The Teen Brain
Jay N. Giedd, MDChild Psychiatry, NIMH
Bethesda, MD, USA
Workshop on the
Mechanism of Brain and
Mind
Kobe, Japan
August 22, 2011

Short talk, huh?

Oh, you mean
they found one?

Isn’t that acontradictionof terms?

What is your next talk on –the Loch Ness Monster?

The adolescent brain is not a
broken or defective adult brain.
It is exquisitely forged by theforces of our evolutionary
history to have different featurescompared to children or adults.

Adolescent Behavioral Changes
in Social Mammals• Increased risk taking• Increased sensation seeking• Greater peer affiliation
Facilitate separation from natal family?
Less inbreeding = evolutionary advantage?

Hall of Human Origins(Smithsonian Museum, Washington DC)

Brain volume increase driven bychange in environment

The Double Edged Sword of
Adolescent Brain Plasticity

Opportunity
Vulnerability

NIMH Child Psychiatry Branch
Data Base (1991-present)• Longitudinal Assessment (~ 2 year intervals)– Imaging (sMRI, fMRI, MEG, DTI, MTI)
– Genetics– Neuropsychological / Clinical• 8000+ Scans from 3000+ Subjects– ~ ½ Typically-Developing• ~ ½ Twins– 25 Clinical Populations• ADHD, Autism Spectrum, Autism Savants,, Bipolar
Disorder, Childhood Onset Schizophrenia, Depression,
OCD, PANDAS, Sex Chromosome Variations (XXY, XXX,
XXY, XXYY, XXXXY), Tourette’s Syndrome, …

Long Term Strategy•Map Trajectories•Discern Influences•Improve Lives

How the Brain Looks to MRIPart 1 – Mapping Trajectories ofAnatomic Brain Development•White Matter• Gray Matter

The Neuron
Dendrites

Axon
Cell body(the cell’s life
support center)

Terminal
branches ofaxon

Neuronal Impulse
MyelinsheathDonald Bliss, MAPB, Medical Illustration

White Matter
White Matter
Nucleus
Axon
Oligodendroglia

Male (152 scans from 90 subjects)
Female (91 scans from 55 subjects)
95% Confidence Intervals

Age in years

Myelin  Increased Bandwidth
Speed 100x, Refractory Period 1/30xSignal “hops” between nodes of Ranvier

Dynamic White Matter Changes
during Pediatric Development• Newborns: few myelinated axons• Different regions at differentages– Wernicke (language
comprehension)– Broca (speech production) –6 months later (Need tounderstand language before
producing it)– Dramatic CC changes duringchildhood

Nature, 2000

Diffusion Tensor Imaging (DTI)
Magnetization Transfer Imaging (MTI)

More than just maximizing speed …

• Synchrony• Plasticity• Sensitive Periods• Integration

Aspects of “Connectivity”• LTP• White Matter• EEG coherence• fMRI coactivation• Temporally coupled developmental trajectories– Fire together, wire together, … grow together?

• Similarly affected by same genetic/environmental
factors- - - - Graph Theory (Nodes and Edges) - - - -Graph Theory: Is it a small world after all?
(strangers linked by mutual acquaintance)Collective dynamics of 'small-world' networks(Nature, June 1998)• Small world networks– Many beneficial properties– Surprisingly often seen in natural systems– A whole field of mathematics developing
to quantify aspects of “connectivity”

Disrupted modularity and local connectivity
in childhood onset schizophrenia

Alexander-Bloch, Bulmore, Giedd 2010

Part 1 – Mapping Trajectories ofAnatomic Brain Development• White Matter•Gray Matter

Gray Matter

White Matter vs Gray Matter

White Matter

Gray Matter– Linear increase– Inverted “U”– Not different
by region– Regionally specificGray Matter Development
in Healthy Children & Adolescents(1412 Scans from 540 Subjects)

Frontal Lobe Gray Matter

Volume in ml

240

220

200
4

6

8

10

12

14

Age in years

16

18

20

22

Architectonic complexity aligns with thecomplexity of cortical growth trajectories

Complexity of developmental
trajectories throughout theorbitofrontal cortex, projected
onto a standard brain
template.

The trajectory of eachof the divisions.
Red - cubic fit
Green - quadratic
Blue - linear

The trajectories aresuperimposed on acytoarchitectonic map of
the region (Ongur et al.,2003) to illustrate theoverlap between thecytoarchitectonic fields
and regional trajectory
differences.

Neuronal Branching
Dendrites& Synapses

Diamond, Hopson,
Scheibel, 1998
BIRTH

3 MONTHS OLD

2 YEARSImages by Diane Murphy, PhD, National Institutes of HealthOverproduction / Selective Elimination• Postmortem–Animal–Human
• EEG
• MEG
• PET

Similar Pattern for Synaptic DensityAnd for D1 Receptor Density in Striatum

Movie for adolescent students

Zits cartoons © Zits Partnership

Gray Matter Thickness:
Ages 4 to 25 years

Prefrontal Cortex• “Executive” functions– Long term strategy– Planning– Organization– Impulse control• Integrates input from rest of
the brain• “Time Travel”• Multi tasking bottle neck?

Questions related to changing cortical thickness• What are the social/judicial/parenting/personal implications of late DLPFC
maturation?
• What influences the build up stage?
–

Parenting / Medications / Diet / Video games /Other• Does the “use it or lose it” principle guidethe adolescent pruning?

Overproduction/Selective Elimination as a construct tounderstand developmental pathology?

JudicialSocialPolitical

Educational

CommercialClinicalQuestions related to changing cortical thickness• What are the social/judicial/parenting/personal implications of late DLPFC
maturation?
• What influences the build up stage?
–

Parenting / Medications / Diet / Video games /Other• Does the “use it or lose it” principle guidethe adolescent pruning?

Overproduction/Selective Elimination as a construct tounderstand developmental pathology?

“Life is a journey
not a destination”-fortune cookie from the Peking Duck,
Bethesda, MD 2002

IQ and cortical thickness
IQ > 125
110-125
95-110Philip Shaw, 2006

IQ and cortical thickness
IQ > 125
110-125
95-110Philip Shaw, 2006

Anatomic MRI of the brain
during typical pediatric development• White Matter Increase (Myelination)• Inverted U Gray Matter (Synaptic Pruning?)• Relatively late maturation of:– Prefrontal Cortex– Superior Temporal Sulcus– Inferior Parietal Cortex• Journey / Destination• Critical / Sensitive periods?

fMRI
Probes cerebral blood flow-oxygen consumption duringcortical activation

rest•Oxy and Deoxy
hemoglobin havedifferent magnetic
properties

oxyhemoglobin
deoxyhemoglobin

event
more oxyhemoglobinthan deoxyhemoglobin• Resolution?
Space - few millimeters
Time – few seconds

Functional MRI of the brain during
typical pediatric development• Changing Frontal / Limbic balance• Diffuse to Focal activation patterns• Increased integration of widely distributed brain
circuitry– Fast connections for top down modulation– More efficient neuronal processing?

Do Teens and Adults
process emotions differently?

 Adults and teen subjects havebeen shown to process emotions
differently, they use different
areas of their brain to recognize
feelings

 Many teen subjects failed tointerpret the emotion in faces likethis one as fear.

Recognizing emotions from picturesof faces: Adults vs Teens

When reading emotion, teens (left) rely more on the
amygdala, while adults (right) rely more on the frontal cortex.
Deborah Yurgelon-Todd, 2000

Functional MRI of the brain during
typical pediatric development• Changing Frontal / Limbic balance• Diffuse to Focal activation patterns• Increased integration of widely distributed
brain circuitry– Fast connections for top down modulation– More efficient neuronal processing?

Part 2 - Influences on
Brain Development• Nature / Nurture  Twin studies• Male / Female• Specific Genes• Psychopathology

Part 2 - Influences on
Brain Development• Nature / Nurture  Twin studies• Male / Female• Specific Genes• Psychopathology

Twins• 130 Monozygotic (“identical”) pairs• 105 Dizygotic (“fraternal”) pairs• Structural Equation Modeling
A Additive Genetic Factors
C Common Environment
E Error/ Unique Environment

Heritability varies by age and region

Heritability (a2) at ages 5,12, and 18 years. Colorbar shows heritability values from
0.0 to 1.0
Red arrows- heritability higher at younger ages
Green arrows- heritability higher at older ages

Lenroot et al, 2008

What are the implicationsof substantial age x
heritability interactions
for the design andinterpretation ofimaging/genetic studies?

MODEL

A2

C2

E2

Total Cerebrum

0.89[.67 - .92]

0.00 [.00 - .22]

0.11[.08 - .16]

Gray Matter

0.82[.50 - .87]

0.00 [.00 - .30]

0.18[.13 - .26]

White Matter

0.85[.56 - .90]

0.01 [.00 - .29]

0.15[.10 - .21]

Frontal GM

0.77[.37 - .83]

0.00 [.00 - .38]

0.23[.17 - .32]

Parietal GM

0.80[.44 - .86]

0.00 [.00 - .35]

0.20[.14 - .29]

Temporal GM

0.80[.46 - .86]

0.00 [.00 - .33]

0.20[.14 - .28]

Caudate0.80[.57 - .86]

0.00 [.00 - .22]

0.20[.14 - .29]

Corpus Callosum

0.84[.41 - .89]

0.01 [.00 - .43]

0.15[.11 - .22]

Cerebellum

0.50[.14 - .84]

0.29 [.00 - .63]

0.21[.15 - .29]

The Unique Cerebellum!
(among our gross anatomic measures)• Least heritable• Latest to reach adultvolume• Most sexually dimorphic(male >female, surviving
TCV covariate)

Cerebellar Atlas: Schmalmann, Doyon, Toga, Petricles, Evans (2000)

Multivariate Analysis(degree to which same factors
contribute to multiple structures)• Single factor accounts for 60% of genetic
variability in cortical thickness.
– When covaried for mean global cortical
thickness 6 PCA factors explained 58%– 5 groups of structures strongly influenced by
the same underlying genetic factors
Schmitt et al, 2008

Part 2 - Influences on
Brain Development• Nature / Nurture  Twin studies• Male / Female• Specific Genes• Psychopathology

Brain Maturation and Sex Differences –Implications for Development, Health, andSchool Achievement
School, Educational
Achievement and
Mental Health among
Children andAdolescents
Stockholm
April 26, 2010
Jay N. Giedd, MDChild Psychiatry
Branch, NIMH, USASex Differences in Child& Adolescent Psychiatry• Nearly all neuropsychiatric disorder of childhood
onset have different prevalences, ages of onset,
and symptomatology between boys and girls.

• Might sexually distinct patterns of normal brain
development may interact with other environmental
or genetic factors to account for some of theseclinical differences?

Summary of Sexual Dimorphism• Overwhelming more alike than different• Developmental trajectories more different than finaldestination• Male brain morphometry more variable• Differences are between groups – does NOT imply
constraints for individual boys or girls• Effects of environment, sex chromosomes,
hormones being elucidated

Total Cerebral Volume by Age for
224 Females (375 scans) and 287 Males (532 scans)

Total Cerebral Volume (cc)

1600
1500
1400
1300
1200
1100
1000
900
800
700
0

5

10

15

Age (years)

20

25

30

Summary of Sexual Dimorphism• Overwhelming more alike than different• Developmental trajectories more different than finaldestination• Male brain morphometry more variable• Differences are between groups – does NOT imply
constraints for individual boys or girls• Effects of environment, sex chromosomes,
hormones being elucidated

Sex Differences in Trajectories
224 Females (375 scans) 287 Males (559 scans)
Total Cerebral Volume

Total White Matter

Shape: F=9.26; p<.0001

Shape: F=9.75; p<.0001
500

WM Volume (cc)

1300

1100

1000

900

450
400
350
300
250

0

10

20

30

0

20

30

Age (years)

Total Gray Matter

Frontal Gray Matter
Shape: F=3.16; p=.024
Frontal GM (cc)

760
740
720
700
680
660
640
0

10

Age (years)

Shape: F=3.58; p=.014

780

GM Volume (cc)

TCV (cc)

1200

10

20

Age (years)

30

240
235
230
225
220
215
210
205
200
195
0

10
20
Age (years)30

Is the Corpus Callosum
Sexually Dimorphic?

Summary of Sexual Dimorphism• Overwhelming more alike than different• Developmental trajectories more different than finaldestination• Male brain morphometry more variable• Differences are between groups – does NOT imply
constraints for individual boys or girls• Effects of environment, sex chromosomes,
hormones being elucidated

Variance greater in males

Levene’s test for difference of variance between males andfemales at each point on vertex. (white is zero)Summary of Sexual Dimorphism• Overwhelming more alike than different• Developmental trajectories more different than finaldestination• Male brain morphometry more variable• Differences are between groups – does NOT imply
constraints for individual boys or girls• Effects of environment, sex chromosomes,
hormones being elucidated

Male/Female Differences
Greatest at Extremes• Example – height–@1.78 m (5’10”) – 30:1 male–@1.83 m (6’0”) – 2000:1 male

Summary of Sexual Dimorphism• Overwhelming more alike than different• Developmental trajectories more different than finaldestination• Male brain morphometry more variable• Differences are between groups – does NOT imply
constraints for individual boys or girls• Effects of environment, sex chromosomes,
hormones being elucidated

Social Influences

Sex Difference Investigations
Involving Clinical Populations• Anomalous numbers of
X and Y chromosome– XXY (Klinefelter’s Syndrome)• Anomalous hormone profiles– Congenital Adrenal Hyperplasia– Androgen Insensitivity Syndrome– Familial Precocious Puberty– Kallmann Syndrome

Sex Chromosome Dosage Effects• XO, XYY, XXY, XXYY, XXX,
XXXY, XXXXY• Clinical severity worsens withincreasing number• X gene dosage effects should be
related to the 15% of the X
chromosome genes that are notinactivated.

Impact of sex chromosome dosage
Total Gray and White Matter (cc)XX: 35
XXY: 61
XYY: 28
XXYY: 22XXXXY: 6

Part 2 - Influences on
Brain Development• Nature / Nurture  Twin studies• Male / Female• Specific Genes• Psychopathology

Cortical thickness (mm)ApoE effects on brain morphometry
during pediatric development

T statistical map of thinning in e4
carriers compared to non-carriers

ε2 carriers

ε3 homozygotes

ε4 carrier

Genotype

Thickness of the entorhinal cortex by ApoE
genotype during childhood

Part 2 - Influences on
Brain Development• Nature / Nurture  Twin studies• Male / Female• Specific Genes• Psychopathology

Why Adolescence?
• Time of dramatic change in brain, body, and behavior• Time of peak emergence of:– Schizophrenia– Depression– Anxiety– Substance Abuse– Eating Disorders• Not Autism, ADHD, Alzheimer’s• Moving parts get broken?

Adolescent Brain Changes
sMRI
WM 
GM ∩

EEG
Delta sleep Cyclic power PET glucose utilization

fMRI
Diffuse  focal
“frontalization”
 integration

Postmortem
Overproduction/
Selective elimination
Synapses
Neurotransmitters

Risks for psychopathology duringadolescence
Typical behavior changes
 Risk taking
 Novelty seeking
 Social priorities

Schizophrenia
Exaggeration of typicalregressive changes:•Delta sleep•Membrane phospholipids•Synaptophysin expression•Synaptic spine density•Neuropil•Prefrontal metabolism•Frontal gray matter

Substance AbuseSensitivity to hangover,sedation, andmotor impairment
 Hippocampal vulnerability

Depression
Hormonally mediated limbic effects
preceeding maturation of cognitiveregulatory system

Why Adolescence: Schizophrenia• Is schizophrenia related to an exaggeration of typicalregressive changes of adolescence?

• Delta sleep (synaptic pruning?) – (Feinberg 1982)• Membrane phospholipids (Pettegrew et al. 1991)• Prefrontal metabolism (Andreasen et al. 1992)• Density of synaptic spines (Garey et al. 1998)• Neuropil (Selemon et al. 1995)• Expression of synaptic marker synaptophysin (Eastwood et al. 1995)• Frontal cortical gray matter (Sporn et al. 2003)

Gray Matter thickness changes inChildhood Onset SchizophreniaDecrease Increase

Percentage Change in Regional Cortical Gray Matter Volumes
Between Healthy Volunteers (N=34) and Childhood-Onset
Schizophrenics (N=15) Ages 13-18

Consideration, not explanation• Increase in pre and peri natal adverse events• Subtle cognitive, motor, and behavioral anomalies
during childhood years before illness onset
Support for earlier developmental disturbances
underlying the abnormal maturational events duringadolescence.

Age of attaining peak cortical thickness for the ADHD and healthy control
groups: ADHD has “shift to the right”

The darker colors indicate regions where a quadratic model was not appropriate and thus a peak age could not becalculated, or that the peak age was estimated to lie outside the age range covered
Shaw et al. Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. PNAS, 104(49): 19649-19654

Summary• The adolescent brain is developing not defective• Journey not just destination• Differences in prefrontal/limbic balance affecttemporal discounting, reward circuitry, hot vs cold
cognition, and decision making that may be relevantto the issues of substance abuse• Enormous plasticity confers both vulnerability andopportunity

1. Cognitive/Behavioral

2. Male/Female Differences

Journey notjust Destination

3. Genetic/Environmental

4. Health/Illness

Summary• The adolescent brain is developing not defective• Journey not just destination• Differences in prefrontal/limbic balance affecttemporal discounting, reward circuitry, hot vs cold
cognition, and decision making that may be relevantto the issues of substance abuse• Enormous plasticity confers both vulnerability andopportunity

They need their parents

They need their parents

just as much as they do.