be tested for this deletion. I asked Dr. Cubells what, in cases like this, a genetic counselor or clinician is ethically responsible to communicate to families regarding the implications of obtaining the tests and the implications of the results. This issue is an important concern for eventual pre-natal diagnoses of autism as well as for the project I am working on as the current Neuroethics Program Scholar, which involves considering the implications of using eye-tracking technologies for early, presymptomatic screening of ASD.

The gene copy number (also "copy number variants" or CNVs) is the number of copies of a particular gene in the genotype of an individual.

Dr. Cubells responded that “the first thing you have to make clear is there is a lot of uncertainty.” For cases like the one described above, he would start by explaining that the test will only tell him whether he carries the deletion. If he does not, then there is an “infinitesimally small” likelihood that his future children would have that deletion. However, if he does carry the deletion, things are a much more complicated. There is a big chance that this gentleman’s children would have learning or developmental difficulties, however, as the patient’s mom exemplified, there could also be no discernible influence. “And so the range of possibilities ranges from very challenging to fine.” Regardless, at this stage, Dr. Cubells believe that with this particular chromosomal variation, or copy-number variant (CNV), there are “reasonable odds” that there will be challenges but the field is not ready to be quantitative about it. This is the kind of information, he says, of which genetic counselors must be aware.

There are significant differences in the understanding of risk between the lay public and professionals.² Explaining probabilities to patients or families is difficult, but Dr. Cubells urges that the physician’s role is “to be helpful when he can and to give them [the family and patient] as much information as he can to explain things.” This information should include an explanation of the meaning and difference of variable penetrance and variable expressivity. The former is the proportion of people who carry a particular gene that also expresses and particular trait, or phenotype. The latter describes the differences within this expression, or the ranges of phenotypes linked to a particular gene or genetic anomaly. This information is often confusing for patients and families to understand. It is critical that patients understand these terms in order to  consent to taking part in a microarray test and for comprehending the consequences of test results. Given that the responsibility of making decisions lies with the patient and family, this information needs to be communicated clearly and reliably.

We also discussed issues related to the cost of these genetic arrays and resource allocation. Dr. Cubells explained that genomic micro-arrays cost, at a minimum, around $800. If the company wants to stay in business and possibly make a profit, then they need to charge around $1400. He admits that this amount of money can be also used towards valuable and efficacious behavioral or psychological treatment. And so where should we put our resources? He admits that, despite the obvious benefits of the work he is doing, he is “ambivalent about pushing the importance of genetics in autism because [he] spends a lot of time explaining what ought to happen but the resources aren’t there.” This is a large debate in the field. Many self-advocates and family members struggle, knowing that there is a lack of funding for research on quality of life issues and services, especially for adults who lose a host of services, such as instruction on daily living skills as well as occupational and speech therapies, once they age out of the public school system at the age of 21.³

“But on the other hand,” Dr. Cubells explains, “we do need to understand things at the level of etiology. We need to know if a person has Phelan McDermott versus 15q versus 22q11⁴ because even now there are clinical implications for that.” Dr. Cubells sees a problem in the lack of reimbursement for genetic counselors who see patients with psychiatric problems; insurance companies do not have to pay for this kind of consultation. He says this situation needs to change, but the only way this change will happen is for politicians and professionals to work towards changing the minds of insurance and health care administrators. 

Cost is a real barrier to access to emerging medical technologies like this for many families. This means that critical information will potentially not be available to many patients unless these tests become a mandated part of health care coverage. It is also possible that tests like these will become part of standard pre-natal check-ups, in which case a host of other ethical concerns arise. Disability activists, especially those adherent to neurodiversity, see pre-natal diagnostics of disabilities as an attempt to eradicate disability and difference from the human population—a eugenic enterprise. Additionally, as was discussed in my last post, cultural and faith-based backgrounds of families may mean less acceptance of the use of these technologies. Families may rely on more spiritually-based explanations of disabilities and so may not be open to discussions of genetic causes, which can be seen as more chronic and stigmatizing. Finally, for many of the genetic anomalies identifiable by these tests, no reliable treatments are available. There are educational and behavioral therapies for autism and related disorders; however, there is no guarantee that any intervention will dramatically change behavior or if, given the variability of autistic manifestation, any intervention will even be necessary! These issues will be discussed more fully in my next blog post, where I describe the impact of the use of eye tracking technologies to identify autistic markers in infancy. 

This discussion reminded me of a recent op-ed in the New York Times in which the columnist, Nicholas Kristof, called for more attention in the media and government on mental health. We may be working in the right direction as the Affordable Care Act does include mental health care, but costs remain high and the consequences of these costs are having real effects on real lives. Bringing the impact of psychiatric, intellectual, and developmental disorders has on the quality of life of diagnosed individuals and their families into the public realm is imperative to obtaining more funding for services and more research on how to develop, implement, and distribute these services most effectively. As genetic testing and prescreening for psychiatric conditions continues to become more advanced, I agree with Mr. Kristof and Dr. Cubells. Improving coverage for psychiatric services should be a high priority issue for politicians, health care administrators, scientists, physicians, and, most importantly, families.

Dr. Joseph Cubells is a psychiatrist whose clinical and research interests lay in molecular genetic factors of developmental and behavior disorders, such as autism, schizophrenia, and major depression. He is the Medical Director and Attending Psychiatrist at the Emory Autism Center where he work with adults on the autism spectrum and with genetic and chromosomal disorders that lead to various psychiatric disorders.

References

1. A chromosomal microarray test is a new method of detecting alterations in a person’s DNA. Specifically, these tests look for areas on the DNA with too many or too few copies of genetic material. This method is more specific than earlier genetic tests, thereby allow for more exact maps of the DNA and, ostensibly, the ability to identify more anomalies. For more information, see The American College of Obstetricians and Gynecologists’ Committee Opinion on the use of this test in prenatal diagnosis here: http://www.acog.org/Resources_And_Publications/Committee_Opinions/Committee_on_Genetics/The_Use_of_Chromosomal_Microarray_Analysis_in_Prenatal_Diagnosis.


2. For example, see: Hamepl, J. (2006). Different concepts of risk - A challenge for risk communication. International Journal of Medical Microbiology, 296(S1): 5-10; Miller, A.M, Hayeems, R.Z, & Bytautas, J.P. (2010). What is a meaningful result? Disclosing the results of genomic research in autism to research participants. European Journal of Human Genetics, 18: 867-871; McMahon, W.M., Baty, B.J., & Botkin, J. (2006). Genetic counseling and ethical issues for autism.  American Journal of Medical Genetics Part C (Semin. Med. Genet.), 142C: 52-57; Slovic, R. (1987). Perception of Risk. Scienze, 236(4799): 280-285.


3. For more explanation of this perspective, see this report by the Autistic Self Advocacy Network (ASAN), “ASAN expresses concern regarding new HHS report on autism research” at http://autisticadvocacy.org/2012/07/asan-expresses-concern-regarding-new-hhs-report-on-autism-research/.


4. These are all genetic disorders associated with autistic phenotypes. Phelan-McDermid is “the result of a disruption of the SHANK3/ProSAP2 gene on the terminal end of chromosomee 22,” according to the website for the Phelan-McDermid Syndrome Foundation (www.22q13.org). 15q  and 22q11 refers to partial deletions of chromosomes 12 and 22 that leads to a variety of developmental disorders.

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Sarrett, J. (2014). Ethics, Genetics, and Autism: A Conversation with Dr. Joseph Cubells. The Neuroethics Blog. Retrieved on , from http://www.theneuroethicsblog.com/2014/04/ethics-genetics-and-autism-conversation.html

Intelligence Testing: Accurate or Extremely Biased?

By Emily Young



In the early 1900s, psychologist Charles Spearman noticed that children who did well in one subject in school were likely to do well in other subjects as well, and those who did poorly in one subject were likely to do poorly across all subjects. He concluded that there is a factor, g, which correlates with testing performance (Spearman 1904). The g factor is defined as the measure of the variance of testing performance between individuals and is sometimes called “general intelligence”.



Later on, psychologist Raymond Cattell determined that there are two subsets of g, called fluid intelligence (denoted Gf) and crystallized intelligence (denoted Gc). Fluid intelligence is defined as abstract reasoning or logic; it is an individual’s ability to solve a novel problem or puzzle. Crystalized intelligence is more knowledge based, and is defined as the ability to use one’s learned skills, knowledge, and experience (Cattell 1987). It is important to note that while crystallized intelligence relies on knowledge, it is not a measure of knowledge but rather a measure of the ability to use one’s knowledge.



The first standardized intelligence test was created in 1905 by French Psychologist Albert Binet, as a method to screen for mental retardation in French schoolboys. The test measured intelligence by comparing an individual’s score to the average score of children his own age (Binet 1905). The test was later revised by Lewis Terman of Stanford University and named the Stanford-Binet Intelligence Scales. The Stanford-Binet is now in its fifth edition and includes five sections: fluid reasoning, knowledge, quantitative reasoning, visual-spatial processing, and working memory.



Since the Stanford-Binet, many other standardized intelligence scales have been developed. One of the most popular modern intelligence tests is the Raven’s Progressive Matrices (RPM) test (Raven, 2003). The test gives individuals a series of boxes, each containing shapes that change from box to box, and a box that is empty. The test taker must recognize the pattern that is shown and correctly identify the shape that should go in the empty box from a collection of options. Unlike the Stanford-Binet, RPM is entirely visual; the test taker does not have to answer written questions, meaning the measured IQ is not dependent on reading comprehension. This allows for better testing that eliminates variables such as native language, age, and possible reading disability.

A general example of the questions on the Raven’s Progessive Matrices test.

So what exactly are these IQ tests measuring? The Stanford-Binet measures g through tasks that measure both Gf and Gc. Because RPM is entirely non-verbal and puzzle based, it almost exclusively measures Gf.



Which brings us to the next question; are these tests effectively measuring g?



Since their creation, modern Western intelligence testing has shown a difference in average intelligence, varying from group to group; whites score higher than blacks, the rich score higher than the poor. In some tests, women and men score differently from task to task. Are these differences due to heritable differences in intelligence between race, gender, and socioeconomic status? Or are environment, schooling, and stigma to blame? Or, are the tests themselves flawed?



While intelligence tests claim to be culture-fair, none of the tests created so far are one hundred percent unbiased. As Serpell (1979) found, when asked to reproduce figures from using wire, pencil and paper, and clay, Zambian children performed better in the wire task, while English children performed better in the pencil and paper task. Each group did better in the medium to which they were more accustomed. Pencil and paper IQ tests may be intrinsically biased towards Western culture.



Furthermore, while African-Americans have historically scored lower than white Americans on intelligence testing, this gap as been lessening in recent years (Dickens and Flynn 2006). This could be the result of one of two things; the first possibility is that average intelligence is increasing in the black community at a higher rate than in the white community (measured intelligence has been steadily increasing across all groups due to the Flynn effect). However, it seems more likely that post-segregation, white and black cultures have been merging, and schools have been integrated, meaning that white and black children have a better chance of receiving the same education. If this is the case, IQ tests are either measuring knowledge more than the test creators think they do, or the tests are extremely culturally biased, but this bias is lessening due to assimilation of white and black culture in America.



Not only are intelligence tests culturally biased, but they also seem to be biased in favor of neurotypical individuals. For example, while typically developing individuals generally perform similarly on RPM and the Wechsler Adult Intelligence Scale (WAIS), individuals with Autism typically score higher on RPM than on WAIS (Bolte et al. 2009, Mottron 2004). This is because while RPM is a visual task, WAIS is almost entirely verbal. Individuals with autism seem to use visual strategies to solve tasks and therefore have difficulty on tasks that can only be solved verbally (Kunda and Goel 2010). While this phenomenon is typically seen as a cognitive deficit, it is important to note that autistic individuals outperform neurotypical individuals on some visual tasks.



Therefore, by only measuring one specific part of intelligence, some IQ tests portray autistic individuals as having a cognitive deficit. What if some disorders, such as autism, are not actually disorders, but simply a way of thinking that differs from what is considered “normal”?



For example, Dr. Temple Grandin, an autistic woman with a PhD in Animal Sciences, uses her incredible visual working memory to design cattle equipment that is much more humane and far less anxiety-inducing than previous models. Grandin says her autism allows her to see the world in pictures; her inner thoughts are entirely devoid of language, she simply thinks in extremely detailed movies. She says her visual memory and sensitivity to details has allowed her to be so good at designing things, because details that neurotypical people gloss over are extremely important to her and end up making a huge difference in the efficiency of the final product.

Temple Grandin utilized her incredible working memory to design humane cattle-holding equipment for the agriculture industry.

Autism may not be the only example of a disorder being mischaracterized. Studies have shown that children with ADHD on average have lower IQs than neurotypical children (Kuntsi, 2003). However, in his TEDx talk, Stephen Tonti, a senior at Carnegie Mellon, discusses why he believes ADHD is not a disorder, but simply a difference in cognition. Tonti argues that by viewing ADHD as a disorder implies that it needs to be fixed. He states that his ADHD makes him better at some tasks than neurotypical individuals, and that the world needs a diversity of cognition in order to run smoothly.



Therefore, while IQ tests are intended to measure intelligence, they often only measure one type of intelligence, and are therefore biased against certain groups of people. By trying to fit cognition into a box, IQ testing disvalues cognitive diversity. This may be causing negative impacts. By telling an individual that their intelligence is low when in fact it is simply different, we could not only be holding people back, but we might also be depriving the world of a diverse group of thinkers that could solve problems from a different perspective.



Even if current IQ tests are not fair across all groups, the future of intelligence testing may be brighter; as discussed previously on the Neuroethics Blog, fMRI intelligence testing could eliminate biases in intelligence testing. By observing testers’ thought processes in action, researchers would be able to see which brain pathways a subject recruits to solve a test, and whether he or she uses a visual or verbal approach to the question, thereby observing fluid and crystal intelligence in action.





References



Binet, Alfred. (1905) L'Annee Psychologique, 12,191-244.



Bölte, S., Dziobek, I., & Poustka, F. “Brief report: The level and nature of autistic intelligence revisited”. Journal of Autism and Developmental Disorders 39 (2009): 678–682.



Cattell, Raymond B., and Raymond B. Cattell. "The Discovery of Fluid and Crystallized General Intelligence." Intelligence: Its Structure, Growth, and Action. Amsterdam: North-Holland, 1987. 87-120. Print.



Dickens, William T., and James R. Flynn. "Black Americans Reduce the Racial IQ Gap: Evidence from Standardization Samples." Psychological Science 17.10 (2006): 913-20. Web.



Kunda, Maithilee, and Ashok K. Goel. "Thinking in Pictures as a Cognitive Account of Autism." Journal of Autism and Developmental Disorders 41.9 (2011): 1157-177. Print.



Kuntsi, J., T.C. Eley, A. Taylor, C. Hughes, P. Asherson, A. Caspi, and T.E. Moffitt. "Co-occurrence of ADHD and Low IQ Has Genetic Origins." American Journal of Medical Genetics 124B.1 (2004): 41-47. Print.



Mottron, Laurent, Michelle Dawson, Isabelle Soulières, Benedicte Hubert, and Jake Burack. "Enhanced Perceptual Functioning in Autism: An Update, and Eight Principles of Autistic Perception." Journal of Autism and Developmental Disorders 36.1 (2006): 27-43. Print.



Raven, J., J. C. Raven, and J. Court. Manual for Raven’s Progressive Matrices and Vocabulary Scales, Section I: General Overview. San Antonio: Harcourt Assessment, 2003. Print.



Serpell, Robert. "How Specific Are Perceptual Skills? A Cross-cultural Study of Pattern Reproduction." British Journal of Psychology 70.3 (1979): 365-80. Print.



Spearman, Charles E. "'General Intelligence', Objectively Determined And Measured." American Journal of Psychology 15 (1904): 201-93. Web.





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Young, E. (2013). Intelligence Testing: Accurate, or Extremely Biased? Retrieved on , from http://www.theneuroethicsblog.com/2013/09/intelligence-testing-accurate-or.html

The Future of Intelligence Testing

Few people I know actually enjoy standardized tests. Wouldn’t it be great if technology could eliminate the need for bubble-in forms and Scantron sheets? How nice would it be to simply go in and get a snapshot of your brain to find out how smart you are? Imagine walking into the test center, signing on the dotted line, getting a quick scan, and walking out with your scores in hand, helping you gain admittance into a college or land your next job. No brain-racking questions, no tricky analogies, and no obscure vocabulary. Goodbye SAT, hello functional magnetic resonance imaging (fMRI).

Image from 















http://theturingcentenary.files.wordpress.com/2012/06/brain-functions.jpg    

In the general, there have been two types of intelligence studies: psychometric and biological. Biological approaches make use of neuroimaging techniques and examine brain function. Psychometrics focuses on mental abilities (think IQ tests). Dr. Ian Deary and associates suggest that a greater overlap of these techniques will reveal new findings. In their paper, 'Testing versus understanding human intelligence,' they state:



“The lack of overlap between these approaches means that it is unclear what the scores of intelligence tests mean in terms of fundamental biological processes of the brain.”[2]



Applying psychometric analysis techniques (IQ tests) coupled with advanced imaging has the potential to reveal the locations of “higher” cognition and neural processing. I expect that future technologies will have incredibly improved resolution, which will allow scientists to see not only what regions the brain uses but also the exact pathways that are activated for each action. By understanding which pathways are utilized for specific tasks, it may be possible to identify which genes as well as environmental factors (nutrition, education) are responsible for their development. This can lead to programs dedicated to training specific areas of the brain (several of which already exist) [5], and perhaps even drugs that foster development.



I believe it is increasingly important to consider the implications of a technology powerful enough to quickly evaluate an individual’s level of intelligence. However, before I get there, it is necessary to first explain what we can and cannot currently do. What we cannot currently do is use neuroimaging to determine how smart you are. What we can currently do is use neuroimaging to see what parts of your brain contribute to how you process information, access memories and function [3].



Localizing Intelligence



Different parts of your brain do different things and none of these brain regions work in isolation. Some regions contribute to eating, seeing, and other regions play a role in “intelligence”. The varying techniques of imaging-based testing search for different correlates of intelligence [4] (i.e., general intelligence, problem solving, learning abilities). Developments in imaging technologies have improved our ability for greater analysis, allowing for the study of both damaged and healthy brains. For example, MRI studies have found that the volume of gray matter correlates to intelligence, providing evidence for generalizations made regarding brain volume and intelligence [7]. A 2006 study of 100 postmortem brains examined the relationship between an individual’s Full Scale Wechsler Adult Intelligence Scale (WAIS) score and the volume of their brain regions. The factors they considered important to the relationship between brain size and intelligence were age, sex and hemispheric functional lateralization (They found that general verbal ability was correlated with cerebral volume in women and right-handed men. They did not find a relationship between ability and volume in with every group, however).



Additionally, PET and fMRI studies have revealed more information regarding the functionality of certain regions of the brain. By recording and interpreting the brain activity of subjects as they complete a variety of tasks, researchers are able to draw inferences based on the performance in the types of task (and thus, the type of intelligence) that calls on particular areas of the brain.  This is interesting, as knowing how parts of the brain are utilized may reveal more information about the structure and hierarchy used in neural development. It also may provide interesting information regarding the pathways of neural signals throughout the nervous system. Image-based testing may allow researchers to discover why certain neurons are connected, if they are indeed aligned in a purposeful manner and consequently, how to repair such pathways when they are damaged.

Image from http://news.wustl.edu/news/Pages/24068.aspx

A study from Washington University in St. Louis has shed light on how our brains utilize various networks for performance with working memory tasks [1]. They described a mechanism, global connectivity, which coordinates control of other networks. In a sense, global connectivity is the CEO of your brain, insuring that all components of your system are functioning and allowing for effective control of thought and behavior. Specifically, they found that a region of the lateral prefrontal cortex (LPFC), whose activity has been found to predict working memory performance, employs global connectivity. They report that,



“critically, global connectivity in this LPFC region, involving connections both within and outside the frontoparietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brainwide influence that facilitates the ability to implement control processes central to human intelligence.”



This fascinating study identified a very specific characteristic of the brain (the global connectivity of the left LPFC) that suggested investigators were accurately able to predict fluid intelligence (where fluid intelligence refers to reasoning and novel problem solving ability) [4].





Potential Issues



We are learning more about the brain and the biological bases for intelligence every day. We have expanded our understanding of memory, cognitive thought and neural computation [2,6]. Our understanding of imaging techniques and what we can learn from them continues to grow. It may very well be possible to someday use neuroimaging to evaluate an individual’s intelligence. It is becoming more widely accepted that a neurobiological basis for intelligence exists (at least for reasoning and problem-solving) [4]. At the same time, the success of these intelligence studies presents ethical issues. Gray et al. pose the question, “Is it ever ethical to assess population-group (racial or ethnic) differences in intelligence?” While little variation has been found between racial groups, the public perception of intelligence studies has been negatively impacted by concerns of racism [4]. It is important to consider the consequences of studies that investigate intelligence differences in population-groups (racial, ethnic, and socioeconomic status). Gray states that it is not necessary to consider race when exploring the neurobiological bases of intelligence. The majority of variation occurs within a racial group and not between them. However, if a study were to investigate race and intelligence, Gray states that it will be necessary to have consent as well as active support from the target groups (i.e., financial support).



There are in fact studies that have investigated test score differences associated with race. Claude Steele, Ph.D., a professor of social psychology at Stanford University, discussed the test performance differences of white and black Americans. In his interview with PBS, Dr. Steele explained that a serious gap in test scores exists between whites and blacks, citing 100-point differences on the verbal and quantitative sections of the SAT. This is a concern for policy makers who are responsible for maintaining a standard level of education, as these low scores may help identify areas that need improvement. However, the negative effect of these findings is due to something Dr. Steele refers to as “stereotype threat.” He explains that when a salient negative stereotype about a group that you identify with may apply (i.e., lower SAT scores), when you are in that test situation the prospect of matching the stereotype can be distracting and upsetting. This stereotype threat impacts test taking, undermining test performance.



When considering the neurobiological bases of intelligence, it may be harder to escape these stereotypes. It may someday become known which genes code for higher intelligence, and thus higher test scores. Already, we have begun studying what regions of the brain relate to intelligence test performance. The next step will be discovering which genes code for the development of those regions, then connecting the dots from genes to intelligence. Furthermore, an understanding of the environmental and social influence that control the activation of these genes (and thus development) will be needed. Future generations may have stereotype threats that are based on genes rather than groups. When you know that you carry the genes for a certain level of intelligence, you may find yourself doubtful of your ability to perform above the level predicted by your genome and fall short of your potential.



There is a lot to be learned regarding how our genes relate to intelligence and by understanding how different gene pools code for their “smarts,” our understanding could grow immensely. However, as I mentioned earlier, suggesting that one group is genetically hard-coded to be smarter than another will have enormous implications. Science and research are going to continue pushing this ethical boundary and I predict that we eventually will be able to find many links between genes and intelligence. It is both beneficial and crucial to discuss how genes and intelligence should be studied now, before the research takes place. We have a unique opportunity where ethics can lay the guidelines before this technology emerges.



There are exciting possibilities that neuroimaging intelligence tests may bring. On the one hand, we can learn so much about the brain, how we think and how we can make it better. On the other hand, it may drive ethnic and racial groups, as well as socio-economic groups, farther apart. So we really have to ask ourselves, is that the price we have to pay to not fill out another Scantron sheet?







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Craig, E. The Future of Intelligence Testing. The Neuroethics Blog. Retrieved on from, http://www.theneuroethicsblog.com/2012/12/the-future-of-intelligence-testing.html






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References



1. Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012). Global connectivity of prefrontal cortex predicts cognitive control and intelligence. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32(26), 8988–99. doi:10.1523/JNEUROSCI.0536-12.2012

2. Deary, I. J., & Caryl, P. G. (1997). Neuroscience and human intelligence differences. Trends in neurosciences, 20(8), 365–71. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9246731

3. Duncan, J. (2000). A Neural Basis for General Intelligence. Science, 289(5478), 457–460. doi:10.1126/science.289.5478.457

4. Gray, J. R., & Thompson, P. M. (2004). Neurobiology of intelligence: science and ethics. Nature reviews. Neuroscience, 5(6), 471–82. doi:10.1038/nrn1405

5. Hackman, D. a, Farah, M. J., & Meaney, M. J. (2010). Socioeconomic status and the brain: mechanistic insights from human and animal research. Nature reviews. Neuroscience, 11(9), 651–9. doi:10.1038/nrn2897

6. Prabhakaran, V., Rypma, B., & Gabrieli, J. D. E. (2001). Neural substrates of mathematical reasoning: A functional magnetic resonance imaging study of neocortical activation during performance of the necessary arithmetic operations test. Neuropsychology, 15(1), 115–127. doi:10.1037//0894-4105.15.1.115

7. Witelson, S. F., Beresh, H., & Kigar, D. L. (2006). Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. Brain : a journal of neurology, 129(Pt 2), 386–98. doi:10.1093/brain/awh69