Adolescent Maturity and the
Brain: The Promise and Pitfalls of Neuroscience Research in Adolescent Health
Policy
Longitudinal
neuroimaging studies demonstrate that the adolescent brain continues to mature
well into the 20s. This has prompted intense interest in linking
neuromaturation to maturity of judgment. Public policy is struggling to keep up
with burgeoning interest in cognitive neuroscience and neuroimaging. However,
empirical evidence linking neurodevelopmental processes and adolescent
real-world behavior remains sparse. Nonetheless, adolescent brain development
research is already shaping public policy debates about when individuals should
be considered mature for policy purposes. With this in mind, in this article we
summarize what is known about adolescent brain development and what remains
unknown, as well as what neuroscience can and cannot tell us about the
adolescent brain and behavior. We suggest that a conceptual framework that
situates brain science in the broader context of adolescent developmental
research would help to facilitate research-to-policy translation. Furthermore,
although contemporary discussions of adolescent maturity and the brain often
use a deficit-based approach, there is enormous opportunity for brain science
to illuminate the great strengths and potentialities of the adolescent brain.
So, too, can this information inform policies that promote adolescent health
and well-being.
Keywords: Adolescent, Health policy,
Neuroscience, Neuroimaging, Judgment
In the last
decade, a growing body of longitudinal neuroimaging research has demonstrated
that adolescence is a period of continued brain growth and change, challenging
longstanding assumptions that the brain was largely finished maturing by
puberty [1–3]. The frontal lobes, home to key components of
the neural circuitry underlying “executive functions” such as planning, working
memory, and impulse control, are among the last areas of the brain to mature;
they may not be fully developed until halfway through the third decade of life
[2]. This finding has prompted interest in linking
stage of neuromaturation to maturity of judgment. Indeed, the promise of a
biological explanation for often puzzling adolescent health risk behavior has
captured the attention of the media, parents, policymakers, and clinicians alike.
Although such research is currently underway, many neuroscientists argue that
empirical support for a causal relationship between neuromaturational processes
and real-world behavior is currently lacking [4].
Despite the
lack of empirical evidence, there has been increasing pressure to bring
adolescent brain research to bear on adolescent health and welfare policy. For
example, in the policy process, adolescent brain immaturity has been used to
make the case that teens should be considered less culpable for crimes they
commit; however, parallel logic has been used to argue that teens are
insufficiently mature to make autonomous choices about their reproductive
health [5]. This apparently conflicting use of
neuroscience research evidence highlights the need for brain scientists,
neurocognitive psychologists, and adolescent health professionals to work together
to ensure appropriate translation of science for policy. Failing to proactively
define or engage in a discussion about the role of neuroimaging research in
policy may catalyze a course of action many adolescent health professionals
would not endorse.
In this
review, we begin by outlining historical attempts to use developmental
benchmarks as measures of adolescent maturity. (When we refer to “maturity” we
do not intend to suggest the end of development, but rather use this as
shorthand for the achievement of adult-like capacities and privileges.) We then
briefly summarize what is known about adolescent brain development, and what is
unknown. (For in-depth reviews of adolescent brain development, and more
nuanced discussions of research findings, which are beyond the scope of this
review, see [6] and [7]). We provide an overview of what neuroimaging
research can and cannot tell us about the adolescent brain and behavior. We
then highlight the current use of the brain sciences in adolescent health
policy debates. Finally, we outline a strategy for increasing the utility of
brain science in public policy to promote adolescents’ well-being.
A Historical Perspective on Development and Maturity
Throughout
history there have been biological benchmarks of maturity. For example, puberty
has often been used as the transition point into adulthood. As societal needs
have changed, so too have definitions of maturity. For example, in 13th
century England, when feudal concerns were paramount, the age of majority was
raised from 15 to 21 years, citing the strength needed to bear the weight of
protective armor and the greater skill required for fighting on horseback [8]. More recently, in the United States the legal
drinking age has been raised to 21, whereas the voting age has been reduced to
18 years so as to create parity with conscription [9]. Similarly, the minimum age to be elected
varies by office in the U.S.: 25 years for the House of Representatives, 30
years for the Senate, and 35 years for President. However, individuals as young
as 16 can be elected Mayor in some municipalities. The variation evident in
age-based definitions of maturity illustrates that most are developmentally
arbitrary [9]. Nonetheless, having achieved the legal age to
participate in a given activity (e.g., driving, voting, marrying) often comes
to be taken as synonymous with the developmental maturity required for it.
Age-based
policies are not exceptional; policies are frequently enacted in the face of
contradictory or nonexistent empirical support [10]. Although neuroscience has been called upon
to determine adulthood, there is little empirical evidence to support age 18,
the current legal age of majority, as an accurate marker of adult capacities.
Less clear is whether neuroimaging, at present, helps to inform age-based
determinations of maturity. If so, can generic guidelines be established, or is
individual variation so great as to preclude establishing a biological
benchmark for adult-like maturity of judgment?
Brain Development in Adolescence
Current
studies demonstrate that brain structures and processes change throughout
adolescence and, indeed, across the life course [11]. These findings have been facilitated by
imaging technologies such as structural and functional magnetic resonance
imaging (sMRI and fMRI, respectively). Much of the popular discussion about
adolescent brain development has focused on the comparatively late maturation
of the frontal lobes [12], although recent work has broadened to the
increasing “connectivity” of the brain.
Throughout
childhood and into adolescence, the cortical areas of the brain continue to
thicken as neural connections proliferate. In the frontal cortex, gray matter
volumes peak at approximately 11 years of age in girls and 12 years of age in
boys, reflecting dendritic overproduction [7]. Subsequently, rarely used connections are
selectively pruned [6] making the brain more efficient by allowing it
to change structurally in response to the demands of the environment [13]. Pruning also results in increased
specialization of brain regions [14]; however, the loss of gray matter that
accompanies pruning may not be apparent in some parts of the brain until young
adulthood [2,15,16]. In general, loss of gray matter progresses
from the back to the front of the brain with the frontal lobes among the last
to show these structural changes [3,6].
Neural
connections that survive the pruning process become more adept at transmitting
information through myelination. Myelin, a sheath of fatty cell material
wrapped around neuronal axons, acts as “insulation” for neural connections.
This allows nerve impulses to travel throughout the brain more quickly and
efficiently and facilitates increased integration of brain activity [17]. Although myelin cannot be measured directly,
it is inferred from volumes of cerebral white matter [18]. Evidence suggests that, in the prefrontal
cortex, this does not occur until the early 20s or later [15,16].
The prefrontal
cortex coordinates higher-order cognitive processes and executive functioning.
Executive functions are a set of supervisory cognitive skills needed for
goal-directed behavior, including planning, response inhibition, working
memory, and attention [19]. These skills allow an individual to pause
long enough to take stock of a situation, assess his or her options, plan a
course of action, and execute it. Poor executive functioning leads to
difficulty with planning, attention, using feedback, and mental inflexibility [19], all of which could undermine judgment and
decision making.
Synaptic
overproduction, pruning and myelination the basic steps of neuromaturation improve
the brain’s ability to transfer information between different regions
efficiently. This information integration undergirds the development of skills
such as impulse control [20]. Although young children can demonstrate
impulse control skills, with age and neuro-maturation (e.g., pruning and
myelination), comes the ability to consistently use these skills [21].
Evidence
from animal studies suggests that the neural connections between the amygdala
(a limbic structure involved in emotional processing, especially of fear and
vigilance) and the cortices that comprise the frontal lobes become denser
during adolescence [22]. These connections integrate emotional and
cognitive processes and result in what is often considered to be “emotional
maturity” (e.g., the ability to regulate and to interpret emotions). The
evidence suggests that this integration process continues to develop well into
adulthood [23]. Steinberg, Dahl, and others have
hypothesized that a temporal gap between the development of the socioemotional
system of the brain (which experiences an early developmental surge around
puberty) and the cognitive control system of the brain (which extends through
late adolescence) underlies some aspects of risk-taking behavior [24,25]. This temporal gap has been compared with
starting the engine of a car without the benefit of a skilled driver [25].
Adolescent Neuropsychology: Linking Brain and Behavior
As detailed
above, across cultures and millennia, the teen years have been observed to be a
time of dramatic changes in body and behavior. During adolescence, most people
successfully navigate the transition from dependence upon caregivers to
self-sufficient adult members of society. Where specifically, along the
maturational path of cognitive and emotional development, individuals should be
given certain societal rights and responsibilities continues to be a topic of
intense interest. Increasingly, neuroscience has been called on to inform this
question.
Impulse control, response inhibition, and sensation
seeking
Among the
many behavior changes that have been noted for teens, the three that are most
robustly seen across cultures are: (1) increased novelty seeking; (2) increased
risk taking; and (3) a social affiliation shift toward peer-based interactions
[13]. This triad of behavior changes is seen not
only in human beings but in nearly all social mammals [13]. Although the behaviors may lead to danger,
they confer an evolutionary advantage by encouraging separation from the
comfort and safety of the natal family, which decreases the chances of
inbreeding. The behavior changes also foster the development and acquisition of
independent survival skills [13].
Studying the
link between behavioral changes and brain changes has been greatly facilitated
by recent advances in neuroimaging technology and behavioral assessments. One
challenge has been to identify the fundamental units of emotion and cognition
and how they combine to determine more complicated “real-world” behaviors. For
instance, younger adolescents are less likely than older adolescents to wait a
given period of time to receive a larger reward [26]. This tendency can be studied using
experiments in which the subject is asked questions such as whether they would
rather receive $800 now or $1,000 in 12 months. By varying the amount of
monetary difference and/or time between the transactions, an “indifference
point” can be calculated to quantify an individual’s tendency to prefer the
“here and now” to some future reward. There is an extensive literature
characterizing effects of age, gender, intelligence quotient (IQ), and other
variables on this phenomenon, which is termed “delay discounting” [26,27]. However, more recent work has demonstrated
that delay discounting is determined in part by the more fundamental traits of
impulse control and future orientation, each with their own neural
representations and developmental trajectories [28]. Furthermore, future orientation itself is a
multidimensional construct involving cognitive, affective, and motivational
systems.
Studies
using fMRI are beginning to contribute to this parsing of behavior into more
fundamental units by characterizing different neural representations and
maturational courses for separate but related concepts such as impulse control
and sensation seeking. Whereas sensation seeking changes seem to reflect
striatal dopamine changes related to the onset of puberty, impulse control, as
discussed previously, is more protracted and related to maturational changes in
the frontal lobe [21].
“Hot” and “cold” cognition
Perhaps
because of the relative ease of quantifying hormonal levels in animal models,
it is tempting to attribute all adolescent behavioral changes to “raging
hormones.” More nuanced investigations of adolescent behavior seek to
understand the specific mechanisms by which hormones affect neural circuitry
and to discern these processes from nonhormonal developmental changes. An
important aspect of this work is the distinction between “hot” and “cold”
cognition. Hot cognition refers to conditions of high emotional arousal or
conflict; this is often the case for the riskiest of adolescent behaviors [29]. Most research to date has captured
information in conditions of “cold cognition” (e.g., low arousal, no peers, and
hypothetical situations). Like impulse control and sensation seeking, hot and
cold cognition are subserved by different neuronal circuits and have different
developmental courses [30]. Thus, adolescent maturity of judgment and
its putative biological determinants are difficult to disentangle from
socioemotional context.
What We Do Not Know About Brain Development in
Adolescence
In many
respects, neuroimaging research is in its infancy; there is much to be learned
about how changes in brain structure and function relate to adolescent
behavior. As of yet, however, neuroimaging studies do not allow a chronologic
cut-point for behavioral or cognitive maturity at either the individual or
population level. The ability to designate an adolescent as “mature” or
“immature” neurologically is complicated by the fact that neuroscientific data
are continuous and highly variable from person to person; the bounds of
“normal” development have not been well delineated [5].
Neuroimaging
has captured the public interest, arguably because the resulting images are
popularly seen as “hard” evidence whereas behavioral science data are seen as
subjective. For example, in one study, subjects were asked to evaluate the
credibility of a manufactured news story describing neuroimaging research
findings. One version of the story included the text, another included an fMRI
image, and a third summarized the fMRI results in a chart accompanying the
text. Subjects who saw the brain image rated the story as more compelling than
did subjects in other conditions [31]. More strikingly, simply referring verbally
to neuroimaging data, even if logically irrelevant, increases an explanation’s
persuasiveness [32].
Despite
being popularly viewed as revealing the “objective truth,” neuroimaging
techniques involve an element of subjectivity. Investigators make choices about
thickness of brain slices, level of clarity and detail, techniques for
filtering signal from noise, and choice of the individuals to be sampled [5]. Furthermore, the cognitive or behavioral
implications of a given brain image or pattern of activation are not
necessarily straightforward. Researchers generally take pains to highlight the
correlative nature of the relationship; however, such statements are often
misinterpreted as causal [5]. Establishing a causal relationship is more
complicated than it might, at first, seem. For example, there is rarely a
one-to-one correspondence between a particular brain region and its discrete function;
a given brain region can be involved in many cognitive processes, and many
types of cognitive processes may be subserved by a particular brain structure [33].
Some neuroscientists
lament that the technology has been used too liberally to draw conclusions
where there is little empirical basis for interpreting the results. For
example, a 2007 New York Times Op-Ed piece reported the results of a
study in which fMRI was used to view the brains of 20 undecided voters while
they watched videos of presidential candidates; they had previously rated the
candidates on a scale of 1 to 10 from “very unfavorable” to “very favorable” [34]. The results of the brain scans were
interpreted as reflecting the inner thoughts of the participants. For instance,
“[w]hen viewing images of [Senator Clinton], these voters exhibited significant
activity in the anterior cingulate cortex, an emotional center of the brain
that is aroused when a person feels compelled to act in two different ways but
must choose one. It looked as if they were battling unacknowledged impulses to
like [Senator] Clinton” [34]. The editorial drew a swift response from
several neuroscientists who believed that, in addition to subverting the
standard peer review process before presenting data to the public, the
investigators did not address the issue of reverse inference [35]. In neuroimaging terms, reverse inference is
using neuroimaging data to infer specific mental states, motivations, or
cognitive processes. Because a given brain region may be activated by many
different processes, careful study design and analysis are imperative to making
valid inferences [36,37]. In symbolic logic terminology, reverse
inference errors are related to the “fallacy of affirming the consequent”
(e.g., “All dogs are mammals. Fred is a mammal. Therefore, Fred is a dog.”).
In sum,
neuroimaging modalities involve an element of subjectivity, just as behavioral
science modalities do. A concern is that high-profile media exposures may leave
the mistaken impression that fMRI, in particular, is an infallible mind-reading
technique that can be used to establish guilt or innocence, infer “true
intentions,” detect lies, or establish competency to drive, vote, or consent to
marriage.
The adolescent brain in context
Neuroimaging
technologies have made more information available about the structure and
function of the human brain than ever before. Nonetheless, there is still a
dearth of empirical evidence that allows us to anticipate behavior in the real
world based on performance in the scanner [5]. Linking brain scans to real-world functioning
is hampered by the complex integration of brain networks involved in behavior
and cognition. Further hindering extrapolation from the laboratory to the real
world is the fact that it is virtually impossible to parse the role of the
brain from other biological systems and contexts that shape human behavior [6]. Behavior in adolescence, and across the
lifespan, is a function of multiple interactive influences including
experience, parenting, socioeconomic status, individual agency and
self-efficacy, nutrition, culture, psychological well-being, the physical and
built environments, and social relationships and interactions [38–42]. When it comes to behavior, the relationships
among these variables are complex, and they change over time and with
development [43]. This causal complexity overwhelms many of
our “one factor at a time” explanatory and analytic models and highlights the
need to continually situate research from brain science in the broader context
of interdisciplinary developmental science to advance our understandings of
behavior across the lifespan [44].
Adolescent
Maturity and Policy in the Real World: Scientific Complexity Meets Policy
Reality
The most
prominent use of neuroscience research in adolescent social policy was the 2005
U.S. Supreme Court Case, Roper vs. Simmons, which has been described as
the “Brown v. Board of Education of ‘neurolaw,”’ recalling the case that
ended racial segregation in American schools [45]. In that case, 17-year-old Christopher
Simmons was convicted of murdering a woman during a robbery. Ultimately, he was
sentenced to death for his crime. Simmons’ defense team argued that he did not
have a specific, diagnosable brain condition, but rather that his
still-developing adolescent brain made him less culpable for his crime and
therefore not subject to the death penalty. Amicus briefs were filed by,
among others, by the American Psychological Association (APA) and the American
Medical Association (AMA) summarizing the existing neuroscience evidence and
suggesting that adolescents’ still-developing brains made them fundamentally
different from adults in terms of culpability.
The AMA
brief argued that: “[a]dolescents’ behavioral immaturity mirrors the anatomical
immaturity of their brains. To a degree never before understood, scientists can
now demonstrate that adolescents are immature not only to the observer’s naked
eye, but in the very fibers of their brains”’ [46]. (Notably, the brief submitted by the AMA et
al., implied a causal link among brain structure, function, and behavior in
adolescence [5]). The neuroscientific evidence is thought to
have carried significant weight in the Court’s decision to overturn the death
penalty for juveniles [47].
In a
dissenting opinion in that case, Justice Antonin Scalia reflected on a 1990
brief filed by the APA in support of adolescents’ right to seek an abortion
without parental consent (Hodgson v. Minnesota). In this case, the APA
argued that adolescent decision making was virtually indistinguishable from
adult decision making by the age of 14 or 15. Scalia pointed out this seeming
inconsistency: “[The APA] claims in this case that scientific evidence shows
persons under 18 lack the ability to take moral responsibility for their
decisions, [the APA] has previously taken precisely the opposite position
before this very Court. Given the nuances of scientific methodology and conflicting
views, courts which can only consider the limited evidence on the record before
them, are ill equipped to determine which view of science is the right one” [48]. Although one can make the case that the
“cold cognitive” context in which abortion-related decisions are made
encourages more mature judgment than the “hot cognitive” context of a murder,
Scalia’s comments highlight the peril of leaving nonscientists to arbitrate and
translate neuroscience for policy.
The Supreme
Court used neuroimaging research to protect juveniles from the death penalty
based on reduced capacity and consequently reduced culpability. A year after Roper
vs. Simmons was decided, the same logic was extended to limit adolescent
sexual behavior. In 2006, the State of Kansas used its interpretation of
adolescent neuroscience research to expand the state’s child abuse statute to
include any consensual touching between minors under the age of 16 years.
Although scientists may be reticent to apply their research to policy, in some
cases, policy makers are doing it for them.
Some argue
that one must only look to the use of early-life brain science to anticipate
what happens when brain science is overgeneralized [49]. In the early 1990s, there were several
high-profile studies that suggested that there was rapid growth brain growth
and plasticity in the first 3 years of life and, therefore, that “enriched”
environments could hasten the achievement of some developmental milestones [50]. This research was used to perpetuate the
idea that videos, classical music, and tailored preschool educational
activities could give a child a cognitive advantage before the door of neural
plasticity swung shut forever [49]. One could imagine that such a perspective
would discourage the allocation of resources for school-aged children and
adolescents because, if this were true, after early childhood it would simply
be “too late.” The use of neuroscientific research to support “enriched”
environments demonstrates that if neuroscientists do not direct the
interpretation and application of their findings (or the lack of
applicability), others will do it for them, perhaps without the benefit of
their nuanced understanding. A proactive approach to research and research-to-policy
translation that includes neuroscientists, adolescent health professionals, and
policy makers is an important next step.
Toward a
Policy-Relevant Neuroscientific Research Agenda
Public
policy is struggling to keep up with burgeoning interest in cognitive
neuroscience and neuroimaging [51]. In a rush to assign biological explanations
for behavior, adolescents may be caught in the middle. Policy scholar Robert
Blank comments, “We have not kept up in terms of policy mechanisms that
anticipate the implications beyond the technologies. We have little evidence
that there is any anticipatory policy. Most policies tend to be reactive” [51]. There is a need to situate research from the
brain sciences in the broader context of adolescent developmental science, and
to find ways to communicate the complex relationships among biology, behavior,
and context in ways that resonate with policymakers and research consumers.
Furthermore,
the time is right to advance collaborative, multidisciplinary research agendas
that are explicit in the desire to link brain structure to function as well as
adolescent behavior and implications for policy [52].
Ultimately,
the goal is to be able to articulate the conditions under which adolescents’
competence, or demonstrated maturity, is most vulnerable and most
resilient. Resilience, it seems, is often overlooked in contemporary
discussions of adolescent maturity and brain development. Indeed, the focus on
pathologic conditions, deficits, reduced capacity, and age-based risks
overshadows the enormous opportunity for brain science to illuminate the unique
strengths and potentialities of the adolescent brain. So, too, can this
information inform policies that help to reinforce and perpetuate opportunities
for adolescents to thrive in this stage of development, not just survive.
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