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BACKGROUND ON ADOLESCENT SUBSTANCE USE
Substance use during adolescence has been associated with alterations in brain
structure, function, and neurocognition. This review will present the current research
regarding typical adolescent brain development and the subtle but significant
abnormalities in indices of brain functioning associated with alcohol and drug use
during this critical developmental period. Studies using neuropsychological
assessment and structural and functional imaging will be discussed to help elucidate
the relationship between neurocognition with alcohol and marijuana use. Additionally,
methodological issues in neuroimaging and neuropsychological assessment research
will be reviewed.
While several decades of research with adults have shown that chronic heavy drinking
is associated with adverse consequences on the adult brain 1, this relationship has only
recently been explored in the adolescent brain. Understanding the effects of alcohol
and drug use on adolescent neurocognition is crucial, being that rates of use increase
dramatically between ages 12 and 18. Epidemiological studies have shown that past
month alcohol use increases from 17% to 45% between 8 th and 12th grade, and illicit
drug use prevalence expands from 8% to 22%. Lifetime rates indicate that 73% of
youth have used alcohol and 48% have used illicit drugs by their senior year of high
school 2. In the past year, 23% of youth meet diagnostic criteria for a substance use
disorder (alcohol or drug abuse or dependence) by age 20 3.
While the developing brain may be more resilient to neurotoxic effects, exposure to
alcohol and drugs during a period of critical neurological development may interrupt
the natural course of brain maturation and key processes of brain development. In
fact, adolescence may be a period of heightened vulnerability for alcohol’s effect on
the brain 4–7. Cognitive deficits resulting from these alcohol and drug related neural
insults have potentially harmful implications for subsequent academic, occupational,
and social functioning extending into adulthood. Therefore, neurocognitive sequelae
from heavy drinking and drug use are important to elucidate.
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TYPICAL ADOLESCENT BRAIN DEVELOPMENT

Adolescence marks a period of rapid development between childhood and adulthood
involving complex social, biological, and psychological changes. The interactions of
these multidimensional factors have considerable implications for adolescent
development. Included in these alterations are substantial changes in the efficiency
and specialization of the adolescent brain, which is accomplished through synaptic
refinement and myelination 8. Synaptic refinement involves reductions in gray matter
by eliminating unnecessary neural connections 9. During adolescence, this synaptic
pruning occurs primarily in the prefrontal and temporal cortex 10 and in subcortical
structures such as the striatum, thalamus, and nucleus accumbens 11, 12. The adolescent
brain also undergoes increased myelination, which allows for improved integrity of
white matter fiber tracts and efficiency of neural conductivity 13–16. Higher-order
association areas appear to develop only after lower-order sensorimotor regions fully
mature 17, with frontal lobes being the final areas of the brain to complete
development. Along with these neuromaturational changes, it is suggested that
increased myelination allows for smoother, more efficient communication between
frontal-subcortical brain regions, allowing for better top-down cognitive control in
adolescence 18.
In conjunction with these numerous brain transformations, shifting social influences
and peer group affiliation heavily impact adolescent behaviors 19, 20. This may place
youth at a particularly heightened risk for initiating and continuing alcohol and drug
use. Specifically, transformations in the prefrontal regions and limbic systems are
thought to contribute to increased risk taking and novelty/sensation seeking
behaviors 21, 22. The neuromaturation and neurochemical changes that are present
during this period correspond to a range of cognitive, emotional, and behavioral
changes, and are hypothesized to contribute to adolescents’ increased propensity for
alcohol and drug use 23.
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ADOLESCENT SUBSTANCE USE AND NEUROCOGNITION
The current literature suggests that heavy drinking during adolescence does have a
subtle, but significant, deleterious effects on adolescent neurocognitive functioning.
Studies have found that adolescent heavy drinkers exhibit decrements in memory 24,
attention and speeded information processing 25, 26, and executive functioning27–29. In a
study comparing alcohol dependent and healthy control adolescents, Brown et

al. 24 found that drinkers recalled 10% less verbal and nonverbal information than
controls, even after three weeks of monitored abstinence. A similar degree of
reduction was found on attentional and speeded information processing tasks in
abstinent adolescent drinkers 25. These findings are consistent with literature
examining neurocognitive deficits in young heavy drinkers, which found similar
decreases on attention and information processing, along with deficits in language
competence and academic achievement 26. Deficits in executive functioning,
specifically in future planning, abstract reasoning strategies, and generation of new
solutions to problems, have also been found 27.
While it has often been assumed that marijuana use is not linked to long-term
cognitive deficits, recent data suggest that even after four weeks of monitored
abstinence, adolescents who regularly smoke marijuana performed poorer on
performance tests of learning, cognitive flexibility, visual scanning, error commission,
and working memory 30. Further, the number of lifetime marijuana use episodes was
significantly related to overall poorer cognitive functioning, even after controlling for
lifetime alcohol use.
We 7 prospectively examined neuropsychological functioning in 26 youths with no
histories of alcohol or drug problems, and compared them to 47 youths with histories
of heavy adolescent alcohol, marijuana, and stimulant use. Follow-up
neuropsychological tests were given to the subjects seven different times across 8
years, on average between the ages of 16 to 24. While there were no significant
differences between users and non-users on neurocognitive test scores at the first time
point, heavy drinkers performed worse on cognitive tasks at age 24 than light
drinkers. In particular, those who had a history of alcohol withdrawal symptoms (e.g.,
orthostatic hypotension, nausea, insomnia, or irritability) were the most likely to have
decreases in performance scores, especially on tests of spatial functioning. Overall,
heavy drinking during adolescence was linked to a reduction in keeping up with age
expectations 7, 25, 31.
In summary, adolescence is characterized by dramatic increases in rates of substance
use concurrent with ongoing neuromaturation. While neuropsychological studies have
shown that adolescent substance use is linked to poorer spatial, inhibitory, and
learning and memory functioning, neuroimaging techniques may elucidate the neural
mechanisms of these performance deficits.

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ADOLESCENT SUBSTANCE USE AND BRAIN STRUCTURE
Advances in neuroimaging have made it feasible to closely characterize the brain
structure and function of adolescent substance users and to pinpoint the circuitry and
regions that may subserve the neuropsychological deficits observed in adolescent
substance users.
Hippocampal Volume

Magnetic resonance imaging (MRI) was used to examine structural differences in the
hippocampus, an area of the brain crucial to intact memory functioning. Participants
were classified as: (1) light to non-drinkers (≤1 drink per month, ≤ 1 lifetime
marijuana use episode), (2) heavy drinking adolescents (history of consuming 4/5+
drinks in a day), and (3) heavy marijuana users who also engaged in heavy episodic
drinking. Manual tracing techniques were employed by reliable raters, and revealed
that heavy drinkers had smaller left hippocampal volumes (p<.01), while
marijuana+alcohol users had similar volumes as controls 32. Additionally, greater
alcohol abuse/dependence severity was associated with smaller left hippocampal
volumes, a finding that supported previous animal models 33. Heavy drinkers showed
significantly different patterns of hippocampal asymmetry (p<.05; smaller left than
right hippocampal volumes) compared to light-drinking youths, with an asymmetry
ratio linked to memory performance. For controls, greater right than left hippocampal
asymmetry correlated with better verbal learning (p<.05), but not in user
groups 34 (see Figure 1).

Figure 1
Hippocampal volume for adolescents with different substance use patterns.
Adolescent users of alcohol, but not alcohol plus marijuana, showed significantly
smaller left hippocampal volumes than demographically similar non-users (Medina et
al., 2007).

These findings support the hypothesis that heavy alcohol use in adolescence has an
adverse influence on the hippocampus, potentially affecting subsequent memory
performance. Additionally, marijuana, in combination with alcohol use, could have
some neuroprotective effects, but further studies are warranted to examine this
hypothesis. An alternative explanation is that alcohol and marijuana use may create
opposing mechanisms (e.g., neuroinflammation and myelination suppression), so that
macromorphometric variables may actually appear normal. Microstructural
hippocampal changes related to marijuana use may include increased glial
proliferation and white matter density as well as reduced gray matter, resulting in
relatively normal hippocampal volumes despite functional pathology. Alternatively,
heavy adolescent marijuana use may subtly interfere with synaptic pruning processes,
resulting in larger gray matter volumes, particularly in the left hippocampus 32, 34.
Prefrontal Cortex Volume

During adolescence, the frontal lobe, an area of the brain associated with planning,
inhibition, emotion regulation, and integration of novel stimuli, goes through
extensive neuromaturation, increasing in efficiency and specialization. In a study
comparing prefrontal cortex volumes of adolescent heavy drinkers to non-drinkers and
marijuana and alcohol users, prefrontal volumes were smaller in heavy drinkers
relative to controls (p=.09) 35 (see Figure 2). This difference was particularly
pronounced in females (p<.003), confirming previous studies that examined youth
with comorbid drug and psychiatric disorders 36.

Figure 2
Ventral prefrontal volume in adolescents with minimal and heavy drinking histories;
ventral prefrontal region is highlight in white in the figure to the right.
Interestingly, in our preliminary comparison of prefrontal cortex volumes of 16
marijuana-using and 16 control adolescents, few differences were observed. However,
among females, marijuana users had a 4% larger posterior and prefrontal cortex
volume (p=.06) than non-users, on average. This was associated with poorer verbal
memory, suggesting potentially interrupted synaptic pruning in female users.
Marijuana-using adolescents showed larger global gray matter volumes than controls,

with increased marijuana use predicting increased volume (β=.61, p<.01) and poorer
verbal and attention performance 35. These findings also suggest that marijuana use
during adolescence may disrupt gray matter pruning processes.
White Matter Volume

White matter maturation during adolescence through young adulthood is important for
neuronal transmission between connecting brain regions. A recent study comparing
adolescent marijuana users and matched controls indicated no significant differences
in white matter volumes 37. However, marijuana use (β = .42, p < .04) and smaller
white matter volume (β = −.34, p < .03) each predicted increased depressive
symptoms on the Hamilton Depression Rating Scale 38. Further, marijuana use
interacted with white matter volume to predict depression scores on the Beck
Depression Inventory (BDI) 39. White matter volume was negatively associated with
depressive symptoms on the BDI, such that less white matter volume was associated
with more depressive symptoms in adolescent marijuana users only (β = −.59, p < .
03). Although between-group differences were not found in overall white matter
volume, it seems plausible that marijuana use may cause or be linked to subtle
alterations in white matter tracts that are responsible for mood regulation and
depressive symptoms.
Quality of White Matter

Chronic alcoholic adults show clear abnormalities in brain white matter volume as
well as microstructural alterations in white matter tissue organization 40–42. Typically,
less white matter suggests dissipation of myelin-coated axons 43. Diffusion tensor
imaging (DTI) characterizes the integrity of water matter by examining the diffusion
of water molecules in white matter tissue. Therefore, DTI provides information on the
organization of localized white matter fiber tracts. Two commonly used scalar
measurements are fractional anisotropy (FA), which reflects white matter coherence
by providing an estimate of the directionally dependent movement of water
molecules, and mean diffusivity (MD), an index of the overall displacement of water
molecules.
In a preliminary analysis, we looked at the effects of both binge drinking alone and
with combined marijuana use on white matter integrity 44. Forty-two participants (ages
16–19) were identified as controls (n= 14), binge drinkers (≥ 4 drinks on an occasion
for females, ≥ 5 drinks on an occasion for males; n= 14), or binge drink+marijuana

users (n= 14). Adolescent participants received DTI with whole brain coverage.
Diffusion weighted data were collected on a 3-Tesla GE magnetic resonance scanner
(repetition time=12000 ms; echo time=93.4 ms; 36 × 3.0 mm thick axial slices; voxel
resolution 1.875 × 1.875 × 3.0 mm3 , b-value = 2000 s/mm2). Diffusion-weighted
images were acquired in 15 directions, in addition to a normalization image (b=0)
with no diffusion encoding 45. Four volumes were acquired and averaged for each
direction and the b = 0 volume. FA (or MD) maps from each participant were
submitted to Tract-Based Spatial Statistics (TBSS 46), which facilitated voxelwise
between-group comparisons.
Significant group differences were found in eight white matter regions, including
frontal association fibers such as frontal-occipital and superior longitudinal fasciculi.
Bingers and binge+marijuana users displayed lower FA than controls (ps ≤ .016).
Interestingly, bingers demonstrated significantly lower FA than the binge+marijuana
group (ps .014 to .043). No significant MD differences were found in the 8 clusters
identified by the FA analyses. Our findings suggest poorer white matter integrity in
adolescents with histories of binge drinking than non-drinkers. However, teens with
concomitant binge drinking and marijuana use showed a lesser degree of reduced fiber
tract coherence than those engaging in binge drinking alone.
These findings are largely consistent with our previous structural imaging studies that
found small yet significant effects of marijuana use on adolescent brain structure and
function 34, 37, and stronger associations between alcohol use and tissue status. In a
study that looked specifically at adolescents with alcohol use disorders, we found
reduced white matter microstructural integrity compared to demographically matched
youths without alcohol use disorders 47. Significantly lower FA was found in the
splenium of the corpus callosum, and trends for lower FA were also found in the rest
of the corpus callosum, suggesting possible alcohol-related white matter alterations.
The callosal fibers are a massive collection of white matter tissue that connect the left
and right hemispheres of the brain, and are important for efficient transfer of
information. Microstructural changes in the corpus callosum may underlie
neurocognitive changes associated with alcohol use during adolescent brain
maturation. Notably, decreased white-matter integrity was significantly related to
longer duration of heavy alcohol use, greater number of past alcohol withdrawal
symptoms, and recent consumption of large amounts of alcohol.

Overall, our findings of reduced FA suggest possible myelination alterations in brain
regions developing during adolescence, and underscore the impact of the effects of
alcohol on white matter maturation during adolescence. Our more recent findings
indicate that even subtle binge drinking behaviors can have a substantial impact on
tissue development, as adolescents with both alcohol use disorders as well as less
frequent or new-onset binge drinking habits were found to have altered white matter
integrity. Future studies will follow these cohorts over the adolescent years to see if
changes in substance use are followed by changes in indices of white matter quality.
Brain Blood Flow

Understanding cerebral blood flow (CBF) is important since inadequate blood flow
can damage brain tissue. CBF can also influence the blood oxygen dependent signal
interpreted in functional magnetic resonance imaging (fMRI). Moreover, chronic
alcoholics have been shown to have reduced blood flow into the brain 48. In a study
examining CBF in alcohol dependent young women (n=8), we found decreases as
compared to female light drinkers (n=8) using perfusion-weighted magnetic resonance
imaging 49. In these 18–25 year-olds, decreases were seen in six prefrontal and parietal
regions (η2 = .47 to .83), and there were no regions in which perfusion was greater for
alcohol dependent participants compared to controls. These findings may help clarify
the metabolic changes behind differences in functional brain activity seen in
adolescents with histories of alcohol misuse.
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ADOLESCENT SUBSTANCE USE AND BRAIN FUNCTIONING
In addition to alterations in brain structure, recent findings have suggested decrements
in brain functioning associated with adolescent substance use. Functional magnetic
resonance imaging (fMRI) investigates neural activity of the brain by measuring
changes in blood oxygen level dependent (BOLD) signal 50, which indicates areas of
increased activation in response to a mental task or stimulus 51. This technique is
noninvasive and does not require injections or radioactive materials, making it a safe
and appropriate technique for examining adolescent brain functioning.
Spatial Working Memory

Numerous studies involving adult alcoholics suggest neural disruption while
executing cognitive tasks; however, it is unclear to what extent drinking must
progress, and at what age, before abnormalities manifest. Our group 52 found that
adolescents who drank heavily for one to two years showed abnormalities in brain
response on cognitive tasks measuring spatial working memory (SWM) as compared
to light drinkers. While both the heavy and light drinkers performed similarly on the
task, heavy drinkers exhibited increased activation in the parietal lobe, with decreased
activation in the occipital and cerebellar regions, compared to light drinkers 52.
Additionally, youth with more hangover experiences and greater alcohol consumption
showed greater abnormalities. These results suggest that after as little as one to two
years of heavy drinking, adolescents may exhibit subtle neural reorganization that
includes compensation, highlighting the potential early influence of drinking on
neurocognitive functioning during the escalation of alcohol use disorders.
In another study by our lab 53, young adults who had engaged in four to five years of
heavy drinking showed poorer performance on the same SWM task during fMRI, in
addition to decreased activation in parietal and frontal regions. Together, these results
suggest that the adolescent brain may be able to compensate for subtle neural
abnormalities associated with drinking; however, repeated heavy drinking episodes
may interfere with the brain’s ability to make up for alcohol-related deficiencies in
neural functioning.
Additional studies from our laboratory (e.g., 54 compared young adult marijuana users
(ages 16–18) after one month of abstinence to matched controls on the same SWM
task described in the previous studies. Although there were no differences in task
performance between the marijuana users and controls, the marijuana users exhibited
increased activation in parietal, temporal, and frontal (including insula) brain regions.
The marijuana users also showed less activation in cerebellum and occipital cortices
than controls. Findings remained significant after controlling for alcohol and other
drug use, and also suggest compensatory and possibly inefficient SWM-related neural
response associated with marijuana use.
Verbal Encoding

Decrements in verbal encoding abilities have also been observed in binge drinking
adolescents during fMRI tasks involving recall of learned word pairs 55. Compared to
nondrinkers, bingers showed less response in right superior frontal and bilateral

posterior parietal cortices, with more response in occipital cortex, during the verbal
encoding task. This suggests less utilization of working memory systems during
encoding for bingers compared to nondrinkers on tasks of encoding. In addition,
drinkers encoded marginally fewer words than nondrinkers (p=.07), and had no
differential activation to novel stimuli. Together, these results suggest slightly poorer
initial verbal learning, disadvantaged verbal processing, and decelerated learning for
adolescents who engage in binge drinking compared to abstinent adolescents.
Further studies in our laboratory comparing verbal encoding abilities between
adolescents reporting marijuana use and matched controls have found no differences
on task performance. Yet, marijuana users evidence more frontal and less temporal
activation compared to matched controls. Although both groups performed similarly
on the fMRI task, adolescent marijuana users have shown poorer performance on
sensitive measures administered as part of an extensive neuropsychological test
battery (e.g., California Verbal Learning Test-II, Wechsler Memory Scale-III Story
Memory), particularly on initial learning trials 30. Taken together, changes in brain
activation in adolescent marijuana users on a verbal encoding task may be indicative
of less allocation of attentional resources toward encoding the novel material.
Inhibition

In addition to decrements in spatial working memory and verbal encoding, modestly
decreased ability to inhibit behaviors has been found in binge drinking adolescents. A
pilot study from our group 56 found greater BOLD response relative to controls in the
frontal areas and less activation in the cerebellar areas during a go/no-go task of
response inhibition administered during fMRI 57–59, despite similar task performance.
On response selection (“go”) trials, drinkers exhibited less BOLD response than
controls in the mid-cingulate, subcortical, and temporal areas. Better task accuracy
was linked to more frontal response during these trials among controls, but not among
drinkers (p<.025). These findings suggest that even infrequent exposure to large doses
of alcohol may influence inhibitory processing. As with all cross-sectional studies
described, follow-up evaluations will help elucidate the temporal relationship between
inhibition and alcohol use.
We 59 also looked at response inhibition in marijuana users after 28 days of monitored
abstinence, as compared to matched controls. Participants were excluded for any
neurological problems or Axis I diagnoses other than cannabis abuse or dependence.

The study used the same go/no-go task described above, and although marijuana users
performed similarly as controls, they exhibited increased activation on inhibition
(“no-go”) trials in right dorsolateral prefrontal cortex, bilateral medial frontal cortex,
bilateral inferior and superior parietal lobules, and right occipital gyri. On “go” trials,
marijuana users had increased activation in right prefrontal, insular, and parietal
cortices (p<.05, clusters >943 µl). More response during “no-go” trials related to
worse neuropsychological performance (e.g., impulsivity, complex attention,
cognitive flexibility, planning). Neuropsychological indicators of impulsivity were in
turn linked to more medial temporal and less anterior cingulate response in marijuana
users (p<.05). Differences remained even after controlling for lifetime and recent
alcohol use. This suggests that marijuana users have increased brain processing effort
during an inhibition task despite showing intact task performance, even after 28 days
of abstinence. Such increased neural processing effort to achieve inhibition may
predate the onset of regular use, or result from it.
Cue Reactivity

Adolescent response to alcohol advertising is of concern, as they are exposed to
alcohol-related ads on a daily basis in many countries 60. We 61 have observed that
heavy drinking youth show greater brain activation while viewing alcohol
advertisements than they do to non-alcohol beverage ads. This substantially greater
brain activation to alcoholic beverage pictures was observed throughout the brain,
particularly in the prefrontal area, nucleus accumbens, hypothalamus, posterior
cingulate, and temporal lobe, and was prominent in the left hemisphere, limbic, and
visual cortices. This suggests that reward, visual attention limbic, appetitive, and
episodic memory systems were preferentially invoked in response to alcohol ads
relative to non-alcohol ads in heavy drinking teens. Only the inferior frontal gyrus
showed more activation in light drinkers during the task, potentially indicating a
negative valence to these alcohol stimuli in non-drinking teens. Overall, light drinkers
showed more response to non-alcoholic beverage pictures. These findings extend
previous studies in adults, and link alcohol advertisement exposure in youth to
activation in reward, desire, positive emotion, and episodic recall brain areas 62.
Predicting Relapse

Relapse is a common clinical problem in individuals with substance dependence.
Previous studies have implicated a multifactorial process underlying relapse; however,

the contribution of specific neural substrates had yet to be examined. We 63 looked at
whether results from functional imaging shortly after drug cessation could predict
relapse in stimulant dependent individuals. The goals were to evaluate the
neurobiology of decision-making dysfunction in stimulant dependent subjects, and to
determine if functional imaging could be used as a tool to predict relapse.
Participants included treatment seeking methamphetamine dependent adult males
(N=46). All individuals underwent fMRI three to four weeks after cessation of
substance use. Of the 40 subjects who were followed a median of 370 days, 18
relapsed and 22 did not. The main outcome measure was BOLD activation during a
simple two-choice prediction task. During the prediction task, a house was presented,
flanked by a person on its left and right. The participant decided on which side of the
house a car would appear. Each trial was self-paced to maximize self-determined
action, thus the subject determined the number of trials by the latency to select a
response. Immediately following the subject’s response, the car was presented for 300
ms on the far left or right side. The screen provided the feedback whether the
prediction was correct. Unbeknownst to the participant, the computer determined the
response based on the participant’s selection. Three error rate block types included a
high chance level (20% of responses were “correct”), a 50% chance-level, and a low
(80% of responses were “correct”) chance level. The task captures the key elements of
decision-making: the probability of an outcome associated with an option, the positive
or negative consequence, and the magnitude of the consequence 64.
The fMRI activation patterns in right insular, posterior cingulate, and temporal cortex
correctly predicted 20 out of 22 subjects who did not relapse, and 17 out of 18
subjects who did. A Cox regression analysis revealed that the combination of right
middle frontal gyrus, middle temporal gyrus, and posterior cingulate activation best
predicted the time to relapse. In total, this is the first investigation to show that fMRI
can be used to predict relapse in substance dependent individuals. It is likely that
relapse corresponds with less activation in structures that are critical for decisionmaking, and thus poor decision-making sets the stage for relapse. The insular cortex
may act through the interoceptive system to influence ability to differentiate between
good versus poor choices, while the inferior parietal lobule may play a role in poor
assessment of decision-making situations and subsequent reliance on habitual
behavior. Overall, substance dependent adults show brain patterns that can be used to
predict whether and when relapse may occur. Future studies are needed to determine if

this is true for adolescents, and whether brain activation patterns can be used to
evaluate an individuals’ readiness for treatment completion or treatment response.
Summary

Overall, changes in brain functioning in adolescents differ by substance use pattern.
Research has shown that heavy drinking during adolescence can lead to decreased
performance on cognitive tasks of memory, attention, spatial skills, and executive
functioning. These behavioral ramifications of heavy alcohol use may emerge as a
consequence of the reduced volume of important brain structures (e.g., hippocampus),
compromised quality of white matter, and abnormalities in activation during cognitive
tasks. Studies have also shown that marijuana use during adolescence can result in
decreases in cognitive functioning, particularly learning and sequencing scores. In
integrating and interpreting the results of adolescent marijuana studies from our
laboratory, it is important to note that the groups are generally equivalent on task
performance, and therefore the underlying brain responses in controls and users can
be largely assumed to represent activity to the same mental action. Corresponding
marijuana-related changes in cognition may be related to increases in gray matter
tissue volume, decreases in white matter microstructural integrity, and increases in
neuronal activation during cognitive tasks.
In sum, we can reasonably rule out recent use as accounting for the observed
differences between substance groups, given that participants in some studies have
been abstinent one month or greater. Substance using adolescents have been found to
differ from non-users on neuropsychological performance, brain tissue volume, white
matter integrity, and functional brain response. Longitudinal studies are essential to
fully understand how alcohol and marijuana use affect adolescent neurodevelopment.
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METHODOLOGICAL CONSIDERATIONS
The cross-sectional nature of the majority of studies examining adolescent
neurocognitive functioning makes it difficult to determine the influence of alcohol and
drug use on adolescent neurocognition. Therefore, ongoing longitudinal neuroimaging
studies are essential to ascertain the degree to which substance intake is linked
temporally to adverse changes on indices of brain integrity, or whether neural
abnormalities reflect pre-existing patterns. In cross-sectional or longitudinal work,

several methodological features are critical to evaluate the potential influence of
adolescent substance use on neurocognition. These issues pertain to ensuring
participant compliance, accurately assessing potential confounds, and maximizing
participant follow-up.
Adolescent compliance as a research participant can be maximized by attending to
rapport, building trust, and ensuring privacy of self-report data to the extent that is
ethical and feasible to the setting. For behavioral tasks within or outside of imaging, it
is critical to ensure participants comprehend task instructions, are fully trained on
fMRI tasks, and then are given reminders just prior to task administration. Motion
during scan acquisition is detrimental to the quality of imaging data, and is often
worse in younger adolescents than older teens or adults. Adolescent head motion can
be minimized by the following steps: discuss the importance and rationale for keeping
the head still multiple times before and at the scan appointment; model and practice
how to say “yes” and “no” when communicating with the research subject from the
scanner; model and practice techniques for relaxing and ensuring subjects are in a
position suitable for long-term comfort (e.g., legs are not crossed) before scanning
begins; maximize participant comfort by using soft cushions around the head and
under the knees; and many studies, especially those with younger participants, find
practicing scanning in a less expensive mock scanner results in improved participant
comfort and more reliable data during data acquisition.
Accurately measuring and accounting for confounds frequently present in adolescent
substance-using populations is essential for elucidating the true effect of substance use
on adolescent neurocognitive functioning. Common confounds in this population
include head injury, depression, ADHD, conduct disorder, prenatal exposure to
neurotoxins, family history-related effects, and polysubstance involvement.
Conversely, excluding subjects for the aforementioned confounds may impede the
generalizability of results. The tradeoff between minimizing confounds and having
meaningful, ecologically valid results is an important study design decision, especially
given the high cost of fMRI sessions.
Accurately measuring abstinence is another important consideration in substancerelated research protocols. If abstinence is required for participation (and
compensation) in a study, the dynamics of self-report could change. While biological
data may help confirm self-report, these measures are imperfect and do not pinpoint
the quantity of specific timing of substance intake 65, 66. Regarding abstinence from

cannabis, obtaining serial quantitative THC metabolite levels, normalized to
creatinine, is the best approach for guarding against new use episodes 67.
Tracking participants over time is a critical part of many clinical issues when
interested in the degree to which a variable (e.g., alcohol or marijuana use) might
result in neural changes. Although some statistical approaches can help manage
attrition, effective tracking procedures are more desirable to ensure study integrity. To
maximize participant follow-up, frequent contact with participants must be
maintained 68. Having a well-trained, friendly staff experienced with the population
also helps retain participants and parents, and ensures that all participants fully
understand the tasks and expectations during the study. Collecting comprehensive
contact information can help track adolescents over time in case they should relocate.
Additionally, follow-up measures and procedures should be as similar as possible to
baseline, except to mitigate learning and practice effects 69. For imaging studies, field
map unwarping of EPIs (e.g., fMRI and DTI) should also be considered, as this
technique appears to produce more consistent localization of activations 70. Finally, as
technical problems are common, back up plans for each piece of equipment used in
the neuroimaging session should be in place.
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CONCLUSIONS
Current research suggests that substance use in adolescence leads to abnormalities in
brain functioning, including poorer neurocognitive performance, white matter quality,
changes in brain volume, and abnormal neuronal activation patterns. fMRI studies
have illuminated enhanced cue response in adolescent drinkers, and have shown the
potential to predict treatment outcomes in stimulant dependent adults.
A few questions still remain, such as whether heavy substance use during adolescence
causes cognitive impairments and changes in neurodevelopment, if and when are
critical periods of heightened vulnerability to such effects, and if observed
abnormalities remit with reduced use. We have the capability to design studies in
which we restrict or control for nicotine and most other drug use, but few adolescent
drug users do not also use alcohol. It is also important to understand if results
generalize to youth with psychiatric problems, other substance use histories, and low
socioeconomic status, and to further explore implications for changes in brain
activation for learning and behavioral control, along with mood and psychiatric

illness. Harder parametric tasks that include conditions on which behavior does differ
between groups would help us better understand the cognitive domains we have
observed differences on. Lastly, we need to better understand the biochemical changes
that may mediate macrostructural, microstructural, and functional neuronal changes in
response to substance use, such as cannabinoid receptor activity changes. Multimodal
approaches to neuroimaging may help us disentangle such questions (e.g., PET,
spectroscopy).
Our group is currently conducting longitudinal studies of adolescent substance users
as well as youth at risk for substance problems due to family history or early conduct
disorder (minimal use at the time of the first imaging session). Follow-up scan data,
already underway, will elucidate if substance use during the follow-up interval
predicts changes in brain functioning. These investigations will ascertain if: (1)
substance (alcohol and marijuana, predominantly, given sample characteristics) use
during adolescence seems to cause detrimental changes in neurodevelopment, or if (2)
substance use does not account for the differences, the previously observed
differences would likely represent pre-existing markers of risk for heavy substance
use during adolescence.
Because of legal and ethical constraints on alcohol research in human adolescents,
many studies of alcohol’s effects on the developing brain have been conducted in animal
models, primarily rats and mice. The adolescent brain may be uniquely sensitive to
alcohol’s effects because major changes in brain structure and function occur during
this developmental period. For example, adolescent animals are more sensitive than
adults to the effects on memory and learning that result from alcohol’s actions on the
hippocampus. Conversely, adolescent animals appear to be less sensitive than adults to
alcohol-related motor impairment, alcohol-induced sedation, and the development of
seizures during withdrawal. Alcohol exposure during adolescence can have long-lasting
effects and may interfere with normal brain functioning during adulthood.
Key words: adolescent; binge drinking; animal study; animal model; physiological AODE
(alcohol and other drug effects); biological development; brain; brain function; cognition;
learning; memory; motor coordination; AODR (alcohol and other drug related) seizure;
hippocampus; neurotransmitter receptors.

Adolescence and young adulthood are developmental stages of transition during which humans,
as well as members of many other species, mature physically and behaviorally into their adult

state. Adolescents and young adults need to acquire the physical and behavioral skills that will
allow them to live independently of their parents, sustain themselves, and reproduce. This
period is marked by more frequent and sophisticated social interactions with peers, exploration
of new situations and behaviors, and an increased willingness to take risks. In humans, this
often involves the initiation of alcohol and other drug use.

At the same time, the brain undergoes considerable structural and functional changes, at least
in part in response to the individual’s many new experiences. Connections among nerve cells
(neurons) in the brain can change based on which neurons or groups of neurons are regularly
stimulated, a characteristic known as plasticity. This natural process serves to eliminate
unnecessary or unused nerve cell connections,1 allowing the survival of only those neurons that
make meaningful contacts with other neurons. (1 Human infants are born with far more neurons
than are found in the adult brain. Based on a child’s interactions with the environment, the
neurons and connections that are most meaningful can be selected.) This winnowing of neurons
is influenced by, among other factors, the adolescent’s interactions with and experiences in the
outside world.

Adolescence is such a critical phase in brain development that the actions of alcohol and other
drugs on the brain can be assumed to have a particularly profound impact during this
developmental period. Indeed, research has shown that compared with the adult brain, the
adolescent brain is particularly sensitive to some effects of alcohol, yet more resistant to other
effects. Much of this research, especially investigations of specific effects of acute alcohol
administration, has been conducted in animals because studies involving administration of
alcohol to human adolescents are subject to very stringent regulations, and certain studies of
alcohol’s effects on the adolescent brain can be conducted only using animal models. This
article reviews some of the differences in alcohol’s effects on the adolescent and adult brain that
were identified using these animal models. The accompanying article by Tapert and colleagues
summarizes information that has been obtained in studies of human adolescents and young
adults.
MAJOR CHANGES IN BRAIN STRUCTURE AND FUNCTION DURING ADOLESCENCE

Adolescence in humans is broadly defined as the second decade of life, although some
researchers consider ages up to 25 years as “late adolescence.” The corresponding period in
laboratory animals that are frequently used as study subjects is just as loosely defined. In rats it
typically spans postnatal days 30–50 (i.e., PD30–PD50). In both humans and animal models,
adolescence is a period when the brain undergoes extensive remodeling. New connections
among neurons are being formed; at the same time, a substantial number of existing
connections are lost (see Spear 2000). It is hypothesized that this plasticity allows the

individual’s brain to be sculpted based on his or her personal experiences and interactions with
the outside world (Chugani 1998).

One brain region where particularly extensive remodeling occurs is the frontal region of the
outer layer of the brain—the prefrontal cortex—which is thought to be involved in working
memory, voluntary motor behavior, impulse control, rule learning, spatial learning, planning, and
decisionmaking (see Spear 2000; White and Swartzwelder 2005). These changes are especially
extensive in humans. Although the number of neurons and neuronal connections in the
prefrontal cortex appear to decline during adolescence, the relative importance of the frontal
lobes increases.

Developmental changes in the behavioral relevance of certain brain areas are accompanied by
increases or decreases in the activities of chemicals called neurotransmitters, which help
transmit nerve signals from one neuron to another. This signaling takes place when
neurotransmitters released by one neuron bind to protein molecules called receptors on the
surface of the receiving neuron. The interaction between the neurotransmitter and its receptor
initiates chemical and electrical changes in the signal-receiving neuron that influence the
generation of a new nerve signal in that cell. In this way, nerve cells and circuits communicate
and drive behavior. Excitatory neurotransmitters promote the generation of new nerve signals,
whereas inhibitory neurotransmitters make it more difficult to generate a nerve signal in a signalreceiving neuron. Numerous neurotransmitters and their receptors have been identified that act
on specific cells or groups of cells and have specific effects on those cells.

Two important neurotransmitter systems that undergo substantial changes during adolescence
and are affected by alcohol consumption are dopamine and gamma-aminobutyric acid (GABA).
Dopamine can have both excitatory and inhibitory effects, depending on the cells it acts on.
Dopamine-releasing and dopamine-receiving cells are found in numerous brain areas. One
prominent region, which lies deep within the brain, is called the striatum. It consists of several
components that are involved in behaviors such as learning to automatically execute complex
movements triggered by a voluntary command (e.g., driving a car). Another dopamine-using
area is the nucleus accumbens, which plays a role in learning and performing certain behaviors
in response to incentive stimuli (i.e., motivation) (Di Chiara 1997). Activity in the nucleus
accumbens in part accounts for the fact that people perceive the effects of drinking alcohol or
taking other drugs as pleasurable (Di Chiara 1997).

During adolescence, the dopamine system in the striatum appears to undergo substantial
changes. For example, studies in rats have found that dopamine receptor levels in the striatum

increase during early adolescence but then decrease during late adolescence and young
adulthood (Teicher et al. 1995). At the same time, dopamine receptor levels in the nucleus
accumbens increase dramatically.

GABA is the primary inhibitory neurotransmitter in the brain—that is, it represses the activity of
other brain cells. Alcohol generally enhances the effects of GABA on its receptors. This
enhanced GABA activation may play a role in mediating the sedative effects of alcohol and
other sedating agents (Mihic and Harris 1997). In addition, alcohol’s effects on GABA and its
receptors are thought to contribute to the development of tolerance to and dependence on
alcohol (Mihic and Harris 1997). Like dopamine, the GABA system changes substantially during
adolescence. Studies in rats have found that the number of GABA receptors, and thus the
activity of the GABA system, increases markedly in several brain structures during early
adolescence (Moy et al. 1998).

In addition to these two neurotransmitter systems, a system using the neurotransmitter
glutamate also appears to undergo changes during adolescence. Glutamate interacts with
several receptors, including one called the NMDA receptor. Evidence from animal studies
indicates that the NMDA receptor complex changes during postnatal development, and these
changes may continue into adolescence (McDonald et al. 1990).

Although it is beyond the scope of this article to review the changes occurring in various brain
structures and neurotransmitter systems in more detail, this brief description demonstrates that
adolescence is a period of profound alterations in brain function. Therefore, it is reasonable to
expect that alcohol’s effects on the brain and behavior may differ for adolescents and adults.
The following sections will review some of the differences in sensitivity to alcohol that have been
identified using animal models.
ADOLESCENTS ARE MORE SENSITIVE THAN ADULTS TO ALCOHOL’S MEMORYIMPAIRING EFFECTS

Alcohol’s Effects on Memory

Among its many effects on the brain and brain function—such as impairing balance, motor
coordination, and decisionmaking—alcohol interferes with the drinker’s ability to form memories
(i.e., it is an amnestic agent). However, alcohol does not impair all types of memory equally.

Alcohol disrupts a person’s ability to form new, lasting memories to a far greater extent than it
interferes with the ability to recall previously established memories or to hold new information in
memory for just a few seconds (see White and Swartzwelder 2004). One study conducted with
young adults ages 21 to 29 found that intoxicated study participants could recall items on word
lists immediately after the lists were presented, but they had greater difficulty recalling the
information 20 minutes later (Acheson et al. 1998). Interestingly, this effect was much more
powerful in the younger subjects in this age group—that is, people in their early twenties. In
addition, alcohol particularly affects the ability to form explicit memories—that is, memories of
facts (e.g., names and phone numbers) or events (e.g., what the drinker did the previous night).
Because different brain areas play a role in the formation of different types of memories, this
pattern of alcohol-related memory impairment allows researchers to make assumptions about
the brain regions that are most affected by alcohol. Thus, the pattern of memory impairment
observed after intoxication is similar to that found in patients with damage to a brain area called
the hippocampus.

Alcohol and the Hippocampus

The hippocampus is located deep under the brain’s surface (see figure 1) but is extensively
connected with the outer layer of the brain (i.e., the neocortex). It consists of only a few layers of
cells arranged in a characteristic shape with several bends and folds. The primary cells in the
hippocampus are called pyramidal cells because of their shape. The hippocampus can be
divided into several areas, and studies in humans have found that in some patients with an
inability to form new explicit memories, brain damage was limited to a single region of
hippocampal neurons called the CA1 region (Zola-Morgan et al. 1986). In rodents, the activity of
CA1 cells correlates strikingly with behavior: Each CA1 neuron tends to emit signals primarily
when the animal is in a specific area of its environment. For example, cell A may be active
predominantly when the animal is in the northeast corner of its cage, whereas cell B may
become active when the animal enters the southwest corner of the cage. As a result, these cells
can play a very strong and specific role in spatial learning (e.g., the ability to learn the path
through a maze or the location of a certain item, such as a food reward).

Figure 1 Location of the hippocampus, an area
of the brain that appears to be particularly
vulnerable to alcohol's effects. It sits below the
surface of the neocortex in the rat brain (left)
and the human brain.

Researchers have used this characteristic of the CA1 cells to assess the effects of alcohol
exposure and other interventions on hippocampal cell activity in intact, living rodents. In one
study, electrodes were implanted in the hippocampus of rats that then were able to move freely
around their cages. After the animals were administered alcohol, the activities of their CA1 cells
were measured. This study found that the activity of the CA1 cells was reduced when alcohol
levels reached at least 0.5 grams per kilogram (g/kg) of body weight and ceased almost
completely at higher alcohol doses (White and Best 2000). This finding is consistent with the
hypothesis that alcohol can interfere with the formation of new explicit memories by disrupting
hippocampal function.
Alcohol’s Effects on Long-Term Potentiation
In addition to interfering with the activity of CA1 cells, alcohol can impair other hippocampal
functions. One of these, a process called long-term potentiation (LTP), is an experimentally

induced adaptation of the nerve cell connections in response to repeated activation or
stimulation of these connections.2 (2 Although there have been some demonstrations of “LTP-like
phenomena” in the brain during certain types of learning, the term “LTP” itself refers to an
experimentally induced change in brain function.) To illustrate, imagine two neurons in the
hippocampus—a CA1 neuron and a neuron from a region called CA3—that connect in the
hippocampus, with the CA3 neuron sending signals to the CA1 neuron. To transmit the signals,
the CA3 neuron releases a neurotransmitter, which then interacts with receptors on the surface
of the CA1 neuron,3 resulting in the formation of a new nerve signal in the CA1 neuron (see
figure 2). (3 In normal brain function, nerve signals during memory formation are passed from
other areas of the cortex to a region known as dentate gyrus, then to CA3 cells, CA1 cells, and
finally back to the cortex.) The intensity of this signal depends on various factors, including the
number of receptors on the CA1 neuron. When the CA3 neuron first is exposed to a stimulus, it
will emit a signal that leads to a certain level of response in the CA1 neuron. This is called the
baseline response. The CA3 neuron then can be stimulated experimentally in a specific pattern,
a process that resembles what happens during actual learning events. If the original stimulus
subsequently is reapplied to the CA3 neuron, it will evoke a response in the CA1 neuron that is
substantially greater than the response that occurred after the initial stimulation (i.e., the
response is potentiated). In other words, as the result of the patterned stimulation, the CA1 cell
becomes more responsive to signals emitted by the CA3 cell. This potentiated response often
persists for a long period of time, hence the name “long-term” potentiation. There is
accumulating evidence that something like LTP occurs naturally during learning and memory
formation.

Figure 2 Schematic representation of the long-term
potentiation (LTP) process. When a hippocampal CA3
cell is initially stimulated, it releases the neurotransmitter
glutamate, which binds to NMDA receptors on a CA1 cell
and induces a response of a certain size (baseline
response). One mechanism underlying the induction of
LTP may be that when the CA3 cell is repeatedly
stimulated in the proper pattern, the number of glutamate

receptors on the CA1 cell increases and the receptors
become activated. If the original stimulus is then
reapplied to the CA3 cell, the resulting glutamate release
will induce a much greater response in the CA1 cell. This
is called long-term potentiation.

Alcohol has been shown to interfere with LTP during experiments using hippocampal brain
slices from rats. In these experiments, alcohol concentrations corresponding to those achieved
in humans after consuming only one or two drinks interfered with the establishment of LTP
(Blitzer et al. 1990). The brain slices were kept in a special fluid, and two electrodes were
introduced into the tissue, one that allowed stimulation of the CA3 cells and one that recorded
the responses of the CA1 cells. If sufficient alcohol was present in the surrounding fluid during
the repeated patterned stimulation of the CA3 cells, LTP was not detected in the CA1 cells—
that is, their response remained at the baseline level. However, adding alcohol to the fluid after
the patterned stimulation had no effect on LTP, which is consistent with the observation that
alcohol consumption does not impair recall of previously established memories. Although
experiments like this make it tempting to equate LTP with actual learning, it is important to
remember that LTP really is a manifestation of neural plasticity that shares some common
mechanisms with learning. Even though actual learning is certainly more complex than simple
LTP induced in the lab, the LTP process represents an excellent opportunity to study the brain
mechanisms underlying memory and the effects of drugs such as alcohol on these
mechanisms.
One neurotransmitter system involved in the establishment of LTP is the excitatory
neurotransmitter glutamate and its NMDA receptor. When this receptor is activated by
glutamate, it allows calcium to enter the cells. Repeated calcium influx, in turn, sets off a chain
reaction leading to long-lasting changes in the structure and/or function of the cells that cause
LTP. Alcohol has been shown to interfere with activation of the NMDA receptor, thereby reducing
calcium influx and, thus, the subsequent changes in cell function that result in LTP. Researchers
think that this is the main mechanism through which alcohol prevents establishment of LTP,
although other neurotransmitter systems also may play a role (see White and Swartzwelder
2004).
Differential Effects of Acute Alcohol on Memory in Adolescents and Adults
Some evidence suggests that alcohol’s effects on memory and learning are much more severe
in adolescents than in adults. Although difficult to assess in humans, age differences in alcohol’s
effects on memory can be studied in rodents. One approach uses a test called the Morris water
maze task. In this type of experiment, animals are placed in a large circular tank filled with
opaque water. The animals must then locate a platform, submerged about an inch beneath the
surface, where they can rest. The ability to remember the location of the platform across

repeated trials requires activity of the hippocampus; thus, changes in hippocampal function can
be detected by measuring the animal’s ability to learn the location of the platform.
To assess age-dependent effects of alcohol, Markwiese and colleagues (1998) compared the
performance of alcohol-exposed adolescent and adult rats in the Morris water maze task. Each
animal underwent 5 days of training to learn the location of the platform. Before each training
session, one group of animals received no alcohol, and two other groups received one of two
different alcohol doses. The investigators then compared how long it took the alcohol-exposed
and control animals to remember the location of the platform. Among the adult animals, only
those exposed to the highest alcohol concentration showed learning impairments compared
with the control group. In contrast, adolescent animals also showed impairments after they had
received the lower alcohol dose (Markwiese et al. 1998). This experiment demonstrates that
adolescent rats are more vulnerable to alcohol’s effects on memory and learning than are adult
rats. It is not known if the same age-related difference exists in humans, as corresponding
experiments in human adolescents cannot be done for obvious reasons. However, as
mentioned previously, one study comparing people in their early twenties with people in their
late twenties found that the younger age group seemed more vulnerable to alcohol-induced
memory impairment (Acheson et al. 1998).
Researchers also have investigated the mechanisms underlying age-related differences in
sensitivity to alcohol’s effects on memory. These analyses have demonstrated that alcoholinduced inhibition of LTP and of NMDA receptor-mediated activity were greater in brain slices
from adolescent rats than in brain slices from adult rats. For example, in studies using
hippocampal slices taken from adolescent and adult rats, repeated stimulation in the absence of
alcohol induced LTP in samples taken from both age groups (Swartzwelder et al. 1995a; Pyapali
et al. 1999). In fact, in the absence of alcohol, the LTP was more pronounced in adolescent than
in adult brain tissue. When alcohol was added, however, LTP induction was reduced
substantially or almost completely blocked in the adolescent tissue, whereas it took much higher
alcohol concentrations to inhibit the LTP process in tissue from adults.
Similar experiments compared the activity of the glutamate/NMDA system in response to
stimulation in the presence or absence of alcohol in hippocampal brain slices from adolescent
and adult rats. It took significantly higher concentrations of alcohol to reduce NMDA receptor
activity in the adult brain slices, compared with those taken from adolescent animals
(Swartzwelder et al. 1995b).4 (4 Greater sensitivity of the glutamate/NMDA system in
adolescents is not limited to the hippocampus but also is found in other regions of the cortex.)
All of these studies confirm the heightened susceptibility of the adolescent rodent brain to
alcohol-induced inhibition of hippocampal function and memory formation.
ADOLESCENTS ARE LESS SENSITIVE THAN ADULTS TO OTHER ALCOHOL EFFECTS
As the preceding section has shown, adolescent animals are uniquely sensitive to some of
alcohol’s effects on memory. However, adolescents seem less sensitive than adults to other

effects of drinking, such as impairment of motor coordination, sedation, and susceptibility to
seizures during withdrawal.
Motor Coordination
One of the most obvious effects of alcohol consumption in humans as well as laboratory
animals is the impairment of motor activity and coordination. Alcohol interferes with a person’s
ability to perform tasks that require balance and motor coordination, such as standing still,
walking in a straight line, or driving an automobile. In animals, alcohol’s effects on motor
coordination can be demonstrated using the tilting plane test, in which an animal is placed on a
horizontal platform that is gradually tilted, so that the animal must adjust its position to maintain
its balance.
Motor coordination is one of the primary functions of the cerebellum, an area at the base of the
brain. Because the cerebellum continues to develop during adolescence, it is reasonable to
assume that alcohol might affect motor coordination in adolescents differently than in adults. To
investigate this possibility, White and colleagues (2002a) analyzed the motor coordination of
adolescent and adult rats using the tilting plane test before, and at various time points after,
administering alcohol at three different doses (1.0, 2.0, and 3.0 g/kg body weight). These
researchers found that the lowest alcohol dose did not affect the animals’ performance in either
age group. At almost all time points after the administration of the two higher doses, however,
the adult animals were more impaired than the adolescent animals. These findings clearly
demonstrate that, in contrast to alcohol’s effects on memory, adolescent rats appear to be less
sensitive to alcohol’s effects on motor coordination than adult rats. It is not clear precisely why
the adolescent animals were less sensitive to alcohol-induced motor impairment. It is clear,
however, that the cerebellum, which plays a critical role in motor coordination, still is developing
quite rapidly during adolescence. If the cerebellum is less sensitive to alcohol during this period,
this could account for the developmental difference in sensitivity to alcohol. Currently, it is not
known if this difference in sensitivity also applies to human adolescents.
Sedation
Another common effect of alcohol consumption that can be observed both in humans and in
animals is sedation. With increasing alcohol consumption, drinkers tend to become sleepy and
eventually may even pass out. In laboratory animals, sedation can be assessed by observing
the righting reflex that normally helps the animals get back on all four feet if they fall over. When
treated with sedative agents, animals temporarily lose this righting reflex, and the duration of
this loss is a measure of the sedative potency of an agent.
To better characterize alcohol’s effects on the developing organism, researchers also have
evaluated alcohol’s sedative effects in rats of different ages. Little and colleagues (1996)
injected animals from three age groups—juvenile animals (PD20), adolescent animals (PD30),
and adult animals (PD60)—with three different alcohol doses, and found the following:



When treated with the lowest alcohol dose (3 g/kg body weight), none of the adolescent
animals lost their righting reflex, whereas one-half of the juvenile rats and two-thirds of the adult
rats did.



Adolescent animals lost the righting reflex for a significantly shorter period of time than
adult animals. When they regained the reflex, adolescent animals also had significantly higher
blood alcohol concentrations than the adult animals had when they regained the righting reflex.



The juvenile animals also lost the righting reflex for a significantly shorter time than the
adult animals, although not as short as the adolescent animals.
These observations demonstrate that, as with alcohol’s motor-impairing effects, adolescent
animals are substantially less sensitive to alcohol’s sedative effects. Mechanisms that may
contribute to this lower sensitivity are discussed in the following section.
Mechanisms That May Contribute to Reduced Motor-Impairing and Sedative Effects in
Adolescents
Researchers have not yet identified the mechanisms that account for the fact that adolescents
are less susceptible to alcohol-related motor impairment and sedation than older individuals. It
is likely, however, that the neurotransmitter GABA and its receptors play a role in both of these
effects. As mentioned earlier, GABA is an inhibitory neurotransmitter, and the activity of GABA
and its receptors is enhanced by alcohol. As a result, the GABA system has been implicated in
both alcohol’s sedative and its motor-impairing effects. Studies using rats have found that the
levels of GABA receptors in various brain structures, including the cerebellum, increase
markedly throughout adolescence and reach their final levels during early adulthood (Moy et al.
1998). Thus, it appears possible that adolescent rats are less sensitive to alcohol-induced motor
impairment and sedation because, compared with older animals, they have fewer GABA
receptors on which alcohol can act. Another possibility is that the function of GABA receptors is
altered across adolescent development in a way that results in increased sensitivity to alcohol
as the animal gets older.
The combination of reduced sensitivity to alcohol’s motor-impairing and sedative effects on the
one hand and increased sensitivity to alcohol’s memory-impairing effects on the other hand
could be particularly harmful to adolescents. For most people, the maximum amount of alcohol
they can consume is determined by alcohol’s motor-impairing and sedative effects—that is, if
they do not stop drinking voluntarily, drinkers at some point become so incapacitated that they
cannot continue to drink even if they want to. If, like adolescent animals, human adolescents
also are less sensitive to these alcohol effects, it appears plausible that they might continue to
drink longer than adults, achieving higher blood alcohol concentrations in the process. As a
result, the adolescents could become even more vulnerable to the effects of alcohol on memory
and other functions to which they are more susceptible than adults even at lower blood alcohol
levels.
Susceptibility to Seizures During Withdrawal

Like all neurotransmitters, GABA has numerous functions and effects in regulating brain activity.
For example, in addition to playing a role in motor impairment and sedation, GABA also is
involved in the development of seizures during alcohol withdrawal. Long-term drinking causes
the body to adjust to the continued presence of alcohol so that it eventually functions normally
only in the presence of the drug. At that point, cessation of drinking can lead to an array of
adverse symptoms, collectively called withdrawal, which include symptoms mediated by GABA.
Because alcohol stimulates the activity of GABA receptors, long-term drinking causes the brain
to produce fewer of these receptors. If alcohol then is withheld, GABA activity suddenly drops off
because fewer GABA receptors are available and alcohol no longer activates the ones that
remain. This insufficient GABA activity has been linked to the development of seizures during
withdrawal. If adolescents are less sensitive than adults to alcohol’s effects on GABA and its
receptors, adolescents also should be less prone to seizures during withdrawal from alcohol.
This hypothesis has been investigated in rats. For these experiments, Acheson and colleagues
(1999) administered alcohol to adolescent and adult rats for 5 days, then injected the animals
with a chemical that induces seizures and rated the severity and duration of the seizures. The
study found that although adolescent and adult animals experienced seizures of various
severities at a similar rate, the more severe seizures lasted significantly longer in the adult
animals than in the adolescent animals. Thus, this study supports the hypothesis that
adolescent animals are less sensitive than adults to alcohol’s effects on the GABA system.
ALCOHOL EXPOSURE DURING ADOLESCENCE AFFECTS BRAIN FUNCTION DURING
ADULTHOOD
When investigating alcohol’s effects on the adolescent brain, it is important not only to focus on
the immediate effects (e.g., memory impairment, motor impairment, or sedation) but also to
explore the consequences of alcohol use on the adolescent’s future development. Because the
brain undergoes such extensive changes and remodeling during adolescence, it is reasonable
to assume that disruption of these processes by alcohol could lead to long-term alterations that
influence adult behavior and responses to alcohol.
The preceding sections have described how acute alcohol exposure affects the body differently
during adolescence than during adulthood, with adolescents being more sensitive to some
effects of alcohol and less sensitive to others. In addition, adolescents may respond differently
to repeated heavy alcohol exposure, a drinking pattern also known as chronic intermittent
exposure or binge drinking, which is particularly common among adolescents. Binge drinking is
characterized by repeated episodes of heavy drinking followed by withdrawal. Several lines of
evidence suggest that these repeated withdrawal episodes contribute to many of the effects of
chronic alcohol exposure on the brain (see White and Swartzwelder 2004).
In one study of the long-term consequences of binge drinking during adolescence, White and
colleagues (2002b) studied animals that were repeatedly exposed to high levels of alcohol
during adolescence. The alcohol-exposed and control animals were evaluated as adults with
respect to alcohol’s effects on motor activity, using the tilted plane test. As mentioned earlier,

adult rats normally are more sensitive than adolescents to alcohol-induced motor impairment
(i.e., the rats’ sensitivity to motor impairment increases between adolescence and adulthood).
This study found, however, that rats repeatedly exposed to alcohol during adolescence did not
show this increase in sensitivity to alcohol’s effects (White et al. 2002b); these animals
performed as well on the tilted plane test in adulthood as they had in adolescence. In a control
experiment, adult rats were exposed to the same regimen of alcohol administration as were the
adolescent animals. When these adult rats were subsequently tested, their sensitivity to alcoholinduced motor impairment was unchanged despite the repeated alcohol exposure. Thus, it is
not the alcohol treatment per se that leads to reduced sensitivity to motor impairment; instead, it
appears that alcohol exposure during adolescence interferes with the developmental processes
that lead to adult sensitivity to alcohol’s effects on motor coordination.
In a similar experiment, White and colleagues (2000) evaluated how chronic intermittent alcohol
exposure during adolescence affects rats’ spatial memory in adulthood. As discussed earlier,
acute alcohol administration impairs learning and memory more in adolescent animals than it
does in adults. For this experiment, adolescent and adult animals were repeatedly exposed to
high doses of alcohol. When all the animals had reached adulthood, the investigators compared
their ability to learn where to retrieve food in a maze with that of animals which had never
received alcohol. They found that animals in all test groups (i.e., with or without alcohol
administration during adolescence or adulthood) learned to perform the memory task equally
well. However, when the animals received a low dose of alcohol just before being tested on the
memory task, those that had been exposed to alcohol as adolescents performed worse than
animals in the other three groups (White et al. 2000). These results indicate that repeated
alcohol exposure during adolescence enhances the individual’s sensitivity to alcohol’s memoryimpairing effects during adulthood. Similar results were obtained in a study of college students,
which found that students with a history of binge drinking performed worse on memory tasks
after consuming alcohol than did students without such a history (Weissenborn and Duka 2003).
Researchers also have demonstrated the long-term consequences of adolescent alcohol
exposure on adult brain function by measuring the electrical brain activity of adult rats that had
or had not been repeatedly exposed to alcohol during adolescence. Using electrodes implanted
in various regions of the animals’ brains, researchers examined both the electroencephalogram
(EEG), which is a measure of ongoing brain activity, and event-related potentials (ERPs), which
are spikes in brain activity induced by a sudden stimulus (e.g., a light or sound). One of the
studies found that animals which had been exposed to alcohol during adolescence showed
changes in the EEG pattern as well as in ERPs measured in various brain regions, particularly
the hippocampus (Slawecki et al. 2001). These investigators noted that although similar effects
have been reported following long-term alcohol exposure during adulthood, alcohol exposure
during adolescence appears to result in more stable effects, especially on the hippocampus,
after shorter periods of exposure than would be observed in adult animals.
Similar experiments have examined the effects of an acute alcohol dose on the EEG of adult
rats that had or had not been exposed to alcohol repeatedly during adolescence. A study by
Slawecki (2000) found that although the acute alcohol dose significantly altered several EEG

variables in the hippocampus and other brain regions of the control animals, these variables
were not altered in the animals that had been exposed to alcohol during adolescence. In
addition, the alcohol-exposed animals showed fewer behaviors indicative of intoxication in
response to the acute alcohol dose than did the control animals. These findings suggest that
alcohol exposure during adolescence leads to persistent and brain region–specific changes in
electrical brain activity in response to an acute alcohol dose during adulthood. In particular, the
observation that some EEG responses to alcohol were reduced in the alcohol-exposed animals
indicates that adolescent alcohol exposure can produce long-lasting changes in responsiveness
to at least some alcohol effects.
CONCLUSIONS
Various avenues of research have demonstrated that at least in laboratory animals,
adolescence is a unique stage of brain development which is particularly sensitive to the
disrupting effects of alcohol. For example, in rodents, adolescent alcohol exposure increases
the brain’s sensitivity to some alcohol effects (e.g., memory impairment) and decreases
sensitivity to other effects (e.g., motor impairment and sedation). Furthermore, in rodents,
alcohol exposure during adolescence not only has an immediate impact on brain function, it also
may lead to consequences for various brain functions that last even into adulthood. To what
extent these findings are applicable to humans is a matter of debate, particularly because of the
differences between humans and rodents in terms of the plasticity and time course of brain
development. Nevertheless these findings suggest that similar processes might occur in
humans—a conclusion that is especially pertinent and worrisome because adolescence in
humans often is the period when alcohol consumption begins and when particularly dangerous
drinking patterns, such as binge drinking, are common. This combination of frequent high
alcohol consumption and increased vulnerability of the brain to alcohol’s harmful effects may
result in cognitive deficits and other problems that persist far beyond adolescence.
One brain area that seems to be particularly affected by adolescent alcohol consumption is the
hippocampus, which plays a role in numerous cognitive functions, including learning and
memory. In fact, preliminary studies in humans have found that alcohol abuse during
adolescence may be associated with a reduction in the size of the hippocampus (De Bellis et al.
2000), which in turn could be a sign of impaired hippocampal function. Theoretically, alcohol
could lead to cell death in the hippocampus through several mechanisms (e.g., by excessive
activation of the glutamate/NMDA receptor system). Several studies, however, have failed to
detect obvious nerve cell loss after repeated exposure to various patterns of alcohol
administration during adolescence or early adulthood (see White and Swartzwelder 2004).
Other studies, in contrast, have found that high-dose binge exposure to alcohol led to brain
damage in adolescents but not in adults (Crews et al. 2000). These differences in findings may
be accounted for by differences in the rodent strain used; in the pattern, dose, and route of
alcohol administration; and in the brain regions studied. In addition, the long-term behavioral
changes that follow chronic intermittent alcohol exposure during adolescence may involve
subtle changes in neuronal connections which are not easily measurable. Thus, additional
research is necessary to elucidate the exact effects of alcohol on the adolescent hippocampus

and other brain structures and to better understand the long-term implications of adolescent
alcohol exposure.

"Drinking Alcohol Damages Teenagers’ Brains"
by David J. Hanson, Ph. D.

Does drinking in adolescence harm brain development? Does consuming
alcohol before age 21 cause permanent brain damage? Does underage
drinking retard mental development?
Federal agencies warn us that:
“Research indicates that the human brain continues to develop into a
person’s early twenties and that exposure of the developing brain to alcohol
may have long-lasting effects on intellectual capabilities.” 1
“Exposing the brain to alcohol during this period (i.e, before age 21) may
interrupt key processes of brain development” and “alcohol–induced brain
damage may persist.” 2
“The brains and bodies of teens are still developing, and alcohol use can
cause learning problems.” 3
Private interest and activist groups assert that:
“Drinking before the age of 21 can cause irreversible brain damage.”

4

“There is growing evidence to suggest that alcohol use prior to age 21
impairs crucial aspects of youthful brain development” 5
“alcohol can do long-term and irreversible damage to critical neurological
development that is ongoing during the teen-age years and continues until
age 20.” 6
Similarly, newspaper stories tell us:
“research indicates that the brain continues to develop until age 21, and that
young brains can be irreversibly damaged by alcohol.” 7

Research “shows the human brain doesn't stop growing until about age 21
or 22, and that alcohol consumption can alter or retard that growth,
including memory and test-taking ability.” 8
The evidence about teen drinking and potential brain damage comes from
two sources.
(1) The first source of evidence is from lab rats that are typically given very
large doses of alcohol. Large enough quantities of alcohol appear to cause
brain impairment in young rats, especially if given over a long enough period
of time. 9
Interestingly, at lower levels of consumption, the “adolescent” rats tend to
be less susceptible to motor impairment 10 and also less easily sedated than
are older rats. 11The conclusions to be drawn from this for rats’ brains and
alcohol isn’t clear.
A more serious problem is that rats aren’t humans and many if not most
processes found in rats don’t apply at all to humans. For example,
innumerable drugs cure diseases in rats but the vast majority of such drugs
fail to do so in humans.
(2) The second source of evidence comes from humans. However, the
humans who are studied are virtually always alcohol and/or drug dependent
individuals. Not surprisingly, long-time alcohol abusers tend not to do as well
at a variety of mental tasks as those who don’t abuse alcohol. 12
It appears that large enough quantities of alcohol can impair brain
development in rats and that it can also do the same in humans. There’s no
surprising news there.
These studies never deal with light or moderate alcohol consumption among
young humans. However, “natural experiments” on drinking among young
people have been going on for thousands of years around the world.
In many societies most people drink and they begin doing so in the home
from a very early age. Examples familiar to most people include Italians,
Jews, Greeks, Portuguese, French, Germans and Spaniards. 13 There is
neither evidence or any reason to even suspect that members of these
groups are brain impaired compared to those societies that do not permit
young people to consume alcohol.

There appears to be absolutely no evidence whatsoever that the light or
moderateconsumption of alcohol by persons under the age of 21 causes any
brain impairment or harm. Of course, that doesn’t justify breaking any laws.
Federally-funded research does suggest that teens who drink alcohol with
their parents are less likely than others to have either consumed alcohol or
abused it in recent weeks according to a nation-wide study of over 6,200
teenagers in 242 communities across the U.S.
Drinking alcohol with parents “may help teach them responsible drinking
habits or extinguish some of the ‘novelty’ or ‘excitement’ of drinking”
according to senior researcher Dr. Kristie Long Foley of the School of
Medicine at Wake Forest University. Dr. Foley describes drinking with parents
as a “protective” behavior. 14
Contrary to popular belief, drinking with parental approval is legal in many
states across the country. Only seven states prohibit those under age 21
from drinking under all circumstances. 15
Needless to say, no one of any age should ever over-consume
or abuse alcohol.
This website does not provide medical opinion or advice and none should be inferred.

Alcohol can cause alterations in the structure and function of the developing brain, which
continues to mature into a person’s mid 20s, and it may have consequences reaching far
beyond adolescence.
In adolescence, brain development is characterized by dramatic changes to the brain’s
structure, neuron connectivity (i.e., “wiring”), and physiology. These changes in the brain
affect everything from emerging sexuality to emotionality and judgment.
Not all parts of the adolescent brain mature at the same time, which may put an adolescent
at a disadvantage in certain situations. For example, the limbic areas of the brain mature
earlier than the frontal lobes. The limbic areas regulate emotions and are associated with an
adolescent’s lowered sensitivity to risk. The frontal lobes are responsible for self-regulation,
judgment, reasoning, problem-solving, and impulse control. Differences in maturation
among parts of the brain can result in impulsive decisions or actions and a disregard for
consequences.
How Alcohol Affects the Brain
Alcohol affects an adolescent’s brain development in many ways. The effects of underage
drinking on specific brain activities are explained below.

Alcohol is a central nervous system depressant. Alcohol can appear to be a stimulant
because, initially, it depresses the part of the brain that controls inhibitions.
CEREBRAL CORTEX—Alcohol slows down the cerebral cortex as it works with information
from a person’s senses.
CENTRAL NERVOUS SYSTEM—When a person thinks of something he wants his body to
do, the central nervous system—the brain and the spinal cord—sends a signal to that part
of the body. Alcohol slows down the central nervous system, making the person think,
speak, and move slower.
FRONTAL LOBES—The brain’s frontal lobes are important for planning, forming ideas,
making decisions, and using self-control.
When alcohol affects the frontal lobes of the brain, a person may find it hard to control his or
her emotions and urges. The person may act without thinking or may even become violent.
Drinking alcohol over a long period of time can damage the frontal lobes forever.
HIPPOCAMPUS—The hippocampus is the part of the brain where memories are made.


When alcohol reaches the hippocampus, a person may have trouble remembering
something he or she just learned, such as a name or a phone number. This can happen
after just one or two drinks.



Drinking a lot of alcohol quickly can cause a blackout—not being able to remember
entire events, such as what he or she did last night.



If alcohol damages the hippocampus, a person may find it hard to learn and to hold
on to knowledge.
CEREBELLUM—The cerebellum is important for coordination, thoughts, and awareness. A
person may have trouble with these skills when alcohol enters the cerebellum. After drinking
alcohol, a person’s hands may be so shaky that they can’t touch or grab things normally,
and they may lose their balance and fall.
HYPOTHALAMUS—The hypothalamus is a small part of the brain that does an amazing
number of the body’s housekeeping chores. Alcohol upsets the work of the hypothalamus.
After a person drinks alcohol, blood pressure, hunger, thirst, and the urge to urinate
increase while body temperature and heart rate decrease.
MEDULLA—The medulla controls the body’s automatic actions, such as a person’s
heartbeat. It also keeps the body at the right temperature. Alcohol actually chills the body.
Drinking a lot of alcohol outdoors in cold weather can cause a person’s body temperature to
fall below normal. This dangerous condition is called hypothermia.

For teenagers, the effects of a drunken night out may linger long after
the hangover wears off.
A recent study led by neuroscientist Susan Tapert of the University of
California, San Diego compared the brain scans of teens who drink heavily
with the scans of teens who don't.
Tapert's team found damaged nerve tissue in the brains of the teens who
drank. The researchers believe this damage negatively affects attention
span in boys, and girls' ability to comprehend and interpret visual
information.
"First of all, the adolescent brain is still undergoing several maturational
processes that render it more vulnerable to some of the effects of
substances," Tapert says.
In other words, key areas of the brain are still under construction during the
adolescent years, and are more sensitive to the toxic effects of drugs and
alcohol.

Damage to the brain of a teenage drinker, top view
Courtesy of Susan Tapert/Tim McQueeny, UCSD

Thought, Memory Functions Affected
For the study, published last month in the journal Psychology of
Addictive Behaviors, Tapert looked at 12- to 14-year-olds before they
used any alcohol or drugs. Over time, some of the kids started to drink, a
few rather heavily — consuming four or five drinks per occasion, two or
three times a month — classic binge drinking behavior in teens.

Comparing the young people who drank heavily with those who remained
non-drinkers, Tapert's team found that the binge drinkers did worse on
thinking and memory tests. There was also a distinct gender difference.
"For girls who had been engaging in heavy drinking during adolescence, it
looks like they're performing more poorly on tests of spatial functioning,
which links to mathematics, engineering kinds of functions," Tapert says.
And the boys?
"For boys who engaged in binge drinking during adolescence, we see poor
performance on tests of attention — so being able to focus on something
that might be somewhat boring, for a sustained period of time," Tapert
says. "The magnitude of the difference is 10 percent. I like to think of it as
the difference between an A and a B."
Teenage Tendency To Experiment To Blame
Pediatrician and brain researcher Ron Dahl from the University of
Pittsburgh notes that adolescents seem to have a higher tolerance for the
negative immediate effects of binge drinking, such as feeling ill and
nauseated.
"Which makes it easier to consume higher amounts and enjoy some of the
positive aspects," Dahl says. "But, of course, that also creates a liability for
the spiral of addiction and binge use of these substances."
He adds that there is a unique feature of the teenage brain that drives
much behavior during adolescence: The teen brain is primed and ready for
intense, all-consuming learning.
"Becoming passionate about a particular activity, a particular sport,
passionate about literature or changing the world or a particular religion" is
a normal, predictable part of being a teenager, he says.
"But those same tendencies to explore and try new things and try on new
identities may also increase the likelihood of starting on negative
pathways," he adds.
Damaged Brain Tissue

Tapert wanted to find out in what way binge drinking affects a teen's
developing brain. So using brain imaging, she focused on the white matter,
or nerve tissue, of the brain.
"White matter is very important for the relay of information between brain
cells; and we know that it is continuing to develop during adolescence,"
Tapert says.
So Tapert imaged the brains of two groups of high school students: binge
drinkers and a matched group of teens with no history of binge drinking.
She reports in her recent study a marked difference in the white matter of
the binge drinkers.
"They appeared to have a number of little dings throughout their brains'
white matter, indicating poor quality," Tapert says.
And poor quality of the brain's white matter indicates poor, inefficient
communication between brain cells.
"These results were actually surprising to me because the binge drinking
kids hadn't, in fact, engaged in a great deal of binge drinking. They were
drinking on average once or twice a month, but when they did drink, it was
to a relatively high quantity of at least four or five drinks an occasion," she
says.
In another study, Tapert reported abnormal functioning in the hippocampus
— a key area for memory formation — in teen binge drinkers. Reflecting
their abnormal brain scans, the teen drinkers did more poorly on learning
verbal material than their non-drinking counterparts.
What remains unknown, says Tapert, is if the cognitive downward slide in
teenage binge drinkers is reversible.

Dynamic changes in neurochemistry, fiber architecture, and tissue composition
occur in the adolescent brain. The course of these maturational processes is being
charted with greater specificity, owing to advances in neuroimaging and indicate

grey matter volume reductions and protracted development of white matter in
regions known to support complex cognition and behavior. Though frontosubcortical circuitry development is notable during adolescence, asynchronous
maturation of prefrontal and limbic systems may render youth more vulnerable to
risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption
and comorbid marijuana use are common among adolescents, and are associated
with neural consequences. This review summarizes the unique characteristics of
adolescent brain development, particularly aspects that predispose individuals to
reward seeking and risky choices during this phase of life, and discusses the
influence of substance use on neuromaturation. Together, findings in this arena
underscore the importance of refined research and programming efforts in
adolescent health and interventional needs.
Keywords: Adolescence, Substance use, Alcohol, Marijuana, Risk taking,

Neuromaturation

Introduction
Adolescence is a time of subtle, yet dynamic brain changes that occur in the
context of major physiological, psychological, and social transitions. This juncture
marks a gradual

Neuropsychology Review
Springer

Adolescent Brain Development and the Risk for Alcohol and Other
Drug Problems
Sunita Bava and Susan F. Tapert

Additional article information

Abstract
Dynamic changes in neurochemistry, fiber architecture, and tissue composition
occur in the adolescent brain. The course of these maturational processes is being
charted with greater specificity, owing to advances in neuroimaging and indicate
grey matter volume reductions and protracted development of white matter in
regions known to support complex cognition and behavior. Though frontosubcortical circuitry development is notable during adolescence, asynchronous
maturation of prefrontal and limbic systems may render youth more vulnerable to
risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption
and comorbid marijuana use are common among adolescents, and are associated
with neural consequences. This review summarizes the unique characteristics of
adolescent brain development, particularly aspects that predispose individuals to
reward seeking and risky choices during this phase of life, and discusses the
influence of substance use on neuromaturation. Together, findings in this arena
underscore the importance of refined research and programming efforts in
adolescent health and interventional needs.
Keywords: Adolescence, Substance use, Alcohol, Marijuana, Risk

taking, Neuromaturation

Introduction
Adolescence is a time of subtle, yet dynamic brain changes that occur in the
context of major physiological, psychological, and social transitions. This juncture
marks a gradual shift from guided to independent functioning that is analogized in

the protracted development of brain structure. Growth of the prefrontal cortex,
limbic system structures, and white matter association fibers during this period are
linked with more sophisticated cognitive functions and emotional processing,
useful for navigating an increasingly complex psychosocial environment. Despite
these developmental advances, increased tendencies toward risk-taking and
heightened vulnerability to psychopathology are well known within the adolescent
milieu. Owing in large part to progress and innovation in neuroimaging techniques,
appreciable levels of new information on adolescent neurodevelopment are
breaking ground. The potential of these methods to identify biomarkers for
substance problems and targets for addiction treatment in youth are of significant
value when considering the rise in adolescent alcohol and drug use and decline in
perceived risk of substance exposure (Spear 2010).
What are the unique characteristics of the adolescent brain? What neural and
behavioral profiles render youth at heightened risk for substance use problems, and
are neurocognitive consequences to early substance use observable? Recent efforts
have explored these questions and brought us to a fuller understanding of
adolescent health and interventional needs. This paper will review
neurodevelopmental processes during adolescence, discuss the influence of
substance use on neuromaturation as well as probable mechanisms by which these
substances influence neural development, and briefly summarize factors that may
enhance risk-taking tendencies. Finally, we will conclude with suggestions for
future research directions.

Adolescent Brain Development

Overall brain size changes little beyond early school age (Pfefferbaum et al. 1994),
though the adolescent brain continues to undergo considerable maturation (BarneaGoraly et al. 2005; Paus et al. 1999; Sowell et al. 1999). Changes in cortical
volume occur alongside axonal growth and refinement of cortical connections
(Huttenlocher and Dabholkar 1997; Yakovlev and Lecours 1967). Maturing neural
circuitry, particularly in the prefrontal cortex, limbic system, and white matter
association and projection fibers is linked with advancements in cognition and
behavior, but also renders the adolescent brain vulnerable to unhealthy
environmental influences.

Grey Matter
Neuropsychology Review
Springer

Adolescent Brain Development and the Risk for Alcohol and Other
Drug Problems
Sunita Bava and Susan F. Tapert
Additional article information

Abstract
Dynamic changes in neurochemistry, fiber architecture, and tissue composition
occur in the adolescent brain. The course of these maturational processes is being
charted with greater specificity, owing to advances in neuroimaging and indicate
grey matter volume reductions and protracted development of white matter in
regions known to support complex cognition and behavior. Though fronto-

subcortical circuitry development is notable during adolescence, asynchronous
maturation of prefrontal and limbic systems may render youth more vulnerable to
risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption
and comorbid marijuana use are common among adolescents, and are associated
with neural consequences. This review summarizes the unique characteristics of
adolescent brain development, particularly aspects that predispose individuals to
reward seeking and risky choices during this phase of life, and discusses the
influence of substance use on neuromaturation. Together, findings in this arena
underscore the importance of refined research and programming efforts in
adolescent health and interventional needs.
Keywords: Adolescence, Substance use, Alcohol, Marijuana, Risk

taking, Neuromaturation

Introduction
Adolescence is a time of subtle, yet dynamic brain changes that occur in the
context of major physiological, psychological, and social transitions. This juncture
marks a gradual shift from guided to independent functioning that is analogized in
the protracted development of brain structure. Growth of the prefrontal cortex,
limbic system structures, and white matter association fibers during this period are
linked with more sophisticated cognitive functions and emotional processing,
useful for navigating an increasingly complex psychosocial environment. Despite
these developmental advances, increased tendencies toward risk-taking and
heightened vulnerability to psychopathology are well known within the adolescent
milieu. Owing in large part to progress and innovation in neuroimaging techniques,
appreciable levels of new information on adolescent neurodevelopment are

breaking ground. The potential of these methods to identify biomarkers for
substance problems and targets for addiction treatment in youth are of significant
value when considering the rise in adolescent alcohol and drug use and decline in
perceived risk of substance exposure (Spear 2010).
What are the unique characteristics of the adolescent brain? What neural and
behavioral profiles render youth at heightened risk for substance use problems, and
are neurocognitive consequences to early substance use observable? Recent efforts
have explored these questions and brought us to a fuller understanding of
adolescent health and interventional needs. This paper will review
neurodevelopmental processes during adolescence, discuss the influence of
substance use on neuromaturation as well as probable mechanisms by which these
substances influence neural development, and briefly summarize factors that may
enhance risk-taking tendencies. Finally, we will conclude with suggestions for
future research directions.

Adolescent Brain Development
Overall brain size changes little beyond early school age (Pfefferbaum et al. 1994),
though the adolescent brain continues to undergo considerable maturation (BarneaGoraly et al. 2005; Paus et al. 1999; Sowell et al. 1999). Changes in cortical
volume occur alongside axonal growth and refinement of cortical connections
(Huttenlocher and Dabholkar 1997; Yakovlev and Lecours 1967). Maturing neural
circuitry, particularly in the prefrontal cortex, limbic system, and white matter
association and projection fibers is linked with advancements in cognition and
behavior, but also renders the adolescent brain vulnerable to unhealthy
environmental influences.

Grey Matter
The developmental trajectory of grey matter follows an inverted parabolic curve,
with cortical volume peaking, on average, around ages 12–14, followed by a
decline in volume and thickness over adolescence (Giedd et al. 1999; Gogtay et
al. 2004; Sowell et al.2003). Widespread supratentorial diminutions are evident,
but show temporal variance across regions (Wilke et al. 2007). Declines begin in
the striatum and sensorimotor cortices (Jernigan and Tallal 1990; Jernigan et
al. 1991; Sowell et al. 1999), progress rostrally to the frontal poles, then end with
the dorsolateral prefrontal cortex (Gogtay et al. 2004; Sowell et al. 2002b), which
is also late to myelinate (Paus et al. 1999). Longitudinal charting of brain
volumetry (Giorgio et al. 2010) from 13–22 years of age reveals specific declines
in medial parietal cortex, posterior temporal and middle frontal gyri, and the
cerebellum in the right hemisphere, coinciding with previous studies showing these
regions to develop late into adolescence (Giedd 2004; Gogtay et al. 2004; Sowell
et al. 2002a, b). Examination of developmental changes in cortical thickness from
8–30 years of age indicates a similar pattern of nonlinear declines, with marked
thinning during adolescence. Attenuations are most notable in the parietal lobe, and
followed in effect size by medial and superior frontal regions, the cingulum, and
occipital lobe (Tamnes et al. 2009).
The mechanisms underlying cortical volume and thickness decline are suggested to
involve selective synaptic pruning of superfluous neuronal connections, reduction
in glial cells, decrease in neuropil and intra-cortical myelination (Huttenlocher and
Dabholkar 1997; Paus et al. 2008; Shaw et al. 2008; Tamnes et al. 2009). Regional
variations in grey matter maturation may coincide with different patterns of

cortical development, with allocortex, including the piriform area, showing
primarily linear growth patterns, compared to transition cortex (orbitofrontal,
insular, cingulate, entorhinal, and perirhinal regions) demonstrating a combination
of linear and quadratic trajectories, and isocortex (medial and lateral prefrontal,
precentral motor, somatosensory, lateral temporal, and lateral occipital regions)
demonstrating cubic growth curves (Shaw et al. 2008). Though the functional
implications of these developmental trajectories are unclear, isocortical regions
undergo more protracted development and support complex behavioral functions.
Their growth curves may reflect critical periods for development of cognitive skills
as well as windows of vulnerability

Neuropsychology Review
Springer

Adolescent Brain Development and the Risk for Alcohol and Other
Drug Problems
Sunita Bava and Susan F. Tapert
Additional article information

Abstract
Dynamic changes in neurochemistry, fiber architecture, and tissue composition
occur in the adolescent brain. The course of these maturational processes is being
charted with greater specificity, owing to advances in neuroimaging and indicate
grey matter volume reductions and protracted development of white matter in
regions known to support complex cognition and behavior. Though frontosubcortical circuitry development is notable during adolescence, asynchronous

maturation of prefrontal and limbic systems may render youth more vulnerable to
risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption
and comorbid marijuana use are common among adolescents, and are associated
with neural consequences. This review summarizes the unique characteristics of
adolescent brain development, particularly aspects that predispose individuals to
reward seeking and risky choices during this phase of life, and discusses the
influence of substance use on neuromaturation. Together, findings in this arena
underscore the importance of refined research and programming efforts in
adolescent health and interventional needs.
Keywords: Adolescence, Substance use, Alcohol, Marijuana, Risk

taking, Neuromaturation

Introduction
Adolescence is a time of subtle, yet dynamic brain changes that occur in the
context of major physiological, psychological, and social transitions. This juncture
marks a gradual shift from guided to independent functioning that is analogized in
the protracted development of brain structure. Growth of the prefrontal cortex,
limbic system structures, and white matter association fibers during this period are
linked with more sophisticated cognitive functions and emotional processing,
useful for navigating an increasingly complex psychosocial environment. Despite
these developmental advances, increased tendencies toward risk-taking and
heightened vulnerability to psychopathology are well known within the adolescent
milieu. Owing in large part to progress and innovation in neuroimaging techniques,
appreciable levels of new information on adolescent neurodevelopment are
breaking ground. The potential of these methods to identify biomarkers for

substance problems and targets for addiction treatment in youth are of significant
value when considering the rise in adolescent alcohol and drug use and decline in
perceived risk of substance exposure (Spear 2010).
What are the unique characteristics of the adolescent brain? What neural and
behavioral profiles render youth at heightened risk for substance use problems, and
are neurocognitive consequences to early substance use observable? Recent efforts
have explored these questions and brought us to a fuller understanding of
adolescent health and interventional needs. This paper will review
neurodevelopmental processes during adolescence, discuss the influence of
substance use on neuromaturation as well as probable mechanisms by which these
substances influence neural development, and briefly summarize factors that may
enhance risk-taking tendencies. Finally, we will conclude with suggestions for
future research directions.

Adolescent Brain Development
Overall brain size changes little beyond early school age (Pfefferbaum et al. 1994),
though the adolescent brain continues to undergo considerable maturation (BarneaGoraly et al. 2005; Paus et al. 1999; Sowell et al. 1999). Changes in cortical
volume occur alongside axonal growth and refinement of cortical connections
(Huttenlocher and Dabholkar 1997; Yakovlev and Lecours 1967). Maturing neural
circuitry, particularly in the prefrontal cortex, limbic system, and white matter
association and projection fibers is linked with advancements in cognition and
behavior, but also renders the adolescent brain vulnerable to unhealthy
environmental influences.

Grey Matter
The developmental trajectory of grey matter follows an inverted parabolic curve,
with cortical volume peaking, on average, around ages 12–14, followed by a
decline in volume and thickness over adolescence (Giedd et al. 1999; Gogtay et
al. 2004; Sowell et al.2003). Widespread supratentorial diminutions are evident,
but show temporal variance across regions (Wilke et al. 2007). Declines begin in
the striatum and sensorimotor cortices (Jernigan and Tallal 1990; Jernigan et
al. 1991; Sowell et al. 1999), progress rostrally to the frontal poles, then end with
the dorsolateral prefrontal cortex (Gogtay et al. 2004; Sowell et al. 2002b), which
is also late to myelinate (Paus et al. 1999). Longitudinal charting of brain
volumetry (Giorgio et al. 2010) from 13–22 years of age reveals specific declines
in medial parietal cortex, posterior temporal and middle frontal gyri, and the
cerebellum in the right hemisphere, coinciding with previous studies showing these
regions to develop late into adolescence (Giedd 2004; Gogtay et al. 2004; Sowell
et al. 2002a, b). Examination of developmental changes in cortical thickness from
8–30 years of age indicates a similar pattern of nonlinear declines, with marked
thinning during adolescence. Attenuations are most notable in the parietal lobe, and
followed in effect size by medial and superior frontal regions, the cingulum, and
occipital lobe (Tamnes et al. 2009).
The mechanisms underlying cortical volume and thickness decline are suggested to
involve selective synaptic pruning of superfluous neuronal connections, reduction
in glial cells, decrease in neuropil and intra-cortical myelination (Huttenlocher and
Dabholkar 1997; Paus et al. 2008; Shaw et al. 2008; Tamnes et al. 2009). Regional
variations in grey matter maturation may coincide with different patterns of

cortical development, with allocortex, including the piriform area, showing
primarily linear growth patterns, compared to transition cortex (orbitofrontal,
insular, cingulate, entorhinal, and perirhinal regions) demonstrating a combination
of linear and quadratic trajectories, and isocortex (medial and lateral prefrontal,
precentral motor, somatosensory, lateral temporal, and lateral occipital regions)
demonstrating cubic growth curves (Shaw et al. 2008). Though the functional
implications of these developmental trajectories are unclear, isocortical regions
undergo more protracted development and support complex behavioral functions.
Their growth curves may reflect critical periods for development of cognitive skills
as well as windows of vulnerability for neurotoxic exposure or other
developmental perturbations.

White Matter
In contrast to grey matter reductions, white matter across the adolescent years
shows growth and enhancement of pathways (Giedd 2008; Yakovlev and
Lecours 1967). This is reflected in white matter volume increase, particularly in
fronto-parietal regions (Benes1989; Huttenlocher 1990; Nagel et al. 2006;
Yakovlev and Lecours 1967). Diffusion tensor imaging (DTI), a neuroimaging
technique that has gained widespread use over the past decade, relies on the
intrinsic diffusion properties of water molecules and has afforded a view into the
more subtle microstructural changes that occur in white matter architecture. Two
common scalar variables derived from DTI are fractional anisotropy (FA), which
describes the directional variance of diffusional motion, and mean diffusivity
(MD), an indicator of the overall magnitude of diffusional motion. These measures
index relationships between signal intensity changes and underlying tissue

structure, and provide descriptions of white matter quality and architecture
(Conturo et al. 1999; Pierpaoli and Basser 1996; Shimony et al. 1999). High FA
reflects greater fiber organization and coherence, myelination and/or other
structural components of the axon, and low MD values suggest greater white
matter density (Roberts and Schwartz2007). Studies of typically developing
adolescents show increases in FA and decreases in MD. These trends continue
through early adulthood in a nearly linear manner (Barnea-Goraly et al. 2005;
Bonekamp et al. 2007; Mukherjee et al. 2001; Schmithorst et al.2002), though
recent data suggest an exponential pattern of anisotropic increase that may plateau
during the late-teens to early twenties (Lebel et al. 2008).
Areas with the most prominent FA change during adolescence are the superior
longitudinal fasciculus, superior corona radiata, thalamic radiations, and posterior
limb of the internal capsule (see Fig. 1) (Bava et al. 2010b). Other projection and
association pathways including the corticospinal tract, arcuate fasciculus,
cingulum, corpus callosum, superior and mid-temporal white matter, and inferior
parietal white matter show anisotropic increases as well (Ashtari et al. 2007;
Bonekamp et al. 2007; Giorgio et al. 2010; Giorgio et al. 2008; Tamnes et
al. 2009). Changes in subcortical and deep grey matter fibers are more pronounced,
with less change in compact white matter tracts comprising highly parallel fibers
such as the internal capsule and corpus callosum (Bava

Neuropsychology Review
Springer

Adolescent Brain Development and the Risk for Alcohol and Other
Drug Problems
Sunita Bava and Susan F. Tapert
Additional article information

Abstract
Dynamic changes in neurochemistry, fiber architecture, and tissue composition
occur in the adolescent brain. The course of these maturational processes is being
charted with greater specificity, owing to advances in neuroimaging and indicate
grey matter volume reductions and protracted development of white matter in
regions known to support complex cognition and behavior. Though frontosubcortical circuitry development is notable during adolescence, asynchronous
maturation of prefrontal and limbic systems may render youth more vulnerable to
risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption
and comorbid marijuana use are common among adolescents, and are associated
with neural consequences. This review summarizes the unique characteristics of
adolescent brain development, particularly aspects that predispose individuals to
reward seeking and risky choices during this phase of life, and discusses the
influence of substance use on neuromaturation. Together, findings in this arena
underscore the importance of refined research and programming efforts in
adolescent health and interventional needs.
Keywords: Adolescence, Substance use, Alcohol, Marijuana, Risk

taking, Neuromaturation

Introduction

Adolescence is a time of subtle, yet dynamic brain changes that occur in the
context of major physiological, psychological, and social transitions. This juncture
marks a gradual shift from guided to independent functioning that is analogized in
the protracted development of brain structure. Growth of the prefrontal cortex,
limbic system structures, and white matter association fibers during this period are
linked with more sophisticated cognitive functions and emotional processing,
useful for navigating an increasingly complex psychosocial environment. Despite
these developmental advances, increased tendencies toward risk-taking and
heightened vulnerability to psychopathology are well known within the adolescent
milieu. Owing in large part to progress and innovation in neuroimaging techniques,
appreciable levels of new information on adolescent neurodevelopment are
breaking ground. The potential of these methods to identify biomarkers for
substance problems and targets for addiction treatment in youth are of significant
value when considering the rise in adolescent alcohol and drug use and decline in
perceived risk of substance exposure (Spear 2010).
What are the unique characteristics of the adolescent brain? What neural and
behavioral profiles render youth at heightened risk for substance use problems, and
are neurocognitive consequences to early substance use observable? Recent efforts
have explored these questions and brought us to a fuller understanding of
adolescent health and interventional needs. This paper will review
neurodevelopmental processes during adolescence, discuss the influence of
substance use on neuromaturation as well as probable mechanisms by which these
substances influence neural development, and briefly summarize factors that may
enhance risk-taking tendencies. Finally, we will conclude with suggestions for
future research directions.

Adolescent Brain Development
Overall brain size changes little beyond early school age (Pfefferbaum et al. 1994),
though the adolescent brain continues to undergo considerable maturation (BarneaGoraly et al. 2005; Paus et al. 1999; Sowell et al. 1999). Changes in cortical
volume occur alongside axonal growth and refinement of cortical connections
(Huttenlocher and Dabholkar 1997; Yakovlev and Lecours 1967). Maturing neural
circuitry, particularly in the prefrontal cortex, limbic system, and white matter
association and projection fibers is linked with advancements in cognition and
behavior, but also renders the adolescent brain vulnerable to unhealthy
environmental influences.

Grey Matter
The developmental trajectory of grey matter follows an inverted parabolic curve,
with cortical volume peaking, on average, around ages 12–14, followed by a
decline in volume and thickness over adolescence (Giedd et al. 1999; Gogtay et
al. 2004; Sowell et al.2003). Widespread supratentorial diminutions are evident,
but show temporal variance across regions (Wilke et al. 2007). Declines begin in
the striatum and sensorimotor cortices (Jernigan and Tallal 1990; Jernigan et
al. 1991; Sowell et al. 1999), progress rostrally to the frontal poles, then end with
the dorsolateral prefrontal cortex (Gogtay et al. 2004; Sowell et al. 2002b), which
is also late to myelinate (Paus et al. 1999). Longitudinal charting of brain
volumetry (Giorgio et al. 2010) from 13–22 years of age reveals specific declines
in medial parietal cortex, posterior temporal and middle frontal gyri, and the
cerebellum in the right hemisphere, coinciding with previous studies showing these
regions to develop late into adolescence (Giedd 2004; Gogtay et al. 2004; Sowell

et al. 2002a, b). Examination of developmental changes in cortical thickness from
8–30 years of age indicates a similar pattern of nonlinear declines, with marked
thinning during adolescence. Attenuations are most notable in the parietal lobe, and
followed in effect size by medial and superior frontal regions, the cingulum, and
occipital lobe (Tamnes et al. 2009).
The mechanisms underlying cortical volume and thickness decline are suggested to
involve selective synaptic pruning of superfluous neuronal connections, reduction
in glial cells, decrease in neuropil and intra-cortical myelination (Huttenlocher and
Dabholkar 1997; Paus et al. 2008; Shaw et al. 2008; Tamnes et al. 2009). Regional
variations in grey matter maturation may coincide with different patterns of
cortical development, with allocortex, including the piriform area, showing
primarily linear growth patterns, compared to transition cortex (orbitofrontal,
insular, cingulate, entorhinal, and perirhinal regions) demonstrating a combination
of linear and quadratic trajectories, and isocortex (medial and lateral prefrontal,
precentral motor, somatosensory, lateral temporal, and lateral occipital regions)
demonstrating cubic growth curves (Shaw et al. 2008). Though the functional
implications of these developmental trajectories are unclear, isocortical regions
undergo more protracted development and support complex behavioral functions.
Their growth curves may reflect critical periods for development of cognitive skills
as well as windows of vulnerability for neurotoxic exposure or other
developmental perturbations.

White Matter
In contrast to grey matter reductions, white matter across the adolescent years
shows growth and enhancement of pathways (Giedd 2008; Yakovlev and

Lecours 1967). This is reflected in white matter volume increase, particularly in
fronto-parietal regions (Benes1989; Huttenlocher 1990; Nagel et al. 2006;
Yakovlev and Lecours 1967). Diffusion tensor imaging (DTI), a neuroimaging
technique that has gained widespread use over the past decade, relies on the
intrinsic diffusion properties of water molecules and has afforded a view into the
more subtle microstructural changes that occur in white matter architecture. Two
common scalar variables derived from DTI are fractional anisotropy (FA), which
describes the directional variance of diffusional motion, and mean diffusivity
(MD), an indicator of the overall magnitude of diffusional motion. These measures
index relationships between signal intensity changes and underlying tissue
structure, and provide descriptions of white matter quality and architecture
(Conturo et al. 1999; Pierpaoli and Basser 1996; Shimony et al. 1999). High FA
reflects greater fiber organization and coherence, myelination and/or other
structural components of the axon, and low MD values suggest greater white
matter density (Roberts and Schwartz2007). Studies of typically developing
adolescents show increases in FA and decreases in MD. These trends continue
through early adulthood in a nearly linear manner (Barnea-Goraly et al. 2005;
Bonekamp et al. 2007; Mukherjee et al. 2001; Schmithorst et al.2002), though
recent data suggest an exponential pattern of anisotropic increase that may plateau
during the late-teens to early twenties (Lebel et al. 2008).
Areas with the most prominent FA change during adolescence are the superior
longitudinal fasciculus, superior corona radiata, thalamic radiations, and posterior
limb of the internal capsule (see Fig. 1) (Bava et al. 2010b). Other projection and
association pathways including the corticospinal tract, arcuate fasciculus,
cingulum, corpus callosum, superior and mid-temporal white matter, and inferior

parietal white matter show anisotropic increases as well (Ashtari et al. 2007;
Bonekamp et al. 2007; Giorgio et al. 2010; Giorgio et al. 2008; Tamnes et
al. 2009). Changes in subcortical and deep grey matter fibers are more pronounced,
with less change in compact white matter tracts comprising highly parallel fibers
such as the internal capsule and corpus callosum (Bava et al. 2010b; Lebel et
al. 2008). Fiber tracts constituting the fronto-temporal pathways appear to mature
relatively later (Schneiderman et al. 2007; Tamnes et al. 2009), though comparison
of growth rates among tracts comes largely from cross-sectional data that present
developmental trends.

Fig. 1
Clusters of significant change in the superior longitudinal fasciculus over
time in adolescents age 17.5 to 19 (≥153 μl, p < .01; N = 22) (Bava et
al. 2010a, b). Results are superimposed ...

The neurobiological mechanisms contributing to FA increases and MD decreases
during adolescence are not entirely understood, but examination of underlying
diffusion dynamics point to some probable processes. For example, decreases in
radial diffusivity (RD), diffusion that occurs perpendicular to white matter
pathways, suggests increased myelination, axonal density, and fiber compactness
(Giorgio et al. 2008; Snook et al.2005), but have not been uniformly observed to
occur during adolescence. Similarly, changes in axial diffusivity (AD), diffusion
parallel to the fibers’ principle axis, show discrepant trends, with some studies
documenting decreases (Eluvathingal et al. 2007; Lebel et al. 2008; Suzuki et
al. 2003), and others increases in this index (Ashtari et al.2007; Giorgio et

al. 2010). Decreases in AD may be attributable to developing axon collaterals,
whereas increases may reflect growth in axon diameter, processes which are both
likely to occur during adolescence. Technical and demographic differences such as
imaging parameters, inter-scan intervals, age range, and gender ratios may account
for divergent findings.
Both grey matter volume decreases and FA increases in frontoparietal regions
occur well into adolescence, suggesting a close spatiotemporal relationship
(Gogtay et al. 2004; Lebel et al. 2008). Changes in tissue morphometry are
attributable to synaptic proliferation and pruning (Huttenlocher 1979) as well as
myelination. Diminutions in gray matter density and concomitant brain growth in
dorsal parietal and frontal regions suggest an interplay between regressive and
progressive changes (Sowell et al. 2001), and the coupling of these neurobiological
processes is associated with increasingly economical neural activity (Huttenlocher
and Dabholkar 1997).

Sexual Dimorphisms in Brain Structure