Many have advanced the idea that adolescent anatomical brain development justifies denying adolescents the civil liberties and decisional autonomy that are granted to almost all adults automatically [1][2]. In an earlier writing, I made a case for the opposite position [3], pointing out that a significant fraction of the adult population never exceeds the behavioral maturity of a typical 13-year-old, therefore an age of majority above 13 is equivalent to declaring a lot of normal adults to be incompetent. So the point is made that in a society where normal, mentally healthy, non-demented adults are almost universally given the right to make decisions regarding their own lives, it is discriminatory for the age of majority to be higher than 13 years.

But those arguing against giving adult rights to youth also bring physical brain anatomy into the discussion, not simply behavior. In this writing, I construct an analogous argument to that in [3] – a significant fraction of the adult population never exceeds the neurological development level* of a typical 13-year-old (as measured by, for example, fractional volume of white matter in the brain), therefore, an age of majority above 13 is equivalent to declaring a lot of normal adults to be incompetent and should not stand. I will now proceed to show that this is the case starting with a technical analysis of anatomical data from brain scans.

The usual brain development referred to in these discussions consists of two processes – synaptic pruning and myelination. [4] The cell bodies of neurons make up gray matter, and the myelinated axons make up white matter [5]. Thus the adolescent brain development generally referred to in these discussions should cause white matter to increase and gray matter to decrease (to make room for the white matter). Indeed it is often stated that the maximum number of neurons or maximum amount of gray matter occurs approximately at the beginning of adolescence, and that unused connections are pruned away during adolescence and the remaining neural connections are myelinated. This implies that the maturation of the brain through the teenage years is governed by a loss of gray matter and a gain of white matter.

White matter volume may change not only in the youthful years, but also evolves during adult life as well. Also, the percentage of brain volume occupied by white matter varies considerably from person to person among adults of the same age, from less than 30 percent to more than 40 percent over much of adulthood, while the percentage of gray matter declines smoothly during adulthood from age 20 until the 80’s. [6] There is some inconsistency in study results, to be sure. One study reports an increasing white matter volume during youth, having a value of around 390 mL at age 13, and then increasing to the maximum value of 420 mL in early adulthood. [7] Another study reports nearly constant white matter volume throughout adolescence from age 12 to age 19 in the prefrontal lobe [8] , but this source explains that it contradicts earlier findings. (Strictly, it does not contradict [7] because it is the prefrontal brain area only, not the whole brain.) This source gives the fractional volume occupied by frontal white matter in early adolescence as ranging approximately from 0.06 to 0.075.

In the study [7], the increase in white matter mean volume from age 13 to early adulthood is from 390 to 420 mL, which is a gain of around 8%, in absolute terms. Since the whole brain volume does not decrease during adolescence, this means that in terms of the fraction of the brain occupied by white matter, the fraction increases by 8% of its mean value, or less, between age 13 and adulthood. Put another way, it is at least 92% of its adult value at age 13. Given that the normal adult values range from 30% - 40% according to [6], with an average around 36% for much of early adulthood (ages 20s and 30s), this would imply, if we informally splice together the studies, that the 13-year-old mean value for white matter fraction, is around 33% or a bit more (because that is 92% of 36%). Notice that a small, but significant, fraction of the normal adult population in [6] falls below this level. Thus, in the same spirit as the behavioral argument I made in [3], to claim that the incompletely developed brain justifies legal classification of 13-year-olds (and above) as minors, would also imply that this segment of the adult population in [6] is incompetent, since these adult subjects have a white matter volume fraction below the level equivalent to a 13-year-old. No reasonable scientist or judge would, of course, conclude that this segment of the study population should be as a matter of fact found legally incompetent on this basis alone, thus if we reason based on white matter alone we have no reason to conclude that setting the age of majority at 13 years would be too low. To say otherwise would be inconsistent.

What about gray matter? Here we have a serious historical misunderstanding. It was formerly thought that gray matter density and gray matter volume changed in tandem [9] which was the basis of one of the popularized “brain maturation maps” used to illustrate the continuing development of the human brain through the adolescent years. However, it has later been found in a recent study [10a,10b] that this assumption is not correct: Gray matter density and gray matter volume move in opposite directions during adolescence, which throws into question the manner by which gray matter can be used in the definition of development or maturity of the brain. But even aside from this issue, the newer study shows the differences between men and women are comparable to the difference between 13-year-olds and adults, thus, to use it to justify an age of majority higher than 13 is equivalent to a rather extreme form of sexism on this metric. If this is unacceptable, then it must be similarly unacceptable to use this metric of gray matter to claim that even young adolescents are on average too immature for civil rights and self-determination.

There are other measures of brain maturation being used recently such as white matter fractional anisotropy, but at least one important study shows that for most voxels (that is, for most brain areas), there is no significant correlation between age and fractional anisotropy, even when the study includes much younger children down to age 6! [11] The small minority of the brain’s voxels that do show a correlation, presumably many of them would lose the significance if limited to adolescents by excluding the younger children’s data. Another important caveat is that this analysis cannot, strictly speaking, be used to compare adolescents to adults, because there are no data points for age higher than 20 years, in fact, even the sample size of individuals above age 16 is small. Finally the human brain is plastic and the partial inability to use some small areas does not necessarily mean that certain brain functions are impaired relative to adults, or to older adolescents, since a different part of the brain may be used instead.

On another note – the claim is often made that adolescent brain development explains the peak in risk-taking that occurs in adolescence in neurologically typical youth [12]. However, the development of the brain’s anatomy cannot explain the phenomenon of (typical) adolescent risk-taking if the phenomenon does not exist. Newer analyses suggest that in fact the phenomenon of adolescent risk taking is an illusion, at least in neurologically typical adolescents.[13][14]

In conclusion, it is often claimed that adolescent brain development provides a justification to deny civil liberty rights to adolescents from the ages of 13-17. However, once one quantifies development using measures such as white matter volume, gray matter volume, and fractional anisotropy, it becomes evident that many healthy adults do not exceed the brain development* level of a typical 13-year-old. Thus the immaturity of the brain cannot be used to justify a denial of adolescent liberties without also implying that much of the adult population is incompetent, which is absurd. Furthermore, denying adolescent liberty on the basis that “immature brains result in risk-taking” does not make sense, because in mentally normal adolescents, the peak in risk-taking due to neurodevelopment does not exist. 


*It has come to my attention that multimodal analysis methods can now reliably estimate brain age in the range from 3-20 years based on scans. [15] This at most slightly weakens the case made in this article regarding decisional maturity. Consider by analogy, an argument based on the physical body: A sufficiently clever computer program might be able to look at an image of your body taken under very controlled conditions and estimate your age and determine your sex (much as a human can), especially if your face is included. This would, however, have virtually no impact on the question of whether or not it is discriminatory to bar people over 50 or women from using weight machines. In fact, even if I could write a computer program that could determine your age and sex by measuring the shape of your arms very precisely, this would not have an impact on whether such a rule was discriminatory. The determining factors on whether the rule is discriminatory have more to do with whether age/sex is a reliable enough way of gauging safety risk, and whether it is ethical to discriminate on the basis of age/sex but not on the basis of a disability that has a comparable effect on injury risk or physical strength. The question is not whether people of different sexes or ages are different, of course they are. The question is about the relevance of the differences to the variables that matter to the discussion (in this example, physical strength and safety risk).

Similarly, merely showing that the brain changes with age is not sufficient to claim that a rule based on age is not unfairly discriminatory. It is also necessary to make an independent assessment of the relevance of such differences. For this and other reasons, this article focuses mainly on the "macroscopic" brain parameters like total gray matter and white matter. It is at least plausible that these macroscopic variables are related to decisional judgment maturity in some way, just as total muscle mass might relate to strength but exact muscle shape is less likely to.

With sufficient resolution and good algorithms, of course each of us has a unique brain that is unlike that of any of the rest of us. The same is true for the rest of the body. However, no one in their right mind would argue that this justifies arbitrary bans on a particular individual or individuals exercising a given right or being allowed to use athletic facilities. Again, one must ask what differences are relevant, and what the "macroscopic" parameters are that at least plausibly relate to them.     


 [1] Steinberg, Laurence. "Risk Taking in Adolescence: New Perspectives from Brain and Behavioral Science." Current Directions in Psychological Science 16.2 (2007): 55-59. Web.

[2] Johnson, Sara B., Robert W. Blum, and Jay N. Giedd. "Adolescent Maturity and the Brain: The Promise and Pitfalls of Neuroscience Research in Adolescent Health Policy." Journal of Adolescent Health 45.3 (2009): 216-21. Web.

[3] Cole, Nightvid F. "Minority vs. Legal Incompetence: The Case for Lowering the Age of Majority to 13." Science 2.0. Science 2.0, 16 May 2017. Web. 23 May 2017.< >

[4] Coghlan, Andy. "Revealed: The Teenage Brain Upgrades That Occur before Adulthood." New Scientist 25 July 2016: Web.

 [5] Purves, Dale, George J. Augustine, David Fitzpatrick, Anthony-Samuel LaMantia, Leonard E. White, and James O. McNamara. Neuroscience, 4th Edition. (unknown city) : W. H. Freeman, 2008. Print.

[6] Ge, Yulin, Robert I. Grossman, James S. Babb, Marcie L. Rabin, Lois J. Mannon, and Dennis L. Kolson. "Age-Related Total Gray Matter and White Matter Changes in Normal Adult Brain. Part I: Volumetric MR Imaging Analysis." American Journal of Neuroradiology 23.8 (2002): 1327-333. Web.

[7] Matsui, Mie, Chiaki Tanaka, Lisha Niu, Kyo Noguchi, Warren B. Bilker, Michael Wierzbicki, and Ruben C. Gur. "Age-related Volumetric Changes of Prefrontal Gray and White Matter from Healthy Infancy to Adulthood." International Journal of Clinical and Experimental Neurology 4.1 (2016): 1-8. Web.

 [8] Nagel, Bonnie J., Krista Lisdahl Medina, June Yoshii, Alecia D. Schweinsburg, Ida Moadab, and Susan F. Tapert. "Age-related Changes in Prefrontal White Matter Volume across Adolescence." NeuroReport 17.13 (2006): 1427-431. Web.

 [9] Gogtay, Nitin, Jay N. Giedd, Leslie Lusk, Kiralee M. Hayashi, Deanna Greenstein, A. Catherine Vaituzis, Tom F. Nugent, III, David H. Herman, Liv S. Clasen, Arthur W. Toga, Judith L. Rapoport, and Paul M. Thompson. "Dynamic Mapping of Human Cortical Development during Childhood through Early Adulthood." PNAS. 21st ed. Vol. 101., 2004. 8174-179. Web.

[10a] Muse, Queen. "Penn Study Finds Gray Matter Density Increases During Adolescence." Penn Medicine News. Penn Medicine, 26 May 2017. Web. 3 June 2017. . Reference inside this source is to [10b].

[10b] Gennatas, Efstathios D., Brian B. Avants, Daniel H. Wolf, Theodore D. Satterthwaite, Kosha Ruparel, Rastko Ciric, Hakon Hakonarson, Raquel E. Gur, and Ruben C. Gur. "Age-Related Effects and Sex Differences in Gray Matter Density, Volume, Mass, and Cortical Thickness from Childhood to Young Adulthood." The Journal of Neuroscience 37.20 (2017): 5065-073. Web.

 [11] Barnea-Goraly, N., Vinod Menon, Mark Eckert, Leanna Tamm, Roland Bammer, Asya Karchemskiy, Christopher C. Dant, and Allan L. Reiss. "White Matter Development During Childhood and Adolescence: A Cross-sectional Diffusion Tensor Imaging Study." Cerebral Cortex 15.12 (2005): 1848-854. Web.

 [12] Steinberg, Laurence. “A Social Neuroscience Perspective on Adolescent Risk-Taking.” Developmental review : DR 28.1 (2008): 78–106. PMC. Web. 4 June 2017.

 [13] Remund, Adrien. "Young Adults’ Excess Mortality: Individual Reality or Yet Another Heterogeneity’s Ruse?" Proc. of European Population Conference 2014, Budapest, Hungary. Web.

 [14] Bjork, James M., and Dustin A. Pardini. "Who Are Those "risk-taking Adolescents"? Individual Differences in Developmental Neuroimaging Research." Developmental Cognitive Neuroscience 11 (2015): 56-64. Web.

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