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Running head: NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM 1

A Review: Neurodevelopment and Neuroanatomy of Individuals with Autism Spectrum

Disorder; Implications for Therapist

A Research Paper

Presented to

The Faculty of the Adler Graduate School

____________________

In Partial Fulfillment of the Requirements for

the Degree of Master of Arts in

Adlerian Counseling and Psychotherapy

____________________

By:

Meghan K. Williams

March 2010

NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM

1a

Acknowledgements

Cyndi Frank: I deeply appreciate all of your support, encouragement, wisdom, and the

sacrifices you made for me. You are a strong, devoted, loving, and amazing mom

and I love you very much. Thank you for being believing in me, helping me reach

my potential, cheering me on, and for being my hero.

Chris Williams: My love, thank you for being a wonderful, caring, accepting, and

supportive husband; for being a true best friend. Your love and encouragement

over the years is greatly appreciated.

James Patrick: You were the reason for my passion for autism. It is because of wanting

to help make your life better, I am in this field. Thank you for inspiring me. You

will always be my little brother and I love you.

Barb Luskin: Thank you for your support, determination, wisdom, insight, and

your time mentoring me. Also, thank you for challenging me to succeed. I truly

value and admire you. Your passion for autism and helping others motivates and

inspires me to do the same. I want to share the knowledge you have given me

with others.

Adler Graduate School’s faculty and staff: Thank you all for your encouragement over

the past years. You have become a second family to me and have made AGS

feel like home, thank you for doing this. I appreciate all of your hard work and

dedication to the school and the field. Thank you for your time, patients,

understanding, and for teaching me how to have the courage to be imperfect.

All of my friends and family: Thank you for your love and support over the years.

NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM 2

Abstract

This is an in-depth review of current research literature on the neurodevelopment and

neuroanatomy of individuals with Autism Spectrum Disorders (ASD). To gain a better

understanding of ASD, researchers have turned to the brain to seek answers. Currently,

researchers are exploring different sections of the brain to determine if there is

overgrowth, undergrowth, or abnormalities that would lead to the symptoms of autism.

Researchers have found significant differences in certain parts of the brain, while no

differences in other parts. Through the results of these studies, researchers, therapists,

and other individuals who work with ASD clients are gaining a better, more in-depth

understanding of the etiology of ASD, the usefulness of early intervention, as well as

techniques and strategies to be used in treatments.

NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM 2a

Outline

A Review: Neurodevelopment and Neuroanatomy of Individuals with Autism

Spectrum Disorder; Implications for Therapist

Introduction

Definition of Autism

DSMIV-TR Criteria

The Brain

Neurodevelopment

Overgrowth

Connectivity

Brain volume

Whole-brain and specific regions

Biological bases

Neurotrophins

Head circumference

Infancy

Childhood

Postmortem

Genes

Neuroanatomy

White and gray matter

Lobes and cortices

Cerebral cortex

NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM 2b

Frontal lobe and cortex

Orbitofrontal lobe

Medial temporal lobe

Anterior cingulate cortex

Cerebellum

Thalamus

Corpus callosum

Amygdala and hippocampus

Other abnormal structures

Discussion

Directions for Further Research

Implications for Therapist

Application for Adlerian Therapists

Pampering

Encouragement

Courage to be imperfect

Forward movement

Black and white thinking

Life Style Analysis

Early Recollections.

Life Task

“The Question”

NEURODEVELOPMENT AND NEUROANATOMY OF AUTISM 2c

Conclusion

References

Appendix


A Review: Neurodevelopment and Neuroanatomy of Individuals with Autism

Spectrum Disorder; Implications for Therapist

Autism has been around for centuries. Some individuals in the field speculate

that famous people in history were on the autism spectrum. A few of the most well

known are Albert Einstein, Sir Isaac Newton, Ludwig van Beethoven, Wolfgang

Amadeus Mozart, Lewis Carroll, and Vincent van Gough. Although it may never be

known whether these individuals were on the autism spectrum, we do know how

prevalent autism has become in our society.

There has been an increase in autism spectrum disorders (ASD) diagnosis over

the past 25 years. Because of this increase, there is a need for refined diagnostic tools,

more services and treatment options, as well as more research. Researchers are trying

to gain a better understanding of the etiology,

Autism begins before 3 years of age, but exactly when it begins is unknown.

Autism is hypothesized to be a complex disorder involving brain growth and perhaps

brain maturation (Lainhart, 2003). Researchers generally feel that autism is a

malfunction of the central nervous system (New Dictionary of Cultural Literacy, n. d.).

Additionally, research efforts have aimed at pinpointing biological markers to facilitate

early diagnosis and intervention, identification of such markers also help to better

understand the pathomechanisms leading to these developmental anomalies

(Dissanayake, Bui, Huggins, & Loesch, 2006).

This literature review will cover a portion of the current research available on the

neurodevelopment and neuroanatomy of individuals with autism. Specifically, it reviews

research on brain overgrowth, connectivity, volume, and head circumference, as well as


specific brain structures and directions for further research. In addition, it addresses

implications for therapy and the need for therapist to adapt their therapeutic approaches

when working with ASD clients.

Definition of Autism

The word autism comes from the Greek word autos meaning “self” and combined

with the suffix ismos meaning “of action or of state” (Online Etymology Dictionary). Leo

Kanner and Hans Asperger first used the word autism in 1940s. Both men used the

term in their individual publications, Kanner in 1943 and Asperger in 1944, but neither

knew the etiology (Sicile-Kira, 2004). Today, the term autism refers to a spectrum of

disorders with specific characteristics, and researchers are still trying to determine the

etiology.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is

variable in expression (Merriam-Webster's Medical Dictionary) and with an estimated

genetic origin of 90% (Palmen et al., 2005). ASD is comprised of several different

phenotypes each of which has the same triad of deficits. These deficits are of impaired

social interaction, impaired communication, and restricted interests and repetitive

behaviors (Belmonte et al., 2004). Other ASD characteristics are a deficit of executive

function (Ozonoff et al., 1991), complex information processing (Minshew et al., 1997),

theory of mind (Baron-Cohen et al., 1985), and empathy (Baron-Cohen, 2002).

DSM-IV-TR Criteria

The Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR)

(American Psychiatric Association, 2000) is what mental health professionals us to

diagnose their clients. The most current edition was published 1994, but the newest


revision was published in 2000. A new edition is currently in the works and the projected

release date is in 2012.

In the DSM-IV-TR, the two major diagnoses under the category of Autism

Spectrum Disorders (ASD) are autistic disorder and Asperger disorder. The criteria for

both disorders are as follows:

299.00 Autistic Disorder:

• Qualitative impairment in social interaction

• Qualitative impairment in communication

• Restricted, repetitive, and stereotyped patterns of behavior, interests, and

activities

299.80 Asperger’s Disorder:

• Qualitative impairment in social interaction

• Restricted, repetitive, and stereotyped patterns of behavior, interests, and

activities

• Clinically significant impairments in social, occupational, or other important areas

of functioning

• No clinically significant delay in language

• No clinically significant delay in cognitive development of age-appropriate self-

help skills, adaptive behaviors, and curiosity about the environment in childhood

In order for individuals to be diagnosed with ASD, they must meet a specific

number of the criterions from the DSM-IV-TR. Often time the clinician will use additional

assessment tools, inventories, and questionnaires. Ultimately the clinician makes the

decision as to rather or not individuals have ASD.


The Brain

Neurodevelopment

Overgrowth. Brain overgrowth in autism is an area researchers are trying to

understand and determine its effects on autism. Current studies have shown brain

overgrowth occurring during the first two years of life and at the time when the formation

of cerebral circuitry is at its most abundant and vulnerable stage (Courchesne, 2004).

The most significant overgrowth occurs in cerebral, cerebellar, and limbic structures of

the brain. These structures manage higher-order cognitive, social, emotional, and

language functions (Courchesne, 2004).

A study by Ghaziuddin, Zaccagnini, Tsai, & Elardo (1999), compared

megaloencephaly in autism to megaloencephaly in attention deficit hyperactivity

disorder (ADHD. Megaloencephaly is an abnormal enlargement of the brain (Stedman's

Medical Dictionary). The researchers compared 20 male subjects with autism with 20

male controls with ADHD (Ghaziuddin, Zaccagnini, Tsai, & Elardo, 1999). Four of the

subjects and five of the controls had evidence of megaloencephaly. Additionally, the

four subjects with megalencephaly were also hyperactive and impulsive like their

counter parts in the control group.

These findings suggest that megaloencephaly may not be specific to autism

(Ghaziuddin, Zaccagnini, Tsai, & Elardo, 1999) and may have to do more with other

neurological disorders. In addition, when megaloencephaly is present, it may indicate

the presence of additional symptoms such as hyperactivity and impulsivity (Ghaziuddin,

Zaccagnini, Tsai, & Elardo, 1999). More research is needed to determine the correlation

between ASD, ADHD, and megaloencephaly.


Other studies have also found that the frontal cortex and white matter show the

greatest early overgrowth followed by slowing of growth (Carper et al., 2002). These

regions also show sharply reduced growth thereafter (Courchesne & Pierce, 2005).

These studies will be discussed in more depth in section Frontal Cortex and Gray and

White Matter.

Connectivity. The brain is a complex system of neural connections. These

connections are responsible for sending signals and messages between the different

parts of the brain and the rest of the body. Problems arise whenever there is a

disruption in the connection. Researchers are trying to determine how the connectivity

in the brain influences autism.

Scientist can differentiate local connectivity within neural assemblies. They are

able to discriminate long-range connectivity between functional brain regions (Belmonte

et al., 2004). Scientist can also separate the physical connectivity associated with

synapses. In addition, they can separate the pathways from the computational

connectivity associated with information transfer (Belmonte et al., 2004).

Just and colleagues (2004), did a study to determine if the connectivity in the

language part of the brains was different between a group of high-functioning autistic

participants and a control group. The two groups were measured using functional MRI

during a sentence comprehension exercise.

They determined that in two of the key language areas, Wernicke's and Broca's

area, the two groups differed in the distribution of activation. The autism group produced

reliably more activation than the control group in Wernicke's area. However, in the

Broca's area the autistic group had reliably less activation than the control group.


Furthermore, the functional connectivity between the various participating cortical

areas was consistently lower for the autistic group than the control group. Their findings

suggest that in the brain of individuals with autism, high local connectivity may develop

in tandem with low long-range connectivity. Additionally, the neural basis of disordered

language in autism involves a lower degree of information integration, as well as a lower

synchronization across the cortical network for language processing (Just et al., 2004).

Recent attempts at a theoretical synthesis have focused on abnormal neural

connectivity, and there seems some disagreement as to whether this abnormality

involves a surfeit (Rubenstein and Merzenich, 2003; Belmonte et al., 2004) or a deficit

(Brock et al., 2002; Just et al., 2004) of connectivity. Courchesne (1997), found that

deficits of long-range connectivity and coordination of cognitive functions in the

cerebellum. Like wise, Brock et al. (2002) proposed that underconnectivity between

separate functional brain regions in autism may reflect in a lack of EEG synchrony in the

gamma band. Moreover, high physical connectivity and low computational connectivity

may reinforce each other by failing to differentiate signal from noise (Rubenstein and

Merzenich, 2003; Belmonte et al., 2004).

Lewis and Elman (2008) hypothesized that a deviant brain growth direction will

lead to deviant patterns of change in cortical connectivity. They proposed that the

differences in brain size during development would alter the relative cost and

effectiveness of short- and long-distance connections. Additionally would influence the

growth and retention of connections.

They proposed that a reduced brain size would favor long-distance connectivity,

while brain overgrowth would favor short-distance connectivity. In addition, they


proposed that inconsistent growth, as seen in autism, would result in potentially

disruptive changes to established patterns of functional and physical connectivity during

development.

To explore this hypothesis, Lewis & Elman (2008) used neural networks, which

modeled interhemispheric interaction. These neural networks were grown at the rate of

either typically developing children or children with autism. They analyzed the influence

of the length of the interhemispheric connections at multiple developmental stages.

Lewis and Elman (2008) found that the networks that modeled autistic growth

were less affected by removal of the interhemispheric connections than those that

modeled normal growth. These results indicated a reduced reliance on long-distance

connections for short response times. This difference increased considerably at

approximately 24 simulated months of age. These results supported their hypothesis

that the deviant growth trajectory in autism spectrum disorders may lead to a disruption

of established patterns of functional connectivity during development, with potentially

negative behavioral consequences, and a subsequent reduction in physical

connectivity.

Brain volume. To further understand autism, researchers are turning to the brain

volume of individuals with autism. Researchers compare the brain volume of individuals

with autism to neurologically typical individuals. Resent studies suggest that early in

development there is an increased brain volume, while other studies suggest a

decrease in brain volume later in development.

Whole-brain and specific regions. MRI studies in young children with autism

revealed excessive volume of cerebrum, cerebral white matter (Courchesne et al.,


2001; Sparks et al., 2002; Herbert et al., 2003), or an increased total brain volume

(Piven et al., 1995; Aylward et al., 2002). Another MRI study of toddlers with autism

found that brain volume was 10% greater than average, with 90% of these toddlers

having volumes exceeding normal average, and occurring by 2-years-old (Courchesne

et at., 2001, Courchesne et al., 2003, Sparks et at., 2002). Furthermore, a MRI study

analyzed the neuroanatomy of 2-5-year-old girls and boys with autism, and found that

both the boys and girls with autism had significantly abnormally enlarged whole brain

volume (Bloss & Courchesne, 2007).

Rojas and colleagues (2006) did a study on the whole brain and correlated

regional volume changes with several autism symptoms. They performed MRI scans on

24 males with ASD and compared those to scans from 23 neurologically typical male

subjects. They used voxel-based morphometry (VBM) to analyze the regional gray

matter volume.

Rojas et al. (2006) found in the autism group that the volumes of the medial

frontal gyri, left pre-central gyrus, right post-central gyrus, right fusiform gyrus, caudate

nuclei, and the left hippocampus were larger than in the control group. They additionally

found some regions of the cerebellum exhibited smaller volumes in the autism group.

Furthermore, significant partial correlations were found between the volumes of the

caudate nuclei, multiple frontal and temporal regions, the cerebellum, and a measure of

repetitive behaviors. Their results also revealed that the caudate, cerebellar, and

precuneus volumes, as well as with frontal and temporal lobe regional volumes were

associated with social and communication deficits in the group with autism. Rojas et al.


(2006), concluded that VBM was sensitive to associations between social and repetitive

behaviors and regional brain volumes in autism.

Sparks and colleagues (2002) explored the specific gross neuroanatomic

substrates of the brain morphometric features in 45 3- 4-year-old children with ASD.

They compared the subject group with age-matched control groups of 26 typically

developing (TD) children and 14 developmentally delayed (DD) children. Sparks et al.

(2002) use three-dimensional coronal MRI to measure the volumes of the cerebrum,

cerebellum, amygdala, and hippocampus. The volumes were then analyzed with

respect to age, sex, volume of the cerebrum, and clinical status.

The children with ASD were found to have significantly increased cerebral

volumes as compared to the children with TD and DD (Sparks et al., 2002). Additionally,

Sparks et al. (2002) found the cerebellar volume for the ASD group was also increased

in comparison with the TD group. However, the increase was proportional to overall

increases in cerebral volume. Moreover, the measurements of amygdalae and

hippocampi in the ASD group revealed enlargement bilaterally that was proportional to

overall increases in total cerebral volume. In addition, the DD group had smaller

cerebellar volumes than both of the other groups (Sparks et al., 2002). They concluded

that the results suggested abnormal brain growth early in the developmental processes

of autism.

Herbert et al, (2003) conducted a study on 17 high-functioning boys with autism

and 15 neurologically typical boys. These two groups were compared using a MRI

whole-brain morphometric profile. This profile includes both total brain and major brain

region volumes.


In their study (Herbert et al, 2003) neuroradiologists reviewed the MRI scans of

both groups and determined the brains of all subjects to be clinically normal. The entire

brain was segmented into several different sections and those sections were divided

into subsections. After which volumes were formulated for each region and then

compared between both groups. Lastly, Herbert et al, (2003) used factor analysis to

group brain regions based on their intercorrelations.

Herbert and colleagues (2003) discovered the volumes were significantly

different between groups overall. In the group with autism, the diencephalon, cerebral

white matter, cerebellum, and globus pallidus-putamen were all significantly larger than

the neurologically typical group. They concluded the morphometric profile of the brain of

boy with autism suggests there is an overall increase in brain volumes as compared

with controls. Additionally, results suggest that there may be differential effects driving

these differences, and the cause is unknown, and further investigation is needed.

In a cross-sectional design, Aylward et al. (2002) reported brain volume in autism

to be larger than normal in 8-12-year-olds, but not in adolescents and adults. Also using

a cross-sectional design, Courchesne et al. (2001) found abnormally enlarged brain

volume in 2-4-year-olds, but not 5-16-year-old children with autism. Several other recent

MRI studies reported statistically non-significant differences in autistic brain volume at

4- 11-years-old (Carper et al., 2002), 5-13 years (Kates et al., 2004), 7-11-years-old

(Herbert et al., 2002, 2003, 2004), 8-45-years-old (Hardan et al., 2003), 17-47-years-old

(Rojas et al., 2002) and 18-43-years-old (Carper & Courchesne, 2005). The absence of

significant brain volume difference in older children and adults with autism (Courchesne

et al., 2001; Aylward et al., 2002) may suggests that early hyperplasia in autism is


followed by a plateau during which brain growth in neurologically typical individuals

catches up.

Hardan, Minshew, Mallikarjuhn, and Keshavan (2001) obtain measurements of

the brain volume in a sample of 16 males with autism and 19 neurologically typical

males. The third, fourth, and lateral ventricles, along with intracranial and cerebral

volumes were obtained through MRI scans for both groups. Their results found that the

mean cerebral and third ventricle volumes were significantly greater in the group with

autism than in the controls. These findings were consistent with previous studies.

Biological bases. Previous studies on individuals with autism have reported

brain volume increase of approximately 5%, especially in children, as compared to

neurologically typical control groups. Palmen et al. (2005) hypothesized that if this brain

volume increase is genetically determined, then biological parents of individuals with

autism might be expected to also show brain or intracranial enlargement. They

suggested that identifying structural brain abnormalities under genetic control was

importance as it could represent endophenotypes of autism.

In their studies, Palmen and colleagues (2005) used quantitative anatomic brain

MRI of different intracranial areas in biological, non-affected parents of individuals with

autism and in healthy, closely matched control subjects. Palmen et al. (2005) measured

the total brain volume, as well as the frontal, parietal, temporal, and occipital lobe

volumes. The cerebral and cortical gray and white matter where also measured along

with the cerebellum, laterals ventricle, and third ventricle.

Palmen et al. (2005) found no statistically significant differences between the two

groups in any of the brain volumes. They concluded that since the intracranium was not


enlarged in the subject group, it is unlikely that their brain volumes had originally been

enlarged and have been normalized. Additionally, increased brain volume in autism

might be caused by the interaction of parents’ genes, possibly with an additional effect

of environmental factors. On the other hand, increased brain volumes might reflect

phenotypes of autism.

Neurotrophins. At the biochemical level, there is a link between enlarged brain

volume and increased levels of neurotrophins (Akshoomoff, Pierce, & Courchesne,

2002, Courchesne et al., 2001). The neurotrophins were found in the neonatal blood

spots of infants who later received a diagnosis of autism (Nelson et al., 2001). These

factors have been known to increase neuronal survival (Lewin & Barde, 1996).

Additionally, they play an important role in central synapse formation, as well as

maturation (Vicario- Abejon, Owens, McKay, & Segal, 2002).

In addition, there is evidence that the neurotrophic factors also play an important

role in immunomodulation (Nassenstein et al., 2003), angiogenesis (Kraemer &

Hempstead, 2003), and body metabolism (Chaldakov, Fiore, Hristove, & Aloe, 2003).

Furthermore, the evidence for the role of neurotrophins and neuropeptides in bone

metabolism and growth (Garcia- Castellano, Diaz-Herrera, & Morcuende, 2000)

suggests that the increased levels of these factors may affect both brain development,

as well as linear growth in autism.

Head circumference. Researchers are trying to determine if head growth is an

indicator of autism. Lainhart (2003) suggested that if increased head growth in infancy is

a risk factor for autism, then it must precede the onset of the disorder. Increased rate of

head growth during infancy might precede parental and clinical recognition of autism


even if the underlying neurological differences are already present. Recognition of a

disorder is not always coincident with its onset. Several research studies explored the

possibility of head circumference as being either an identifying or a determining factor in

autism.

Infancy. It appears that at birth HC is within normal range or is slightly smaller

than normal for the majority of autism cases. Macrencephalic HC at birth in autism is

uncommon, occurring in approximately 6% of all autism cases (Courchesne & Pierce,

2005). Different research groups have found similar average newborn HC size in autism

(Courchesne & Pierce, 2005). The average HC at birth in autism was 34.7 cm in

Gittberg and de Souza (2002) study, 34.41 cm in Lainhart et al. (1997) study, and 34.65

cm in Courchesne et al. (2003) study, as well as Huttman et al. (2002) reporting the

same average range for their sample.

Some studies reports a very small percentage of autistic newborns have an

extremely large HC. For instance, excessive HC at birth in autism was reported for 4 of

42 (Gillberg & de Souza, 2002), 5 of 206 (Mason-Brothers et al., 1990), 3 of 51

(Lainhart et al., 1997), and 1 of 15 (Courchesne et al., 2001) cases. Among a sample of

autistic children who were pre-selected because of having clinical macrencephaly, only

1 of the 18 had macrencephaly at birth, 1 of the 18 had microcephaly at birth, and the

remaining 16 were normencephalic (Stevenson et al., 1997).

Courchesne, Carper, and Akshoomoff (2003) conducted a retrospective analysis

of head circumference (HC) measurements. The findings suggested that much of the

overgrowth occurred postnatally within the first 6-14-months (Courchesne et al., 2003).

This overgrowth seemed to coincide with what is normally a period of exuberant


synaptogenesis, dendritic arborization, and ongoing myelination (Courchesne et al.,

2003). Courchesne, Carper, and Akshoomoff (2003) also reported that 59% of the

infants diagnosed with ASD showed a HC increase of 1.5-2 S.D. or more across the first

year of life as compared to 6% of normal infants. This overgrowth was concluded by

about 2 years of age.

Their study also measured for correlations between HC in the first year of life and

later neuroanatomical outcome (Courchesne, Carper, & Akshoomoff, 2003). They found

that in the infants with ASD, the HC size at birth and HC overgrowth by the end of the

first year of life were strongly correlated with abnormal cerebellar and cerebral volumes

at 2-5-years-old. Courchesne, Carper, and Akshoomoff (2003) concluded that the

clinical onset of autism appears to be preceded by two phases of brain growth

abnormality. The first abnormality is a reduced head size at birth, and the second is an

overgrowth in head size between 1 to 2 months and 6 to 14 months. Abnormal rates of

head growth may serve as an early detection for autism.

Using linear mixed-effects models, Dissanayake, Bui, Huggins, and Loesch

(2006) compared the HC, height, and weight measurements of three infant groups. The

measurements were extracted from health records over the first 3 years of life for 16

children with high-functioning autism (HFA), 12 children with Asperger disorder (AsD),

and 19 typically developing children. They found that the HFA and AsD groups were

similar in their HC, height, and weight, and had a higher growth rate than the control

group. Dissanayake, Bui, Huggins, and Loesch (2006) concluded that the results

indicate that in autism, growth dysregulation is not specific to the brain but also involves

growth in stature.


Childhood. Gillberg and de Souza (2002) did a study of head circumference

(HC) in children with Asperger disorder (AsD), lower functioning autism, and typically

developing children. Their study determined that the children with AsD were more likely

to have an enlarged HC at birth as compared to the other two groups. Moreover, the

AsD group was likely to have a larger HC later in development.

A study by Barthotomeusz and colleagues (2002) tested the correlation between

HC and brain volume in children with autism and a control group. They used MRI to

gather the data. Their study reported that in both children with autism and the control

group, HC was an accurate index of brain volume in young children (Barthotomeusz et

al., 2002).

The objective in a study by Hazlett et al. (2005) was to examine brain volume

and HC in children with autism as compared with a control group. At the first time point

in an ongoing longitudinal MRI study of brain development in autism, they preformed a

cross-sectional study of brain volume on 51 children with autism and 25 control children

between 18 and 35 months of age. They also gathered retrospective longitudinal HC

measurements from birth to 3-years-old of 113 children with autism and 189-control

group of children.

Hazlett et al. (2005) found significant enlargement in cerebral cortical volumes in

the ASD group. In addition, the ASD group had enlargement in both white and gray

matter. This enlargement was generalized throughout the cerebral cortex. It was also

determined that the HC appeared normal at birth, but followed by a significant increased

rate of HC growth beginning around 12-months-old. Finally, they concluded that indirect


evidence suggests that this increased rate of brain growth in autism may have its onset

postnatally in the latter part of the first year of life.

Head growth rates are often accelerated in autism, so to explore this further

Sacco et al., (2007) devised a study aimed at defining the clinical, morphological, and

biochemical correlates of HC in autistic patients. HC were measured in 241 individuals

with ASD, 3-16-years-old. They assessed clinical parameters using the Autism

Diagnostic Observation Schedule, Autism Diagnostic Interview- Revised, Vineland

Adaptive Behavioral Scales, intelligence quotient (IQ) measures, and an ad hoc clinical

history questionnaire. Sacco et al., (2007) also recorded the height and weight of the

participants, as well as their serotonin blood levels and peptiduria.

Sacco et al., (2007) identified that the distribution of HC was significantly skewed

toward larger head sizes. Additionally, macrocephaly was part of a broader macrosomic

endophenotype, which was characterized by highly significant correlations between HC,

weight, and height. Likewise, a HC >75th percentile was associated with more impaired

adaptive behaviors and with less impairment in IQ measures, as well as less impaired

motor and verbal language development. Moreover, large HC were significantly

associated with a positive history of allergic/immune disorders both in the patient and in

first-degree relatives. Their study demonstrates the existence of a macrosomic

endophenotype in autism. Moreover, it points toward pathogenetic links with immune

dysfunctions that they speculate either lead to or are associated with increased cell

cycle progression and/or decreased apoptosis.

Postmortem. Redcay & Courchesne, (2005) conducted a postmortem study on

individuals who had been diagnosed with ASD. They reviewed reports of autism head


circumference (HC), MRI, and postmortem brain weight (BW) were identified and

analyzed. Next, Redcay & Courchesne, (2005) calculated percent difference from

normal values and standardized mean differences to compare brain size across studies

and measurement methods.

Their results revealed a largely consistent pattern of brain size changes. In

autism, they found there was a slight reduced of brain size at birth, followed by a

dramatic increased within the first year of life, and followed by a plateauing of brain size

by adulthood. Redcay & Courchesne, (2005) findings reveal a period of pathological

brain growth, occurring in the first years of life, before the typical age of clinical

diagnosis

Genes. The HOXA1 gene has a critical role in the development of hindbrain

neural structures. Conciatori and colleagues (2004) found an association between the

HOXA1 gene and autism. In a combined case-control and family-based association

design, Conciatori et al. (2004) showed that the HOXA1 A218G polymorphism

contributed significantly to findings of large HC in individuals with autism. It is unclear if

this genotype-phenotype correlation was specific to autism, or related to large HC. Their

study supports the usefulness of HC as a potential endophenotype in autism.

Neuroanatomy

White and gray matter. The white and gray matters of the brain are responsible

for passing information between the cell bodies. Researchers have conducted studies to

determine if there are any abnormalities of the brain matter in autism. Furthermore, if

there are abnormalities, are they isolated to specific brain regions or the whole brain?


Past studies determined that the brain sizes of individuals with ASD were

inversely correlated with the ratio of inter-hemispheric white matter to gray matter

(Jancke et al., 1997; Jancke et al., 1999; Rilling & Insel, 1999). An increases in both

white and gray matter volumes have also been reported, with especially pronounced

increases of 18% in cerebral and 39% in cerebellar white matter (Courchesne et al.,

2001). They also found that the maximum cerebral gray matter volume was reached in

individuals with autism by 2-4 years of age, which was about 4-6 years earlier than

typically developmi8ng children (Courchesne et al., 2001).

In a study of cerebral white matter, researchers discovered that the subregion

with the greatest deviation from normal was the white matter underlying the prefrontal

cortex (Herbert et al., 2004). Another white matter study of individuals with autism

reported abnormalities in white matter diffusion patterns (Barnea-Goraly et al., 2004).

These abnormalities appeared in the medial and dorsolateral frontal regions, temporal

lobes, temporoparietal junction, and anterior regions of the corpus callosum. Carper et

al. (2002), Walter et al. (2005), Buxhoeveden et al. (2006) conducted similar studies

and found abnormalities in the corpus callosum, and suggested it may play a role in the

pathophysiology of ASD.

In a fully automated voxel-based whole brain volumetric analysis, McAlonan et al.

(2005) compared children with ASD and age-matched controls. They hypothesized

there would be similar brain structural changes to prier studies and there would be

structural dysconnectivity in the children with ASD.

Findings indicated that the children with ASD had a significant reduction in total

gray matter volume, especially in the ventral and superior temporal regions, and


significant increase in cerebral spinal fluid volume (McAlonan et al., 2005). Like wise,

there was a reduction of the white matter in the cerebellum, left internal capsule, and

fornices. Palmen et al. (2005) and Hazlett, Poe, Gerig, Smith, and Piven (2006)

conducted similar studies, which had the same findings. The findings suggest

abnormalities in the anatomy and connectivity of limbicstriatal 'social' brain systems may

contribute to the brain metabolic differences and behavioral phenotype in autism

(McAlonan et al., 2005; Palmen et al., 2005; Hazlett et al., 2006).

Wassink and colleagues (2007) conducted a longitudinal brain MRI study to

evaluate whether 5-HTTLPR, a functional promoter polymorphism of the serotonin

transporter gene SLC6A4, influenced cerebral cortical structure volumes in 44 male

children, 2-4-years-old with autism. They found that 5-HTTLPR genotype influenced

gray matter volumes of the cerebral cortex. Additionally, there was an influence of gray

matter in the frontal lobe. They concluded that the SLC6A4 promoter polymorphism 5-

HTTLPR did influences cerebral cortical gray matter volumes in young male children

with autism.

Lobes and cortices. The brain has several subdivision called lobes and

cortices. Each section has a different role and responsibility in the central nervous

system. Certain cognitive and behavioral deficits suggest that there may be several lobe

and cortex abnormalities in patients with autism. However, little anatomical research is

available to verify or refute this (Carper & Courchesne, 2000), so researchers are

focusing on this area.

Cerebral cortex. The cerebral cortex is the extensive outer layer of gray matter

of the cerebral hemispheres. It is responsible for higher brain functions, coordination of


sensory information, voluntary muscle movement, learning, thought, reasoning,

memory, and the expression of individuality (The American Heritage New Dictionary,

n.d.). Investigations of the abnormal brain overgrowth in individuals with autism, which

occurs within the first years of life, is due to enlargement of cerebral, cerebellar, and

limbic structures (Carper and Courchesne, 2000; Carper et al., 2002; Courchesne et al.,

2001; Sparks et al., 2002). Later sections address the cerebellar and limbic structures.

In a previous cross-sectional study, Carper et al. (2002) found abnormal

enlargement of cerebral cortex and cerebral white matter volumes in 2-3-year-old

children with autism. They also found abnormally slow rates of volume change across

later ages. Additionally, in neuropathological studies of cerebral cortex in autism,

researchers found abnormalities of synaptic and columnar structures (Williams et al.,

1980; Casanova et al., 2002).

Researchers have found that the cortical areas most affected are precisely those

broadly projecting, phylogenetically, and ontogenetically late-developing regions

(Belmonte et al., 2004). These regions are essential to complex cognitive functions such

as attention, social behavior, and language (Belmonte et al., 2004). Like wise, in

neurobehavioral studies of individuals with autism, researchers have discovered

associations between cerebellar anatomic abnormalities and certain motor, cognitive,

and social deficits (Haas et al., 1996; Harris et al., 1999; Townsend et al., 1999; Pierce

and Courchesne, 2001). Moreover, recent genetic (Gharani et al., 2004; Vaccarino et

al., 2009) and MRI-behavior correlation (Akshoomoff et al., 2004; Kates et al., 2004)

studies suggest that cerebellar abnormality may play a more central role in autism than

previously thought.


Frontal lobe and cortex. The frontal lobe is the largest and forward most lobe of

each cerebral hemisphere in the brain (The American Heritage Science Dictionary,

n.d.). It is responsible for the control of skilled motor activities, mood, and the ability to

think and reason. Within the frontal lobe, there are two subdivisions, the dorsolateral

and medial frontal cortices, and their role is higher-order cognitive, language, speech,

and social functions (Courchesne & Pierce, 2005). Since individuals with autism deficits

in these areas, researches have conducted studies to determine the cause of the

deficits. Evidence from previous behavioral, imaging, and postmortem studies indicates

that the frontal lobe develops abnormally in children with autism. It is not yet clear to

what extent the frontal lobe is affected (Carper & Courchesne, 2005).

A study by Carper and Courchesne (2000) showed a frontal lobe cortex volume

increase in a subset of patients with autism. In addition, they found that the increase

correlates with the degree of cerebellar abnormality. Carper and Courchesne (2000)

concluded that the evidence of concurrent structural abnormalities in both the frontal

lobe and the cerebellum has important implications for understanding the development

and persistence of ASD (Carper & Courchesne, 2000), and there needs to b more

research.

Another study by Carper and Courchesne (2005) measured cortical volume in

four subregions of the frontal cortex in 2-9-year-old boys with autism and neurologically

typical boys. The dorsolateral region showed a reduced age effect in the boys with

autism when compared with control subjects. There was a predicted 10% increase in

volume from 2-9-years-old as compared with a predicted 48% increase for control

subjects. Additionally, there was a significant enlargement of the dorsolateral and


medial frontal regions in the 2-5-year-old boys with autism. However, they found no

significant differences in the precentral gyrus and orbital cortex. Carper and Courchesne

(2005) concluded that their data indicated regional variation in the degree of

frontocortical overgrowth with a possible bias toward later developing or association

areas.

Buxhoeveden et al. (2006) found cell minicolumns to be narrower in frontal

regions in brains of individuals with autism as compared with controls. Within the frontal

cortex, dorsal and orbital regions displayed the greatest differences while the mesial

region showed the least change. They also found that in contrast to the controls, the

minicolumns in the brain of 3-year-old children with autism were indistinguishable from

those of adults with autism in two of three frontal regions. They suggested that it might

have been due to the small size of the columns in the adult autistic brain rather than to

an accelerated development. Buxhoeveden et al. (2006) concluded that the presence of

narrower minicolumns supports the theory that there is an abnormal increase in the

number of ontogenetic column units produced in some regions of the brain of individuals

with autism during corticoneurogenesis.

Levitt et al. (2003) examined different brain regions in a group of 11-year-olds

boys with autism. They found abnormality of the dorsolateral frontal, medial frontal and

temporal regions. They also found anterior and posterior shifting of several frontal and

temporal sulci, with the greatest deviation from normal being superior frontal, inferior

frontal and superior temporal sulci and the Sylvian fissure.

Carper et al. (2002) assessed whether the volume abnormalities were limited to

particular cerebral regions or are pervasive throughout the cerebrum. They used MRI


scans to quantify volumes of frontal, temporal, parietal, and occipital lobe regions of 38

boys with autism and 39 normal control boys between 2-11-years-old. Several regions

showed signs of gray matter and white matter hyperplasia enlargement, as much as

20%, in 2-3-year-old patients. Additionally, they found that the frontal lobe showed the

greatest enlargement, where as the occipital lobe was not significantly different from the

controls.

Orbitofrontal cortex. The orbitofrontal cortex is part of the frontal lobe. It is

involved in multiple psychologic functions, such as emotional and cognitive processing,

learning, and social behavior (Hardan et al., 2006). These functions are variably

impaired in individuals with autism.

Recent evidence has implicated the orbitofrontal cortex (OFC) in the

pathophysiology of social deficits in autism. Girgis et al. (2007) conducted a MRI-based

morphometric study of the OFC involving 11 children with autism and 18 controls. They

found a decreased gray matter volume in the right lateral OFC in the autism group.

Additionally, they observed correlations between social deficits and white, but not gray,

matter structures of the OFC. Their findings support the role of OFC in autism and

warrant further investigations of this structure using structural and functional

methodologies.

Hardan et al., 2006 examined the size of the OFC, and its medial and lateral

subdivisions of 40 individuals with autism and 41 controls. They preformed MRI scans

on the two groups and analyzed. From the data, Hardan and colleagues (2006) found

no differences between the individuals with autism on any of the OCF measurements.


However, Hardan and colleagues (2006) compared the group with autism and

the controls, and found a smaller right lateral orbitofrontal cortex in children and

adolescents with autism. Furthermore, they observed a larger right lateral orbitofrontal

cortex in adult patients. In addition, they discovered a positive relationship between

circumscribed interests and all orbitofrontal cortex structures in the autism group. These

findings suggest the absence of global volumetric abnormalities in the orbitofrontal

cortex in autism, as well as indicate that there may not be a relationship between the

functional disturbances in this structure and anatomic alterations.

Medial temporal lobe. MRI studies show that there is enlargement of the

temporal cortex at 2-4 years of age in children with autism and failure to grow thereafter

(Carper et al., 2002). Part of the temporal cortex is the medial temporal lobe.

Researchers have discovered abnormalities in this section of the temporal cortex in

individuals with autism.

Salmond and colleagues (2005) examined the memory profile of children with

ASD and a control group, as well as the relationship to structural abnormalities. The two

groups completed a comprehensive neuropsychological memory battery and underwent

MRI for the purpose of voxel-based morphometric analyses. Additionally, to further

examine the role of the medial temporal lobe in ASD, they explored correlations

between cognitive and behavioral test scores and quantified results of brain scans.

Salmond and colleagues (2005) found a selective deficit in episodic memory with

relative preservation of semantic memory. Voxel-based morphometry revealed bilateral

abnormalities in several areas implicated in ASD including the hippocampal formation.

Furthermore, Salmond et al. (2005) found a significant correlation between parental


ratings reflecting autistic symptomatology and the measure of gray matter density in the

junction area involving the amygdala, hippocampus and entorhinal cortex. Their data

revealed a pattern of impaired and relatively preserved mnemonic function that is

consistent with a hippocampal abnormality of developmental origin. Moreover, the

structural imaging data highlight abnormalities in several brain regions previously

implicated in ASD, including the medial temporal lobes.

Anterior cingulate cortex. The anterior cingulate cortex (ACC) is a brain region

that assists the corpus Collosum in communication between the left and right

hemispheres. Functional imaging studies show that the ACC is associated with

integrating information with emotional overtones (Bush et al., 2000). The ACC helps in

anticipating and monitoring complex information and processing of conflicting

information. Furthermore, it assists in viewing personally important faces and

experiencing a feeling of social exclusion (Bush et al., 2000).

Researchers have discovered structural and functional abnormalities of the ACC

in individuals with autism (Courchesne & Pierce, 2005). Reported abnormalities have

also included abnormal enlargement of the ACC by 2-4-years-old (Carper et al., 2002),

reduced ACC volume in adult with autism (Haznedar et al., 1997), as well as

underdeveloped minicolumns in the ACC (Buxhoeveden et al., 2006). Research studies

have also found that lesions of the ACC lead to autism, decreased motivation,

decreased interest in novel information, and a reported reduced "will to act" (Allman et

al., 2002).

Pierce et al. (2004) used fMRI scans of individuals with autism and compared

them to scans of a control group. They examined the brain regions that are functionally


responsive during the presentation of socially familiar and significant faces. Those with

autism showed an absence of medial frontal lobe activity extending from ACC into

frontopolar area 10.

Courchesne and Pierce (2005) reviewed MRI, postmortem, diffusion tensor

imaging, PET, fMRI and MR spectroscopy studies of individuals with autism and found

consistent reports of abnormalities in the ACC. In another postmortem study of

individuals with autism, researchers found a small neuron size and increased neuron

packing density in the ACC, with the abnormalities being interpreted as evidence of

arrest in development (Kemper & Bauman, 1998). All of these findings suggest that

abnormalities of the ACC have a significant effect on autism.

Cerebellum. The cerebellum is the trilobed structure of the brain that sits

beneath the occipital lobe. It is responsible for the regulation and coordination of

complex voluntary muscular movement, the maintenance of posture, and balance (The

American Heritage Dictionary, n.d.). Several past neuropathological and neuroimaging

studies have found anatomical abnormalities in the cerebellum in individuals with autism

(Carper & Courchesne, 2000). Some researchers suggest that the cerebellum is the

most common site of anatomic abnormality in autism (Courchesne & Pierce, 2002).

MRI morphometry reveals hypoplasia of the cerebellar vermis and hemisphere

studies report reductions in numbers of cerebellar Purkinje cells (Belmonte et al., 2004).

Other MRI and postmortem neuropathological studies have implicated the cerebellum in

the pathophysiology of autism. MRI studies of the cross-sectional area of the vermis

have found both decreases and no difference in autism groups. Volumetric analysis of


the vermis may provide a more reliable assessment of size differences (Scott,

Schumann, Goodlin-Jones, & Amaral, 2009).

Scott, Schumann, Goodlin-Jones, and Amaral, (2009) conducted a volumetric

analysis of the structure of the whole cerebellum and its components in children and

adolescents with ASD. They acquired structural MRI scans male participants with ASD

and typically developing children. Findings showed a decrease of total vermis volume in

the ASD group when compared to the control. Their findings were congruent with past

studies.

Previous clinical observations suggest abnormalities within the cerebellum may

explain the severe behavioral deficits and increases in seizures in autism. To explore

this further, Walker, Diefenbach, and Parikh (2007) created a study, which used a

rodent model for the autism-like behaviors. In addition, they explored the possibility for

limiting autism-like behaviors via antiseizure brainstem and cerebellar circuitry. Their

findings suggest that specific neuronal populations within the cerebellum are

responsible for mediating exploration behavior. In addition, these neuronal populations

are similar to the circuitry involved in limbic motor seizures in that they are sensitive to

brainstem inhibition. Furthermore, their results suggest utilizing connection as a form of

treatment to control behavioral deficits seen in autism.

Cleavinger and colleagues (2008) studied the detailed morphometric analysis of

the cerebellum in individuals with autism. They acquired quantitative MRI scans from

the group with autism and compared them to neurologically typical controls.

Additionally, they measured the total cerebellum volumes and surface areas of four


lobular midsagittal groups. Cleavinger et al. (2008) found that in autism the cerebellar

structures proportional to head size and did not differ from typically developing subjects.

Although motor deficits are common in autism, the neural correlates underlying

the disruption are unknown. In order to gain an understanding of these deficits,

Mostofsky et al. (2009) used fMRI to examine neural activation and connectivity during

sequential, appositional finger tapping in 13 children with high-functioning autism (HFA)

and 13 typically developing children. They discovered that the HFA group demonstrated

diffusely decreased connectivity across the motor execution network relative to control

children.

Mostofsky and colleagues (2009) concluded the decreased cerebellar activation

in the HFA group might reflect difficulty shifting motor execution from cortical regions

associated with effortful control to regions associated with habitual execution.

Additionally, they concluded that decreased connectivity in the HFA group might reflect

poor coordination. These findings might help to explain impairments in motor

development in autism, as well as abnormal and delayed acquisition of gestures

important for socialization and communication. Motor deficits may be an early sign of

abnormal development (Mostofsky et al., 2009).

Thalamus. The thalamus is a large ovoid mass of gray matter that relays

sensory messages to the cerebral cortex (The American Heritage Dictionary, n.d.). It

assists in the coordination of nerve impulses relating to the senses of sight, hearing,

touch, and taste. Researchers are interested in determining if there are abnormalities in

the thalamus that could help explain autism.


Hardan et al. (2006) conducted a study to examine the volume of the thalamus in

autism. Additionally, Hardan and colleagues (2006) wanted to investigate the effect of

brain size had on the thalamus. This was in an attempt to replicate a previous study that

reported a relationship between brain volume and thalamus. In addition, they examined

the relationships between thalamic volumes and clinical features.

Volumetric measurements of thalamic nuclei were performed on MRI scans

obtained from 40 individuals with HFA and 41 healthy controls (Hardan et al., 2006).

The researchers observed no differences between the two groups for unadjusted

thalamic volumes. Additionally, they observed no linear relationship between the total

brain volume and thalamic volume in the HFA group. Furthermore, no correlations were

observed between thalamic volumes and clinical features. Hardan et al. (2006) stated

their findings were consistent with previous reports of an abnormal brain size effect on

the thalamus in autism, as well as supported the possibility of abnormal connections

between cortical and subcortical structures in this disorder.

The objective of Hardan et al. (2008) study was to also examine the relationship

between thalamic volume and brain size in individuals with Asperger's disorder (ASP).

Volumetric measurements of the thalamus were performed on MRI scans obtained from

12 individuals with ASP and 12 controls. Hardan et al. (2008), found a positive

correlation between total brain volume and thalamic size in controls, but not in ASP

subjects. These findings were consistent with previous studies. Hardan and colleagues

(2008) concluded that there was an abnormal relationship between the thalamus and its

projection areas in ASP.

Corpus callosum. The corpus callosum (CC) is the arched bridge of nervous


tissue that connects the left and right cerebral hemispheres. It communication between

the two hemispheres (The American Heritage Dictionary, n.d.), and is an index of

interhemispheric connectivity (Keary et al., 2009).

Hardan, Minshew, and Keshavan, (2000) measured the size of the seven

subregions of the CC in individuals with autism to determine if there were any

abnormalities, and they found that the areas of the anterior subregions were smaller.

Vidal et al. (2006) also conducted a volumetric study of the CC and found similar

abnormalities, concluding that there was abnormal cortical connectivity in autism. In

another volumetric study, Keary et al. (2009) examined the size of the CC in individuals

with autism to determine the relationship between the structure and cognitive measures

linked to interhemispheric functioning. Like the previous studies, Keary et al. (2009)

found reductions in total CC volume and in several of its subdivisions, as well as a

relationship between volumetric alterations and performance on several cognitive tests.

In a MRI study of 14 individuals with autism and 28 controls, Casanova et al.

(2009) found macroscopic morphological correlates to recent neuropathological

findings. These findings suggest a minicolumnopathy in autism. They observed that the

individuals with autism manifested a significant reduction in the aperture for

afferent/efferent cortical connections. Furthermore, they observed a reduced size of the

gyral window that directly correlated to the size of the CC. Casanova et al. (2009)

suggested that their findings might help explain abnormalities in motor skill development

and differences in postnatal brain growth.

Amygdala and hippocampus. The brain structures of the amygdala and

hippocampus are part of the limbic system. The limbic system is a group of


interconnected structures that are located beneath the cortex and are associated with

emotions, memory, motivation, and various autonomic functions (The American

Heritage Science Dictionary, n.d.). Previous neuropathologic studies of the limbic

system in autism have found decreased neuronal size, increased neuronal packing

density, and decreased complexity of dendritic arbors in hippocampus, amygdala, and

other limbic structures (Aylward et al., 1999).

Juranek and colleagues (2006) evaluated the volumes of the amygdala,

hippocampus, and whole brain MRI scans of children with autism, and identified a

significant neurobiologic relationship between symptoms of anxiety and depression with

amygdala structure and function. Their results highlight the importance of characterizing

comorbid psychiatric symptomatology in autism.

Past studies report an enlargement of the amygdala in children with autism

(Sparks et al., 2002; Schumann et al., 2004), but not in adolescents or adults with

autism (Aylward et al., 1999; Pierce et al., 2001; Schumann et al., 2004). Researchers

are trying to determine the correlations between the amygdala and autism, as well as

what causes the changes structural sizes.

Other abnormal structures. Several other research studies have discovered

abnormalities of different brain structures in individuals with autism. Langen, Durston,

Staal, Palmen, and van Engeland (2007) found an enlargement of the caudate nucleus,

and Hardan, Muddasani, Vemulapalli, Keshavan, and Minshew, (2006) discovered

increases in total cerebral sulcal, gyral thickness, and in temporal and parietal lobes.

Additionally, Hardan, Kilpatrick, Keshavan, and Minshew (2003) observed structural

abnormalities of the basal ganglia, which may explain motor deficits related to autism.


Van Kooten et al. (2008) found the fusiform gyrus and other cortical regions

supporting face processing were hypoactive in patients with autism. In addition, they

discovered neuropathological alterations, especially in neuron density, abnormalities in

total neuron number and mean perikaryal volume. Furthermore, this study may provide

important insight about the cellular basis of abnormalities in face perception in autism

Discussion

Directions for Further Research

Researchers have made strives towards understanding autism, however,

additional research is necessary. In the majority of the previous studies were comprised

of Caucasian male children. There is a need to have more studies encompassing a

wider age range, greater cultural diversity, and more female participants. Additionally,

future studies should strive for larger sample sizes in order to increase the validity.

In order to discover the causes of autism, early-warning signs, and effective

treatments of autism (Courchesne, 2004), future research should focus on elucidating

the neurobiological defects that underlie brain growth and structural abnormalities in

autism. Focusing on the abnormalities that appear during the critical first years of life is

essential. Future research focusing on the early process of brain pathology will also be

critical to elucidating the etiology of autism (Redcay & Courchesne, 2005)

Moreover, there is also a need for more data on head circumferences at birth,

postmortem studies, as well as additional longitudinal neuroimaging and

neuropathologic studies (Harden et al., 2001). These studies will help to provide a better

understanding of the complexities underlying increased brain size in autism.

Furthermore, similar studies of other pervasive developmental disorders are also


necessary before a case can be made that these developmental neuroanatomic

abnormalities are specific to autism (Courchesne et al., 2001). Through gathering

quantifiable data of the cross-sectional population of those with autism, researchers will

come closer to knowing the exact etiology of autism.

Implications for therapist

The current research concludes that there are significant developmental and

structural differences in brains of individuals with autism. Although the full extent of

these abnormalities is unknown, it is known that these abnormalities cause the brain to

function differently. Individuals with ASD process information differently, have difficulties

with executive functioning, struggle with perspective taking, and have sensory issues.

Knowing these issues provides therapists with an understanding of their clients with

ASD, which they can share, with clients. Educating clients with ASD about their brain

differences can help clients understand themselves and accept their differences.

Since individuals with ASD brains function differently, therapists must work with

them differently. Therapists are unable to use all of the same tools, techniques and

strategies as they use with their neurologically typical clients. They have to focus on

different route to the same goal and tailor their approach.

Therapists have to be more patient and understanding since progress is often

times slower with clients on the autism spectrum, but therapists cannot fragilize their

clients and must still hold them accountable for their actions. It is crucial that therapists

set extremely clear and concise rules and boundaries since clients with ASD struggle

with what is socially appropriate for a therapist/client relationship, but are good rule

followers. These rules and boundaries may have to be reiterated or even written down


because often clients with ASD struggle with memory, which is linked to differences in

their brains.

The way in which therapists communicate with their ASD clients is somewhat

different than they would with other clients. Communication has to be clear, concise,

direct, and to the point. Therapists are unable to allude, perspective taking, or ask “what

if?” questions because clients with ASD struggle with Theory of Mind and executive

functioning. Since individuals with ASD are analytic thinkers, therapist need to use logic

rather than emotions and empathy in therapy.

Research suggests that the neurologic differences in individuals with autism

cause them to be visual processors and learners. Writing things down is a great way for

therapists to explain information to their clients with ASD. In addition, having paper or a

dry erase board clients can use to write and draw on can help them explain there their

thoughts and process information.

Using visual cues (e.g. stop signs, pictures, objects, etc…) are a useful tool to

teach clients communication skills, social interactions, and how to regulate themselves.

One useful visual tool is the 0-10 scale with zero being the lowest end of the scale and

10 being the highest. Having the scale gives clients with ASD a numerical value to

emotions and behaviors, which they often struggle with understanding and processing.

Finding out what visual aides clients with ASD need will enhance the therapeutic

process.

Since individuals with ASD have sensory issues caused by their brain

abnormalities, as a therapist it is important to be accommodating to their sensory needs.

For instance, some clients may be sensitive to lighting, so it is necessary to meet their


needs by either making it brighter or dimmer in the room. In addition, some clients may

be sensitive to sounds and noises, so having appropriate noise control (e.g. white

noise) is important. Having different sensory objects clients can fidget with (e.g. slinky,

Koosh ball, Play-Doh, etc…) can allow them to focus and process information. Even

having a weighted blanket can help some clients calm themselves and be able to

express their thoughts better. Addressing clients’ sensory needs in another way in

which therapists can optimize therapy sessions.

It is essential for therapists to know the neurological differences in their clients

with ASD. It is also important for therapist to understand the impact these differences

have on their clients. Tailoring the therapeutic approaches, tools, and techniques with

maximize the therapeutic outcome for the clients and will optimize their success.

Application for Adlerian Therapists

Adlerian therapists are known for adhering to specific theoretical approaches and

therapeutic techniques. These approaches and techniques can be used with a variety of

different kinds of clients. Adlerian therapists take a holistic approach, do not focus on

the diagnostic labels, and encourage their clients. When it comes to clients with ASD,

Adlerian therapists have to alter, change, and tailor their techniques and approaches to

the individual client.

Frequently clients with ASD have been pamper and/or fragilized; they is they

have been treated as if they are fragile, incompetent, been catered to, and given few

responsibilities or accountability., Other clients, especially those who have been

diagnosed as adolescents and adults may have had a long history of being held to

expectations that they do not understand and have been unable to meet. Client with


both these experiences are often discouraged, striving for significance, have a

hesitating attitude, feel inferior, and struggle with depression and anxiety. Additionally,

clients with ASD are often perfectionist, analytic, and reason with logic.

There are several Adlerian strategies, tools, and techniques to assist clients with

ASD to work through their issues. Please note the following suggestions cannot be used

on all clients with ASD. Ability to use these techniques depends on clients’ individual

developmental levels, may work best with higher functioning clients, and all techniques

have to be tailored to the individual.

Pampering. As Adlerian therapists, we cannot pamper or fragilize our clients

with ASD. Although their brains function differently and they may have disabilities, they

are to have developmentally appropriate responsibilities, held accountable for their

actions, and unable to use their disorder as a crutch. Providing appropriate rules,

boundaries, and expectations, and maintaining consistency will help to ensure

pampering and Fragilizing do not occur.

Encouragement. Some clients with ASD struggle with low self-esteem, feelings of

rejection, and do not have a place or purpose in the world. They may feel as though

they do not belong and are outsiders. Encouragement is essential to working with these

discouraged clients. In addition, assisting clients in determining and writing down their

strengths, abilities, and successes can be validating and encouraging. Along with

encouraging clients, affirmations, positive attitude, and believing in clients is also

important.

Courage to be imperfect. Another technique to assist clients in the therapeutic

process is to teach them how to have the “courage to be imperfect.” Since clients with


ASD are often perfectionist, and sometimes to an extreme, teaching them ways to be

imperfect may help reduce their anxiety, become more self-accepting, and lower stress

levels.

One way to teach some clients with ASD how to be imperfect is through games.

Creating a simple game with clear rules and having the main object to be imperfect.

This may create an environment in which clients are more open, accepting, and able to

processes the idea of imperfection.

Another way to teach how to be imperfect is through the use of social stories.

Social stories are short and concise stories that are meant teach, prepare, and assist in

processing a variety of behaviors, expectations, and experiences. Creating a social

story can be a useful tool that clients can reuse whenever needed. The social story

could be used to inform clients that imperfection is acceptable, as well as specific

statements to repeat to themselves and behaviors they can do whenever they feel

anxious or upset because something is imperfect.

Assigning homework can also be useful when teaching clients how to be

imperfect. Homework helps clients to apply what they learned in therapy sessions to

their everyday lives. An example of homework might include having the client tally the

number of times they experience imperfection in themselves and others, in everyday

life. At the beginning of the subsequence session review the tallied imperfections,

address accepting these imperfections, and discuss the differences between perfection

and good enough. Encouraging and affirming clients on their continual progress, no

matter how fast or slow, is necessary during this therapeutic process.

Forward movement. Determining what drives and motivates clients (e.g. intrinsic


and extrinsic motivators) with ASD is essential in creating forward movement. Once

these drives and motivations are known and understood, they can be used to facilitate

movement.

Forward movement is often slow with some clients with ASD and is necessary to

be additionally patient. Successful forward movement comes in little victories that need

to be noticed, pointed out to clients, and celebrated. Creating a simple progress chart

that is visual and tangible is one way to track clients’ movement. This could be helpful to

show clients how far they have come since the time they began. Looking back,

acknowledging, and celebrating their success will help facilitate additional forward

movement, motivational for the clients, and encouraging to them.

Black and white thinking. Since individuals with ASD have neurological

differences that contribute to their logical and analytical mindset, it creates an all or

nothing, black and white way of thinking. This way of thinking can cause distress in

some clients because they are unable to see other alternatives to problems or

situations. Difficulty seeing the gray area can be detrimental to clients with ASD in their

relationships with others.

An example of how to teach about the gray areas is through the following activity.

On a dry erase board, or paper, draw three columns titled “Black,” “Gray,” and “White.”

In the “Black” column write down a list of words, which have clear opposites and, write

the opposite words in the “White” column. It is the clients’ job to try and think of what

word goes in the middle “Gray” column (see Figure 1 in the Appendix for an example).

Clients may need help thinking of words for the “Gray” column, but be sure to give them

time to think.


After completing a few row, have the clients decide on words to go in the “Black”

and “White” column, and then fill in the “Gray” words. Before, during, and at the end of

the activity discuss with clients how there are gray areas in life, situations, and problem

solving. Also, address logically why gray areas are important and necessary. This

activity can help clients to visually see other alternatives.

Life Style Analysis. An assessment tool most Adlerian therapist use is the Life

Style Analysis (LSA). This tool is useful in determining and understanding clients, their

core values, mistaken beliefs, and a variety of other things in their lives. Although the

LSA works on most clients, it cannot be administer the same way to clients with ASD. It

has to be tailored to the individual client and some sections of the LSA may be

uncompleted.

Early Recollections. Taking Early Recollections (ERs) from clients with ASD is

different than taking ERs from neurologically typical clients. When asking for an early

memory, the therapist has to be more specific then just asking for any memory because

it can be to obscure, unclear, and overwhelming to come clients with ASD. For instance,

ask, “Tell me a memory of you playing when you were seven years old.” Also, therapists

are unable to transform ERs of clients with ASD. It is also too obscure and requires

different processes of thinking that clients with ASD struggle with and are often unable

to perform. Even though ERs are slightly different in individuals with ASD, they can still

be used to uncover current belief systems, mistaken beliefs, and most all other uses

which ERs are typically used for.

Life Task. The most successful way to assess Life Task in individuals with ASD is


to use scaling (i.e. 1-5 or 1-10). Writing down the numbers or drawing number points on

a line is helpful for clients to see. Giving the different areas of Work, Family/Friends,

Significant Other/Love, Self-Care, and Spirituality a numeric value assist in determining

what areas clients need to work on while being visual, concrete, and easier to process.

“The Question”. “The Question” is a diagnostic tool Adlerians use to determine

what the current issues are in clients’ lives. It can be very useful and informative. The

therapist will ask clients some variation of “You fell asleep and while you were sleeping

a miracle happened. When you woke up what would be different?”

Asking a client with ASD “The Question” unfortunately does not work as well as it

does with neurologically typical clients. Some very high function clients might be able to

answer it, but will need additional help understanding it, processing it, and coming up

with answers. Often time clients with ASD will answer the question with, “I do not know.”

They honestly do not know how to answer the question because to them it has not

happened yet so they do not know what the future holds. They are truly unable to

process or think that abstractly. Since their brains function differently, this type of

technique is too obscure and requires a form of brain processing that is difficult and

challenging for them. Instead, therapist need to focus on using more logical, concrete,

visual, and tangible means of diagnostic tools when working with clients with ASD.

Conclusion

For almost three decades, there has been an increase in the number of

individuals diagnosed with ASD. There has been a need for refined diagnostic tools,

more services and treatment options, as well as more research because of this increase


in ASD diagnosis. Researchers have been trying to gain a better understanding of ASD

etiology,

Although the exact etiology of autism is still not know, researchers have made

strides in understanding the neurologic basis for autism. Because of the past research,

it is now known that there is overgrowth in the brain causing great brain volumes and

head circumferences of individuals with autism, which occurs in the first few years of life

and is followed by a normalizing period of development. Additionally, research has

discovered abnormalities in the neurologic connection, patterns of white and gray

matter, as well as developmental and structural abnormalities in specific brain regions.

There is a need for more research in order to fully understand the complex

developmental and structural abnormalities in autism, the role these abnormalities play,

and to determine the exact etiology of autism.

It is essential for all therapists working with clients on the autism spectrum to

know and understand the current research, how it affects clients, and be able to

implement what they have learned. Therapists are responsible for tailoring their

therapeutic approaches to the individual client. They also have to be creative and

adaptive with their assessment and techniques. Treating clients with ASD respectfully,

giving encouragement, being consistent, and having obtainable expectations will assist

in facilitating change, growth, and forward movement, as well as create a positive

environment for success.


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Appendix

Figure 1. This is an example of how to create the “Black, Gray, and White” activity. This activity can be used in helping to teach clients with Autism Spectrum Disorders other alternatives and gray areas in life.

Black

Gray (Client decides on word)

White

Cold

Happy

Starving

Tall

Hate

Clean

Whisper

Awake

Snicker

Walk

Wet

Silent

Bright

Damage

Stand

Child

Cool/Warm

Content

Full/Satisfied

Average

Like

Messy

Talk

Dozing

Giggling

Jog

Damp

Quiet

Dim

Break

Squat

Teenager

Hot

Sad

Stuffed

Short

Love

Dirty

Yell

Sleeping

Laughing

Run

Dry

Loud

Dark

Destroy

Sit

Adult

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