Mapping Early Brain Development in Autism
Eric Courchesne,1,2,* Karen Pierce,1,2Cynthia M. Schumann,1,2Elizabeth Redcay,2,3Joseph A. Buckwalter,1,2
Daniel P. Kennedy,1and John Morgan1,2
1Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
2Autism Center of Excellence, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
3Department of Psychology, University of California, San Diego, La Jolla, CA 92093, USA
Although the neurobiology of autism has been studied for more than two decades, the majority of
these studies have examined brain structure 10, 20, or more years after the onset of clinical symp-
toms. The pathological biology that causes autism remains unknown, but its signature is likely to
be most evident during the first years of life when clinical symptoms are emerging. This review high-
lights neurobiological findings during the first years of life and emphasizes early brain overgrowth as
a key factor in the pathobiology of autism. We speculate that excess neuron numbers may be one
possible cause of early brain overgrowth and produce defects in neural patterning and wiring, with
exuberant local and short-distance cortical interactions impeding the function of large-scale, long-
and communication functions, such alterations in brain architecture could relate to the early clinical
manifestations of autism. As such, autism may additionally provide unique insight into genetic and
developmental processes that shape early neural wiring patterns and make possible higher-order
social, emotional, and communication functions.
Autism is a genetic disorder of neural development in
which the first behavioral symptoms appear early in life.
It is more heritable than breast cancer, colon cancer, Alz-
heimer’s disease, or schizophrenia. There may also be
important differences in the genetic mechanisms in chil-
dren with autism from multiplex families versus singleton
children with no family history of autism (Sebat et al.,
2007; Zhao et al., 2007). Nongenetic factors are thought
to play a role in causing the disorder, but remain unidenti-
higher-order social, emotional, language, and communi-
cation functions (Lord and Risi, 2000; Rogers and Di Lalla,
1990). The first behavioral signs of autism may appear
between 1 and 2 years of age and largely involve abnor-
malities in social attention, language development, and
emotional reactivity (Landa and Garrett-Mayer, 2006;
Wetherby et al., 2004; Zwaigenbaum et al., 2005), and
the diagnosis of autism is commonly made by 2–4 years
of age. Autism spectrum disorders (ASD; referred to as
autism throughout this review) are relatively common, oc-
curring in 1 out of 150 individuals (Fombonne, 2005).
Treatment costs for a child can be as much $30,000 per
year, and the cost of autism in the US is estimated to be
as much as $35 billion per year (Ganz, 2007).
Perhaps the most startling statistic, however, is that for
this disorder of neural development, there are very few
studies of early neural anatomical development at the
age of clinical onset, namely between 2 and 4. This age
is a critical period for early intervention therapies. This is
also the most important period in human life for the forma-
tion of the neural wiring patterns that make possible the
development of higher-order social, emotional, and com-
munication functions, the very ones that are profoundly
tions possible. The genetic and developmental processes
that organize developing brain networks and presumably
aid in disorganizing autistic brain networks are largely un-
studied in the early developmental time period in humans.
Thus, the original alterations in brain architecture that
produce dysfunction in socio-emotional and communica-
tion networks in the infant and toddler with autism remain
Instead, autism studies have largely focused on ages
10, 20, or more years after the onset of the disorder. For
instance, of the nearly 100 magnetic resonance imaging
(MRI), diffusion tensor imaging (DTI), and postmortem
studies of brain structure in autism in the past decade,
only six MRI, one DTI, and zero postmortem studies
have specifically studied autistic children at the typical
age of first clinical identification and diagnosis, namely
2–4 years. The only anatomical evidence at the age of first
preclinical signs, namely 1–2 years, comes from several
retrospective head circumference studies based on pedi-
atrician records. There is also not a single study of the
early development of anatomical connections in autism.
Although not a measure of connectivity patterns, the vol-
ume of cerebral white matter has been reported in three
MRI studies in 2- to 4-year-old autistic children (Carper
et al., 2002; Courchesne et al., 2001; Hazlett et al., 2005).
The most interesting white matter evidence regarding
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
of 7- to 11-year-olds (Herbert et al., 2004; see below). Of
the 39 postmortem studies of autism, the mean age of au-
tistic cases is 21 years, an average of two decades after
Thus, a great percentage of the literature on autism
anatomy has addressed the question of what anatomical
abnormalities characterize the disorder 10, 20, or more
years after clinical onset, but studies of the older and ma-
ture autistic brain leave unaddressed the question of what
neural structural abnormalities underlie the emergence of
autistic behavior in the beginning stages. Studies of early
development are required to address that fundamental
question, and, although few in number, new developmen-
tal studies have revealed the phenomenon of abnormal
early brain overgrowth during the first years of life in this
disorder. New theories based on this neurodevelopmental
evidence argue for early malformation of neural circuits
in specific higher-order cortices that mediate the social,
emotional, language, and communication dysfunctions
that are core features of the disorder.
Theserecentstudies of earlydevelopment arereviewed
in depth below. However, these new developmental find-
larger context of MRI, DTI, and postmortem evidence on
the adolescent or adult autistic brain. The following is a
brief summary of that literature; for other reviews, see
Bauman and Kemper, 2005; Cody et al., 2002; Courch-
esne et al., 2004; Courchesne and Pierce, 2005a; Herbert,
2005; Palmen et al., 2004.
Anatomic Evidence on the Autistic Brain 10–20
or More Years after Clinical Onset
The overall picture from the postmortem literature on the
older child or adult with autism starkly contrasts with
what one might expect from early brain overgrowth. It is
one of neuron loss, degeneration, inflammation, and re-
duced size of cortical minicolumns (the vertical organiza-
tion of neurons in the neocortex). The largest postmortem
study of autism to use stereological methods for quantify-
ing neuron numbers in 10- to 44-year-old cases found
fewer neurons in the amygdala, a structure important in
emotion, learning, and memory (Schumann and Amaral,
2006). The cerebellum, a structure that is important for
tions, has been consistently reported to have reduced
numbers of cerebellar Purkinje neurons, without which
this structure does not function properly (Bailey et al.,
1998; Kemper and Bauman, 1998; Lee etal., 2002;Vargas
et al., 2005). One caveat is that the finding of Purkinje cell
loss has yet to be confirmed with a quantitative stereolog-
ical study. Interestingly, Bailey et al. (1998) observed as-
trogliosis, a sign of glial activation that may be associated
with neuronal degeneration or death, in the cerebellum.
Vargas et al. (2005) reported degenerating Purkinje neu-
rons, glial activation, andincreasesin pro- andanti-inflam-
matory molecules in the cerebellum. Neurons in the deep
cerebellar nuclei, the only pathway exiting the cerebellum,
were reported to be abnormally small and pale in adoles-
In frontal cortex, which mediates many higher-order func-
tions, Araghi-Niknam and Fatemi (2003) found increases
in proapoptotic (pro-cell death) and decreases in antia-
poptotic (anti-cell death) molecules in adult autistic cases.
Increased molecular signs of glial activation have also
been reported in the cerebrum (Laurence and Fatemi,
2005). Vargas et al. (2005) reported glial activation and
pro- and anti-inflammatory molecules in frontal cortex.
Studies have also found smaller frontal and temporal
cortical minicolumns in older children, adolescents, and
adults with autism (Buxhoeveden et al., 2006; Casanova
et al., 2002, 2006). Clearly, more information is needed
on the possible pathology of dendrites, axons, myelin,
synapses, and the numbers of cortical minicolumns and
neurons at all ages in autism, but such studies have yet
to be carried out.
Some evidence of possible degenerative processes in
adults with autism and/or reduced anatomic size also
comes from the in vivo imaging literature. Progressive,
age-related degeneration in the autistic brain from child-
hood to adulthood was first described nearly 30 years
ago by Hoshino et al. (Hoshino et al., 1984) from CT data,
and nearly 15 years ago, a qualitative MRI study reported
cortical thinning, sulcal widening, and occasionally ven-
(Courchesne et al., 1993). Most recently, Hadjikhani et al.
(2006) provided a detailed cortical map showing abnor-
mally thin cortices in multiple superior parietal, temporal,
and frontal regions in adolescents with autism. Interest-
ingly, these regions include the mirror neuron system,
which has been hypothesized by some to be critical in
manetal.,2005; Obermanand Ramachandran, 2007;Wil-
liams et al., 2001, 2006). Potentially consistent with this
would be a new finding showing reduced frontal lobe vol-
umes in adults with autism (Schmitz et al., 2007). On MRI,
the amygdala in autism is reported to be either similar to
(Schumann et al., 2004) or smaller than (Nacewicz et al.,
2006; Pierce et al., 2004) normal adolescents and adults.
The corpus callosum, which carries interhemispheric
axons, has been consistently reported to have reduced
size in one or another of its subregions (Alexander et al.,
2007; Chung et al., 2004; Egaas et al., 1995; Hardan et al.,
2000; Just et al., 2007; Manes et al., 1999). The cerebellar
vermis, which may be involved in modulating emotion,
arousal, and sensory responsiveness, has been reported
to be similar to (Piven et al., 1992) or smaller than (Ciesiel-
ski et al.,1997; Courchesne et al., 1988, 1994, 2001; Kauf-
mann et al., 2003; Levitt et al., 1999) typically developing
children, adolescents, and adults. However, not all MRI
studies have found abnormally thin cortices in mature au-
tistic subjects (Hardan et al., 2006); some have reported
that cortical gray matter enlargement may persist into ad-
olescence and adulthood (Hazlett et al., 2006; Lotspeich
et al., 2004).
On the other hand, meta-analyses of all available MRI
and postmortem data show that overall brain size is near
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
the normal average in autistic adolescents and adults,
with differences from normal being only about 1% in vol-
ume or weight (Redcay and Courchesne, 2005). Despite
the lack of significant brain weight difference, about 5%
of adolescent and adult postmortem cases of autism
do have exceptionally heavy brain weights (Courchesne
et al., 1999; Redcay and Courchesne, 2005).
Head circumference (HC) findings in adolescents and
HC is an imprecise measure of brain size in adults be-
cause, from adolescence onward, CSF occupies an in-
creasing percentage of the volume inside the head, and
the brain occupies a decreasing percentage (Bartholo-
meusz et al., 2002). In fact, research shows that despite
slightly larger head circumference in older autistic pa-
tients, brain size is near the average of normal subjects
(Aylward et al., 2002). These data suggest that HC is not
the head in adults and adolescents with autism.
According to the large amount of literature conducted
10, 20, or more years after the clinical onset of autism,
the norm for patients is an average size brain overall.
neuroinflammatory, processes in frontal, temporal, cere-
ron loss, and perhaps loss of connections, although this
latter possibility is speculative. Variable volumetric find-
ings across MRI studies may reflect individual variability
in such pathological processes and their consequences
for neuronal and circuit survival. Across most structures
that were measured, the most common finding is average
to smaller than normal volume. The relationships between
the pathologies seen at postmortem and in vivo neural,
at this time.
Mature Compared to Developing Brain in Autism
How does evidence gleaned 10–20 years after clinical on-
set square withdata on autism atthe age of clinical onset?
That is, at 2–4 years of age, is there reduced size of ana-
tomical structures, loss of neurons, and reduced size of
minicolumns? Is the brain normal in size? Is brain enlarge-
ment present in just a small 5% of autism cases, perhaps
reflecting only a rare subtype of autism?
In fact, much of the adult literature does not square with
new evidence on the young autistic brain. The overall pic-
ture from MRI and single case studies does not show loss,
reduction, and possible decline, but instead excessive
growth and size. MRI brain volume is 5%–12% greater
than normal in very young autistic children compared to
controls, not just the overall average of 1% found in
meta-analyses of adolescent and adult autism patients
(Courchesne et al., 2001; Hazlett et al., 2005; Redcay
and Courchesne, 2005; Sparks et al., 2002). There are
other examples in specific brain regions; for instance,
Sparks et al. (2002) found a larger amygdala on MRI in liv-
ing 4-year-old autistic children, not a smaller one aswould
be predicted based on the adult findings of reduced
amygdala neuron numbers. Importantly, enlargement of
the right amygdala in 3- and 4-year-old autistic children
has been correlated with increased severity of social and
communication scores on clinical tests (Munson et al.,
2006), an intriguing finding considering the implicated so-
cial and emotional processing functions of the amygdala.
We found normal average minicolumn size in a 3-year-
old with autism, the youngest case ever studied in the
postmortem literature, and not reduced size as would be
predicted from the adult autism minicolumn literature
(Buxhoeveden et al., 2006). Bailey et al. (1998) did not find
Purkinje neuron loss in a 4-year-old autism case, in con-
trast to the adult autistic literature that finds Purkinje loss
to be a consistent result. In the only published stereolog-
ical studyof frontal cortex neuronnumbers,Kennedy etal.
(2007) found 58% more spindle neurons, which are large
specialized pyramidal cells thought by some to be impor-
tant elements in social processing circuits, in a 3-year-old
autistic case as compared to an age- and hemisphere-
matched control. It should be noted that these findings
are from a single patient and highlight the need for large-
sample studies of frontal cortical neuron numbers in the
young autistic brain.
Entirely unlike the adult picture, the picture in the very
young autistic child that is now emerging is one of excess
and enlargement, possibly in the very same regions that
10, 20, or more years later show pathological degenera-
tion, loss, and size reduction. This has given rise to a new
hypothesis: early brain development in autism is charac-
terized by two phases of brain growth pathology (Courch-
esne et al., 2001, 2003; Courchesne and Pierce, 2005a):
early brain overgrowth at the beginning of life and slowing
or arrest of growth during early childhood (Figure 1). In
some individuals, a third phase, degeneration, may be
present in some brain regions by preadolescence. Patho-
logical processes underlying these phases could be re-
lated because regions that undergo early overgrowth later
undergo arrest of growth and, in some individuals, patho-
logical degeneration with age. Age-related changes in
structure as well as substantial heterogeneity in long-
term outcome might alter or mask early brain pathology.
potential regions of early abnormality but cannot directly
inform the neurobiological beginnings of an aberrant de-
velopmental trajectory in autism.
Early Brain Overgrowth in Autism
Evidence from Head Circumference and MRI
During the first years of life, head circumference does cor-
relate well with brain size in typically developing and autis-
tic children (Bartholomeusz et al., 2002), and it has been
used as a retrospective indicator of relative brain size in
autism. At birth, head circumference in infants who later
go on to develop autism is typically near normal or slightly
below the normal average (Courchesne et al., 2003; Daw-
son et al., 2007; Dementieva et al., 2005; Dissanayake
et al., 2006; Gillberg and de Souza, 2002; Hazlett et al.,
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
2005; Lainhart et al., 1997; Mason-Brothers et al., 1990;
Stevenson et al., 1997) (Figure 2). In the two studies that
provided individualdata(Courchesne etal.,2003;Demen-
tieva et al., 2005), 90%–95% of the neonates later diag-
nosed as autistic had average to slightly smaller than
average HC at birth, and only about 5% had excessively
large HC at birth (Figures 3A and 3B). However, Courch-
esne et al. (2003) recently discovered that by 1 or 2 years
of age in autism, head circumference (HC) becomes
abnormally enlarged (Figures 3A and 3C). This finding of
early overgrowth has now been replicated by many inde-
pendent research groups (Dementieva et al., 2005; Dissa-
nayake et al., 2006; Hazlett et al., 2005; Dawson et al.,
2007) (e.g., Figures 3B and 3D).
By the time children with autism reach 2–4 years of age,
overall MRI brain volume is abnormally enlarged by about
10% relative to typically developing 2- to 4-year-olds
(Carper et al., 2002; Courchesne et al., 2001; Hazlett et al.,
2005; Sparks et al., 2002). Two more recent MRI studies
have confirmed this finding of brain enlargement in young
autistic children, with mean subject ages of 2.7 years
(Hazlett et al., 2005) and 3.9 years (Sparks et al., 2002).
A meta-analysis of all published MRI brain size data on
children, adolescents, and adults through early 2005
showed that the period of greatest brain enlargement in
autism is during the toddler years and early childhood
(but it is important to note that even at older ages there
remains an overall 1%–3% percent greater brain volume
in autistic patients) (Figure 4A) (Redcay and Courchesne,
always a reliable measure, does corroborate conclusions
from HC and MRI studies. In the only study to statistically
analyze age-related changes in autism brain weights,
Redcay and Courchesne (2005) found that brain weight
was 15% greater in 3- to 5-year-old male autism cases
than male control cases (1451 g versus 1259 g) (see
Figure 4B). Adult brains also have more cerebrospinal
fluid, which may erroneously increase recorded brain
weights. Even so, the difference between adults with au-
tism and nonautistic control brains is diminished to about
1% (Figure 4B). It is important to note that the average
brain weight of 1451 g in the 3- to 5-year-old autism cases
is about the same as the average normal adult male brain
(Courchesne et al., 1999).
Regions Showing Early Anatomic Overgrowth
years of age, some regions and structures display over-
growth while others do not (Carper and Courchesne,
2005; Carper et al., 2002; Sparks et al., 2002). While there
aremany possible explanations, onepossibility isthe rela-
tive timing of overgrowth and/or regional-specific genetic
mechanisms that might be involved.
Regarding timing, it is possible that some regions have
not been reported to display overgrowth during early or
late childhood because those regions have a much earlier
development. That is, some very early developing brain
regions may in fact experience abnormally accelerated
overgrowth, but prior to the ages investigated by past
MRI studies, namely, prior to 2–4 years of age. Thus, it
could be that some regions or structures may in fact be
experiencing a subsequent arrest of growth during a time
Figure 1. Regional Early Overgrowth in ASD
(A) Model of early brain overgrowth that is followed by arrest of growth.
Blue lines represent ASD, while red lines represent age-matched
typically developing individuals. In some regions and individuals, the
arrest of growth may be followed by degeneration, indicated by the
blue dashes that slope slightly downward.
(B) Sites of regional overgrowth in ASD include frontal and temporal
cortices, cerebellum, and amygdala.
Figure 2. Comparison of Seven Independent Studies of
Head Circumference Measurements (cm) in Relation to
Roche and CDC Scales
References: 1, Mason-Brothers et al., 1990; 2, Lainhart et al., 1997;
3, Gillberg and de Souza, 2002; 4, Courchesne et al., 2003; 5,
Stevenson et al., 1997; 6, Dementieva et al., 2005; 7, Courchesne
et al., 2001.
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
period when other later-developing systems are still
experiencing overgrowth. Given this, it is important to
point out that heterochronicity is a key variable in the pro-
posed hypothesis of phases. Occipital cortex, for exam-
ple, is an early developing region and, as discussed next,
is one of the regions that show little or no evidence of
overgrowth in studies of autistic children ages 2 years
and up. Currently, there are no MRI studies of the autistic
brain younger than 2–4 years of age, so occipital cortex,
for example, may either not undergo overgrowth or over-
growth may occur prior to the age that MRI studies have
With these considerations in mind, MRI research on
autistic 2- to 4-year-olds implicates the frontal lobes, tem-
poral lobes, and amygdala as sites of peak overgrowth
(see Figure 1) (Carper and Courchesne, 2005; Carper
et al., 2002; Courchesne et al., 2001; Hazlett et al., 2005;
Sparks et al., 2002). Although gray and white matter vol-
umes are substantially increased in the cerebrum as a
whole (Courchesne et al., 2001; Hazlett et al., 2005), a
striking finding across a number of studies and ages that
lobe is that frontal and temporal lobes are enlarged the
most and occipital lobe the least (Bloss and Courchesne,
2007; Carper et al., 2002; Hazlett et al., 2006; Kates et al.,
2004; Palmen et al., 2005) (see Figure 5). This regional
gradient ofabnormal enlargement parallelsregionswhose
cognitive functions may be most impaired versus those
most spared. In one study, frontal and temporal sulci are
children (Levitt et al., 2003), which would be consistent
with a disproportionate increase in frontal and temporal
It is reasonable to extrapolate that the same cerebral
regions that experience the greatest amount of early
ture myelination in frontal, but not posterior, white matter
regions in very young autistic children (Ben Bashat et al.,
2007). A DTI study of autistic adolescents reported white
matter abnormality underlying dorsal and medial prefron-
tal cortices, superior temporal cortex, temporoparietal
junction, and the corpus callosum (Barnea-Goraly et al.,
olescents, cerebral white matter was subdivided into
internal and external compartments, and it was reported
that the outer radiate portion of white matter, particularly
in frontal lobes, was prominently disturbed; it was least
deviant in occipital lobes (Herbert et al., 2004). This result
suggests that autism might involve abnormal increases
in short-distance connectivity, especially in brain regions
that mediate higher-order language, cognitive, social,
and emotional functions (see also Belmonte et al., 2004;
Courchesne and Pierce, 2005b; Just et al., 2004). Con-
versely, decreases in the cross-sectional area of the
callosum have been reported across a wide range of ages
2007; Manes et al., 1999; Piven et al., 1997; Rice et al.,
2005; Tsatsanis et al., 2003; Vidal et al., 2006). Because
the majority of these studies were conducted in adoles-
cents and adults, DTI and MRI volumetric studies of white
matter in very young children with autism are needed to
determine whether these abnormalities in the older child
Thus, MRI studies of gray and white volume, cerebral
sulci, and cerebral white matter development each point
Figure 3. Early Brain Overgrowth during
the First Years of Life in Autism
(A) Head circumference (HC) z-scores at birth
and 6–14 months in individuals with autism rel-
ative to norms (from Courchesne et al., 2003)
and (B) at 6–21 months of age (from Demen-
tieva et al., 2005). (C and D) HC (cm) growth
trajectory curves of autism subjects (red line
in [C], open circles in [D]) compared to CDC
50th percentile (blue line in [C], black line in
[D]), showing that neonates who later display
autism undergo an abnormally accelerated
rate of HC growth that becomes significantly
larger than normal at 12 and 24 months of
age (panel [C] from Courchesne et al., 2003;
panel [D] from Dawson et al., 2007). Panels
were adapted and reprinted with permission
from Courchesne et al., 2003, Dementieva
et al., 2005, and Dawson et al., 2007.
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
to pronounced frontal and temporal lobe abnormality.
Peak overgrowth pathology in the cerebrum in autism,
therefore, appears to be in frontal and temporal lobes, re-
gions that mediate the higher-order social, emotional,
cognitive, and language functions that are impaired in
this disorder. Studies are needed to determine whether
these regional increases reflect an abnormally expanded
cortical sheet, an abnormally thickened one, or both, as
defects in corticogenesis.
The map of early cerebral anatomical abnormality is
likely more complex than this because, within frontal cor-
tex, some regions seem to be substantially enlarged (dor-
solateral and mesial prefrontal), while others are enlarged
less or not at all (orbital, precentral gyrus) (Carper and
Courchesne, 2005).Analyses ofothercorticalregionsdur-
ing early development have not been done, and the study
of frontal regions did not examine subregions within the
larger dorsal andmesial divisions.While subcortical struc-
tures have been less extensively studied than cortex, as
noted above, the amygdala has also been reported to be
enlarged in young (Sparks et al., 2002) as well as older
plete regional map of early developmental overgrowth in
the autistic brain remains to be charted.
Early Brain Overgrowth and Abnormal Functional
Early brain overgrowth occurs during developmentally
critical years that are normally characterized by burgeon-
ing language, social, emotion, and attention skills for the
typically developing toddler, but strikingly deviant devel-
opment for the infant and toddler with autism (Baron-
Cohen et al., 1992; Landa and Garrett-Mayer, 2006;
Wetherby et al., 2004; Zwaigenbaum et al., 2005). There-
fore, a fundamental question is: Are the neural systems
that fail to provide those fundamental skills so early in
neurobehavioral development also the ones that undergo
abnormal overgrowth? The answer remains unknown.
The way the brain operates during this period of early
overgrowth remains largely a mystery due to a paucity
To date, event-related potential (ERP) methods have
been applied to the study of functional abnormalities in
the very youngest autistic children. However, the neural
systems underlying ERP abnormalities can only be spec-
ulated because anatomical localization is not a strength of
4-year-old autistic children report abnormal activity from
electrodes over frontal and temporal scalp sites. Dawson
et al. (2002) recorded ERP responses to familiar and unfa-
miliar social and nonsocial stimuli in autistic and normal
Figure 4. Brain Size Difference in Autism by Age
(A) Plot of a meta-analysis of 20 studies depicting brain size changes
with age in ASD. Adapted with permission from Redcay and Courch-
(B) Autism and control mean brain weight by age. Means of post-
mortem brain weight values from individual autistic males and mean
normative data were calculated for three age groups (3–5, 7–12, 13–
70). Comparison of the two lines illustrates that while the normal brain
continues to grow into adolescence, the autistic brain has already
reached its near maximal weight by 3–5 years of age.
References: 1, Gillberg and de Souza, 2002; 2, Courchesne et al.,
2003; 3, Lainhart et al., 1997; 4, Courchesne et al., 2001; 5, Piven,
2004; 6, Sparks et al., 2002; 7, Kates et al., 2004; 8, Herbert et al.,
2003; 9, Aylward et al., 2002; 10, McAlonan et al., 2005; 11, Rojas
et al., 2005; 12, Shultz et al., 2005; 13, Palmen et al., 2005; 14, Hardan
et al., 2003; 15, Piven et al., 1995; 16, Tsatsanis et al., 2003; 17, Ayl-
ward et al., 1999; 18, Carper, personal communication; 19, Haznedar
et al., 2000; 20, Rojas et al., 2002.
Figure 5. Summary of Observed Gray Matter Abnormalities
(Standard Deviations from Normal) from Studies of Children
and Adolescents with ASD
Note the general gradient of abnormality, with frontal and temporal
regions most profoundly enlarged.
References: 1, Carper et al., 2002; 2, Bloss and Courchesne, 2007; 3,
Kates et al., 2004; 4, Palmen et al., 2005; 5, Hazlett et al., 2005.
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
children. They found that in normal 3- to 4-year-old chil-
dren, the P400 and frontal Nc components of the ERP
were enhanced in amplitude in response to their mother’s
face as compared to a stranger’s face and to a familiar toy
as compared to an unfamiliar one. In contrast, autistic
3- to 4-year-olds did not show an enhanced response to
their mother’s face, but did to a familiar toy. In an elegant
that ERP responses to phoneme mismatches were more
normal in autistic 2- to 4-year-olds who showed behav-
These and other ERP studies by Dawson, Carver, Kuhl,
and colleagues were the first to examine the electrophys-
iological correlates of impaired social and linguistic pro-
cessing in autism during the first years of life (Carver and
Dawson, 2002; Dawson et al., 2002, 2004; McPartland
et al., 2004). Their studies support the general hypothesis
that neurophysiological systems that mediate socially sig-
nificant and meaningful information processing are more
developmentally abnormal than those that mediate non-
socially significant information processing, even when
that non-social information is complex and personally rel-
evant to the autistic toddler or young child.
The above ERP studies have given much needed infor-
however, they only partially address the central question
asked above, because ERPs remain unable to anatomi-
cally map dysfunction. To determine whether the specific
neural systems undergoing overgrowth function abnor-
mally in the autistic toddler, fMRI methods are needed
because they provide a powerful noninvasive method for
mapping cortical and subcortical brain functions. Until
recently, however, fMRI has not been utilized for this pur-
pose because it cannot be successfully used with awake,
alert toddlers, whether autistic or typically developing.
One possible solution is to conduct fMRI studies of autis-
tic infants and toddlers during natural sleep. A number of
ERP and fMRI studies comparing sleep and wake states
across infants to adults suggest some higher-order cogni-
tive processing, including differential processing of text
passages, semantic incongruity, and one’s own name,
persists during natural sleep (Bastuji et al., 2002; De-
haene-Lambertz et al., 2002; Perrin et al., 1999, 2002;
Wilke et al., 2003). Furthermore, infants show enhanced
auditory discrimination abilities while awake to phonemes
presented during sleep (Cheour et al., 2002). Thus, evi-
dence suggests that during natural sleep the neural re-
sponse to language, emotion, and other functions can
be examined without incurring artifact due to motion.
We have begun to conduct fMRI studies during natural
sleep (www.autismsandiego.com) and have demon-
stratedforthe firsttimethatitispossible tomap theneural
response to speech and nonspeech sounds as well as
intrinsic functional networks in typically developing infants
(Fransson et al., 2007) and toddlers (Redcay et al., 2007a,
2007b). While there are only a few studies that examine
auditory processing during sleep fMRI with infants and
toddlers (Anderson et al., 2001; Dehaene-Lambertz et al.,
2002; Redcay et al., 2007a, 2007b), we believe it to be
a quite powerful method for revealing deviant neurofunc-
tional systems early in development.
Cellular and Molecular Bases of Overgrowth:
As discussed above, the cellular and molecular bases of
pathological overgrowth in the young autistic brain are un-
known. Further, the critical question of what age-related
cellular and molecular changes occur between this time
of earlyovergrowth andlatermaturity 10–20ormoreyears
later has not been studied. Studies to date have been
hampered by the low availability and quality of control as
well as autistic brain tissue from younger cases. To under-
stand the neural defects underlying the emergence of
autism, itwillbenecessaryfor futureresearch touse mod-
ern quantitative stereological methods to investigate the
cellular basis of early brain overgrowth at the youngest
ages in autism when the growth pathology is at its peak
In the near absence of information that directs and con-
strains hypotheses, speculations have flourished. Among
the numerous abnormalities that could create overgrowth
in the young brain—but have yet to be examined by any
study—are excess neuron numbers, excess glia, acti-
numbers of minicolumns, excessive and premature axo-
nal and/or dendritic growth, excessive and/or premature
growth of neuron cell bodies, excess axon numbers, and
excessive and/or premature myelination (see reviews by
Bauman and Kemper, 2005; Palmen et al., 2004). Among
the more prominent speculations has been that there are
increased numbers of minicolumns in autism (Casanova
et al., 2006). However, minicolumn numbers have not
been stereologically quantified in either the child or adult
Recently, there has been speculation that the cause of
autism is at the synapse (Garber, 2007), but in fact there
have been no quantitative studies of any type of cortical
synapse in the child with autism. Such speculations
have come from genetic studies that have observed evi-
dence of possible involvement of neuroligin and neurexin
genes that affect synapse formation (Chubykin et al.,
2005; Jamain et al., 2003), but it remains unclear whether
the findings may speak to only a tiny percent of autism pa-
tients and how they would produce the gain of function
age of sporadic cases of autism have de novo copy num-
ber variations, typically in one gene within the genome
(Sebat et al., 2007), but the link between those results
and the dysregulation that leads to a brief period of exces-
sive growth in early development in frontal, temporal, and
amygdala regions is unclear. Important new findings are
the association of the MET gene with autism in multiplex
families and reduced expression levels of MET (Campbell
et al., 2006) and members of its signaling pathway in
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
temporal lobe in postmortem autism studies (Campbell
et al., 2007). However, reduction in MET expression
would seem to predict reduced growth and neural cir-
cuit formation, making it unclear how this might relate to
early brain overgrowth and excess gray and white matter
There are no gene-association studies of the early de-
velopmental phenotype of autism. It might be that the
genes driving early developmental defects are not those
that drive the reaction to those original developmental
conditions. That is, causal and reactive genetic and non-
genetic factors may be distinct. Thus, it remains an un-
tested possibility that some portion of the heterogeneity
of the autism phenotype reflects individual variation in
genes and gene expression effects in response to patho-
logical conditions set up during early development. Out-
come variability may be shaped by variability in genes that
must respond to earlier generated abnormal neural condi-
tions. Thus, genotype-phenotype association studies that
employ variation inbrainsize, graymattervolumes,immu-
nological measures, functional activation patterns, lan-
guage skills, social skills, or seizures in older children or
adults with autism might be picking up relationships that
reflect genetic factors that shape how each individual’s
nervous system responds to early developmental defect.
It would seem possible that more powerful gene-asso-
ciation studies would utilize measures of the biological
defects that are closest to the initial maldevelopment
rather than defects that may be the long-term outcome
of a long cascade of altered brain-gene expression-expe-
Forinstance, supposethat onefundamental defect pro-
ducing excess brain size is excess neurogenesis. Such an
aimed at correcting this excess, and individual variation in
genes regulating such reactions might lead to variation in
some patients having prolonged and/or profound proa-
poptotic activation while others might not. Genotype-
phenotype studies using, for instance, mature brain size,
amygdala size, or molecular markers of neuroinflamma-
tion might detect genes that influence variations in the
proapoptotic reaction, and not genes that started the
problem in the first place, namely genes that generated
the abnormal excess number of neurons.
What If: Excess Neurons and the Formation of
is an excess of neuron numbers, particularly an excess of
excitatory pyramidal neurons. Excess pyramidal neurons,
could potentially mean an excess of axons, dendrites,
synapses, and myelin, and that would produce the en-
larged volumes of gray and white matter as well as the
overall enlarged brain volume reported in MRI studies of
young autistic children (discussed above). Additionally,
excess neurons could also mean increased brain weight
in young autistic children. An increase in excitatory pyra-
midal neurons could produce an imbalance of excessive
excitation relative to inhibition with its many adverse elec-
trophysiological and behavioral consequences as so elo-
quently theorized by Rubenstein and Merzenich (Ruben-
stein and Merzenich, 2003). Such a mismatch in the ratio
of excitatory to inhibitory neurons might tip the balance
toward excessive and less controlled excitability, reduced
selective responsiveness, spatially broad but disorga-
nized cortical assemblies, and poorly synchronized vol-
leys of signals from such excitable but diffuse and disor-
ganized patches to lower-order systems (Courchesne
and Pierce, 2005a).
Excess neuron numbersin early development seemsan
intuitively neat fit to the apparently proapoptotic neural
environment in the mature brain (summarized above). In-
deed, it may be that the most valuable clues to the causes
of autism from the adult autistic postmortem literature are
the findings that abnormal molecular, potentially neuroin-
ron numbers. If such molecular processes are engaged at
a relatively young age in autism, by 2–4 years of age per-
haps, then arrest of macroscopic growth as described in
MRI studies (reviewed above) becomes understandable,
as does arrest of minicolumn growth in early childhood
(also mentioned above).
An extreme excess of neurons in frontal and temporal
cortices, where cerebral overgrowth is at its maximum
according to MRI studies, could also explain why the first
signs of autism begin between roughly 9 months and
2 years (and not typically later or much earlier) and involve
lack of high-order language, social, emotional, and com-
munication skills. It is during this developmental period
that the formation of neural circuitry in these regions is
most exuberant but also at its most vulnerable stage
(Courchesne and Pierce, 2005a). In frontal cortex at birth,
neurons are very small, dendritic arbors have barely
and synapses are a fraction of their mature size and num-
bers (Conel, 1939, 1941, 1951, 1959; Huttenlocher, 2002),
but this changes dramatically over the next 2 years (see
Figure 6). The building of complex and intricate circuits
in higher-order systems is a stunning feat of the infant
and toddler brain, and within 18–24 months behavioral
capacity has soared (Bates et al., 2003).
Excess neuron numbers could profoundly disrupt this
major event of circuit formation in frontal and temporal
cortices and thereby impede the emergence of higher-
orderbehavior skills. Forexample, mismatches in theratio
of afferent axons from further noncortical sites to an ex-
cessively large pool of frontal and temporal cortical target
neurons would produce broad, sporadic connectivity
within the sites of innervation. Such disparate connectivity
could potentially leave some neurons underinnervated
and alter the afferent signals to these higher-order cortical
regions. Resulting cortical ‘‘functional maps’’ would
appear overall ‘‘normal,’’ but long-distance functional ‘‘in-
teractions’’ would be weakened and noisy. This could ex-
plain one of the most consistent abnormalities reported in
the adult autism literature, which is reduced long-distance
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
functional connectivity between frontal and temporal
higher cortices and between these cortices and other
structures (Castelli et al., 2002; Cherkassky et al., 2006;
Courchesne and Pierce, 2005b; Just et al., 2004, 2007;
Kana et al., 2006; Koshino et al., 2007; Murias et al.,
2007; Rippon et al., 2007; Villalobos et al., 2005).
Further, mismatches in the ratio of local intracortical or
short-distance axons produced by excess neurons within
higher-order systems relative to connections generated
by other distant and low-level neural populations would
lead to local and short-distance connections dominating
numerically and functionally over long-distance afferent
the numeric and signal-timing advantages of local and
short-distance (and hyperexcitable) connections would
easily win out over the inadequate numbers and timing
of long-distance afferents. Such short-distance connec-
tions are in a so-called ‘‘radiate’’ white matter region
immediately underlying cortex, and one MRI study of 7-
to 11-year-old autistic subjects has reported volumes of
this white matter to be excessive, with deviation from nor-
mal being greatest under frontal and temporal cortices
(Herbert et al., 2004). Also, fMRI and EEG studies of func-
tional connectivity in autism have consistently reported
reduced long-distance functional connectivity, and from
that, many have speculated that there might be reduced
2002; Cherkassky et al., 2006; Just et al., 2004, 2007; Kana
etal., 2006;Koshinoetal., 2007; Masonetal., 2007; Murias
et al., 2007; Rippon et al., 2007; Villalobos et al., 2005).
Perhaps most importantly, the imbalance of local and
would disrupt the formation and functioning of large-
scale, long-distance assemblies. Such large-scale, long-
distance networks include the mirror neuron system and
the resting network, systems that involve frontal, tempo-
ral, and parietal cortices and mediate the sense of the
physical and psychological self in relationship to physical
and psychological actions and states of others (Frith and
Frith, 2006; Iacoboni and Dapretto, 2006). The emergence
and elaboration of these major physicaland psychological
social functions in autism are likely derailed by failure of
large-scale, long-distance networks to operate.
The fundamental failure of such large-scale networks to
form correctly may also be behind the failure of normal
language acquisition in autistic toddlers. In our fMRI stud-
ies of 1- to 3-year-old typically developing toddlers, we
observed functional activation patternsin responseto lan-
guage and concluded that the dramatic burst of language
acquisition in normal toddlers depends on recruitment of
large-scale networks involving frontal, temporal, occipital,
and cerebellar regions (Redcay et al., 2007a). Studies in
our laboratory with autistic toddlers are aimed at testing
the theory that large-scale, long-distance networks fail
to function in the young autistic brain for the reasons just
Figure 6. Golgi-Stained Sections of Middle Frontal Gyrus Showing Growth of Pyramidal Neuron Soma and Dendrites
Thenormalnewborn hassparseneuralcircuitry,andthen,withincreasingage,thereisatremendousincreaseinthecomplexity ofneuralcircuitrythat
is illustrated by the great increase of dendritic arbors from birth to 2 years. From Courchesne and Pierce (2005a), adapted from Nolte (1993), whose
figure combined panels from Conel (1939, 1941, 1951, 1959).
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
Lastly, at a momentous period when it is vital to form
large-scale networks out of the chaos of excess neurons
and potentially poorly inhibited and organized short-dis-
increase the chances that activity-dependent mecha-
nisms could stabilize adaptive connections and eliminate
nonadaptive ones. The interesting and hopeful view of
this model is that higher-order systems and large-scale
network connections may be present in autism, but stand
at a disadvantage to the local overconnectivity and noise
produced by the excess excitatory neurons.
In fact, new studies now show a remarkable effect:
namely, extrinsic factors that serve to increase attention,
motivation, or interest can cause more normal functional
activation in brain regions and networks in high-function-
ing autistic individuals (Hadjikhani et al., 2004, 2007;
Pierce et al., 2004; Wang et al., 2004, 2007). Examples
of this phenomenon come primarily from the face-pro-
cessing literature (Dalton et al., 2005; Hadjikhani et al.,
2004; Pierce et al., 2004) and more recently during tasks
of irony comprehension (Wang et al., 2007). Initial studies
of face processing in autism revealed reduced or absent
activity in the fusiform gyrus as compared to controls
(Critchley et al., 2000; Pierce et al., 2001; Schultz
et al., 2000). Recent research, however, has revealed
that increasing interest or attention to the faces by show-
ing familiar faces (Pierce et al., 2004) or increasing gaze
fixation to the face by inserting a dot on the face and in-
structing subjects to attend to the face results in more
normal fusiform activity (Hadjikhani et al., 2004, 2007).
Indeed, Dalton et al. (2005) demonstrated that increased
in attention to the eye region of the face is correlated
with increased levels of fusiform and amygdala activity
in autism. Similarly, during tasks of irony comprehension,
typically developing children automatically engage me-
dial frontal cortex, but children with autism do not do
so unless specific instructions are given to attend to
the facial expression or tone of voice (Wang et al.,
2007). These series of studies support the position that
local and long-distance networks can be activated in
autism if sufficient instruction, motivation, or interest is
given to the participant to overcome the natural ten-
dency to not engage these regions. In other words,
the spontaneous activity of the various local and long-
distance networks is abnormally biased by the various
mismatches mentioned above toward not automatically
engaging in the presence of social-emotional cues.
This raises the question of what conditions can over-
come the threshold of this intrinsic and abnormal spon-
taneous activity. In this context, not enough can be
said about how important it is to learn from those fMRI
studies that have demonstrated conditions under which
more normal functional activation and connectivity pat-
terns can appear during the processing of faces
(Dalton et al., 2005; Hadjikhani et al., 2004, 2007; Pierce
et al., 2004; Wang et al., 2004). Such fMRI experiments
with older autistic children and adults may point the way
for social, emotional, and communication intervention
approaches with infants, toddlers, and young children
at-risk for autism.
New MRI and head circumference studies have given rise
to a new hypothesis—autism involves two phases of early
brain growth pathology (Courchesne et al., 2001, 2003;
Courchesne and Pierce, 2005a): early brain overgrowth
at the beginning of life and slowing or arrest of growth
during early childhood (Figure 1). In some percentage of
patients, a third phase, degeneration, may be present in
some brain regions by preadolescence and continue into
adulthood. This new theory of neural maldevelopment
in autism highlights the first years of life as a key period
when it appears that both malformation of neural circuitry
are appearing (Landa and Garrett-Mayer, 2006; Wetherby
et al., 2004; Zwaigenbaum et al., 2005). During the rela-
tively brief and pivotal early period, the beginning steps
in neural and behavioral maldevelopment in autism can
be revealed as it occurs, rather than the outcome. The op-
portunity for discovering the underlying genetic and other
factors that are driving maldevelopment may be at its
maximum during this time. Genetic factors undoubtedly
play a role in the early overgrowth pathology in autism,
and their identification will have a major impact on under-
standing and treating those with the disorder. Knowledge
of the defects and genetic or other factors involved will
also likely reveal more specific and useful biomarkers of
risk for autism, diagnostic outcome, and treatment re-
sponsiveness. Ultimately, it may lead to targeted modes
of medical and behavioral treatment that greatly benefit
The neural defects that drive this overgrowth remain
unknown. Therefore, studies of the underlying neural de-
fects causing early brain overgrowth in autism are of the
utmost importance. It must be assumed that more than
one major underlying developmental neural defect drives
this complex behavioral disorder.
In this paper, we propose the hypothesis that one
such defect is an excess of neurons (and their axonal
and dendritic processes and synapses) in key frontal
and temporal cortical regions that mediate higher-order
social communication, emotion, and language functions.
By out-competing afferents from distant regions for syn-
aptic space, diluting the impact of signals from distant
brain regions, and generating excessive local excitation,
excess neuron numbers may generate exuberant local in-
tracortical and short-distance cortico-cortical interactions
that impede the function of large-scale, long-distance in-
teractions between brain regions. Because large-scale
frontal, temporal, parietal, and subcortical networks un-
alterations in brain architecture could relate to the early
clinical manifestations in autism. In autism, then, excess
local, but disordered, maps may win out over global re-
tion most readily attended to, processed, and acted upon.
Neuron 56, October 25, 2007 ª2007 Elsevier Inc.
Evidence and this model nonetheless indicate that large-
scale socio-emotional and language networks can be
engaged in many autistic individuals, albeit with greater
than normal difficulty. Though strongly skewed away
from being spontaneously prepared to attend, process,
and react to social information, the diminished functional
coherence in such networks may not preclude effective
activation, particularly in individuals with less excess
of neurons. The challenge then is to identify at-risk infants
and toddlers and start them on treatment protocols that
maximally engage and reinforce the functioning of these
critical large-scale networks. Neurobiological studies of
autism in the first years of life offer great hope for making
progress in understanding how early neural patterning ab-
normalities at the local and global level of organization
arise and what biological as well as behavioral interven-
tions may improve developmental outcome.
This work was supported by NIMH grant 1P50MH081755-01 and
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