Brain Development and Autism Spectrum Disorders

This assignment delves into the complex relationship between brain development during adolescence and Autism Spectrum Disorders (ASD). Students will examine research on neuroimaging correlates of working memory deficits in high-functioning adolescents with ASD, comparing findings to typical adolescent development. The discussion will also touch upon the influence of social and nonsocial processes in ASD, drawing upon functional brain activation patterns revealed through meta-analyses.

Psychology

ABSTRACT
At the time of neurodevelopmental and hormonal changes at the time of adolescence
geared to make sure that independent and reproduction mediate by growing process of neural,
increased myelination in prefrontal areas and remodelling of synaptic. There are many research
that has conducted in order to identify the changes that take place among children and adults. In
accordance with the findings, it can be stated that with aging there are cells that get activated and
these need to be develop with the type of situations that are faced by a person. However, with
advancement in technology there are many issues within brain that are identified and
medications are given so that it can be resolved.

Contents
ABSTRACT....................................................................................................................................2
What has neuroimaging research revealed about the adolescent brain?..........................................1
REFERENCES................................................................................................................................7

What has neuroimaging research revealed about the adolescent brain?
The history of neuroimaging developed by the invention of Italian neuroscientist Angelo
Mosso who was able to create ‘human circulation balance. This was helpful enough to measure
redistribution of blood at the time of intellectual and emotional activity (Dosenbach, Nardos and
Barnes, 2010). However, the precise working was not known to anyone else until the recent
discovery of original instrument that was developed with the reports of Mosso’s that was used by
Stefano Sandrone and his colleagues.
It was in the year 1918 when American neurosurgeon Walter Dandy developed method
of ventriculography. This was helpful enough to provide image of ventricular system of from the
brain through X-ray. For this process, they used by injection of filtered air both lateral ventricles
of nervous system (Pfeifer and Allen, 2012). Then in the year 1970, Godgry Newbold
Hounsfield and Allan McLeod Cormack developed CAT scanning (Computerized axial
tomography). This was helpful enough to provide all anatomic pictures of brain that were used
for research and diagnostic determinations. Apart from this, they were able to able to develop
radioligands that allowed SPECT (single photon emission computed tomography) and PET
(positron emission tomography) of the brain.
It was during the early 1980’s by Paul Lauterbur and Peter Mansfield MRI (magnetic
resonance imaging) was established. During the research it was found that with the correct type
of MRI, they can measure changes in blood flow by PET and this way fMRI (Functional
magnetic resonance imaging) was born.
During the 2000s, there were many changes that took place in the field of neuroimaging
and this stage where it reached that lead to limit the functional brain practical application (Bjork
and Pardini, 2015). More specifically, the area in which they focused more was in crude forms of
brain computer interface. With the help of neurological examination, a physician is able to
determine the neurological disorder that a patient may face. Another type of problem related with
neurology is simple syncope. In these type of situations where history of patient is not suggested
by other symptoms of neurology, then it consist of neurological examination and this is done by
routine neurological imaging when it is not specified due to its probability of determining the
main cause because of which central nervous system is low and the individual is not likely to get
benefited with the process (Giedd and Rapoport, 2010).
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There are different types of brain imaging techniques that are invented with time. These
are done so that better understanding can be raised. In this context, below given are few of the
techniques that are commonly used:
 Computer axial tomography (CAT): This is a type of technique that makes use of
sequence of x-rays of skull that are taken from various way. In other words, it helps in
view immediate brain injuries (Hyde, Samson and Mottron, 2010). More specifically,
scanner is used to perform numerical calculations based on the x-ray sequence. This is
done to know the way x-ray beam is taken by the brain.
 Event related optical signal: This can be determined to be a technique that make use of
infrared light with the help of optical fibres with an aim to measure variations in the
optical properties and all the areas that are active of cerebral cortex. Further, it also
includes other techniques like NIRS (near infrared spectroscopy) and DOT (diffuse
optical imaging) which enables to measure preoccupation of haemoglobin. Further, these
are situated on flow of blood.
 Magnetoencephalography (MEG): it is known as the imaging methods that enables to
evaluate magnetic fields that are developed in the brain by electricals activity (Barendse,
Hendriks and Aldenkamp, 2013). This is done by making use of devices like SQUIDs
(superconducting quantum interference devices). Further, it provides direct measurement
of activities related to neural electrical with low spatial resolution and high temporal
resolution. The magnetic fields that are produced enables to provide appropriate
information to professionals regarding the variations that take place in brain at the type of
emotional that go through.
 Functional magnetic resonance imaging (fMRI: This depend upon properties of
paramagnetic of deoxygenated and oxygenated haemoglobin that help to provide visuals
of changes in flow of blood in brain and this is dependent on the neural activities.
Further, it also enables to provide brain structures that are activated at the time when
different type of tasks are performed (Bava and Tapert, 2010). Advancement in
technology allows these FMARI scanning to present different visual sounds, touch
stimuli and images. Further, it helps to reveal structure of brain and other related
processes that are related with actions and thoughts.
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Since past centuries, there are many changes that have taken place in respect that growth
and development of brain and now it has become feasible with advent of with the help of
functional neuroimaging tools (Crone and Ridderinkhof, 2011). In the past years, there are
developments that were made to understand the structure and functioning of mostly adult’s brain.
This has bought experimental and expertise standards in interpretation of findings and
methodology. All the mentioned techniques are highly beneficial but they have their own set of
limitations as well. Among all the techniques most of the developmental works are founded with
the help of fMRI research. For analysing the different possess that are made by children is a
challenge when compared with adults. One of the main issue that is face to examine is that
children are more anxious in medical environment are they are unfamiliar. Further, they face
difficulty to remain in scanner for long time (Di Martino, Ross and Milham, 2009). However,
both these type of problem can be reduced with training in simulated scanner. This is an effective
way through which they get to make children familiar. Further, the data that are may be
identified will not be fixed or it frequently changes due to changes in size of brain and changes in
structure size of individual.
The transition period that enables to characterized journey from infant to maturity is
adolescence. This is the period in which a person gets to develop their skills that help to change
far from family cells (Zelazo and Carlson, 2012). This way, they are able to start up and free and
active life sexually. There are multiple levels in which these changes take place and these are
within social, emotional and cognitive spheres. Further, one of the significant changes that take
place as an adolescence is puberty. This is determined to be the sexual maturation that affects
secondary and primary characteristics. Further, this also results from hormonal and gonadic
hormonal changes. In accordance with the early studies, it is identified that changes in hormones
does not have significant affect in cognitive development because of their involvement in
emotional development. Moreover, it is identified that from infancy into childhood, cognitive
function gets improved quantitatively, qualitatively and dramatically. Further, there are
improvements in cognitive inhibition, working memory and control over each body function gets
stronger (Hyde, Samson and Mottron, 2010). In addition to this, observations suggest that
increase in emotional and mood lability in adolescence is high. Further, the process to
responding to any type of situation and efficiency in decision making, etc. gets better with time.
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With the help of neuroimaging have enabled to deliver fundamental data in relation with
maturations in brain. In case of adolescence, these changes differ from regions. In this context, it
includes changes that take place in ratio of white and gray matter. More specifically, the matter
of gray decreases which are unmyelinated fiber density and an index of cellular, while the white
matter increases that are index of myelination. However, these changes in matter in the present
period are not known. With the help of myelination, it enables to have faster communication
among regions. Changes in brain take place at frequent basis and this is dependent upon the type
of changes that take place in relation with the situations that are faced. This way, the brain grows
and there are simultaneous changes that take place (Zelazo and Carlson, 2012). There are
changes that are identified in behaviour of adolescent due to the implications that take place for
regional heterogeneity of maturation rates. The hypothesis that is attractive is of imbalance
between emotional and cognitive processing networks. This is mediated by developmental shift
within the balance of mesocortical and mesolimbic dopamine system during adolescence. There
is a typical pattern for adolescent of equilibrium in which 3 systems are included which are
supervisory, approach and avoidance system. The behaviour of adolescent need to have selection
of limbic structure that are associated with coding of emotions and do not need to have selection
of cognitive inhibitory structure. Ventral striatum which is a type of approach related structure
that enables to translate sensory inputs into appetitive stimuli (Di Martino, Ross and Milham,
2009). This can be get more engaged when compared structure like amygdala. As per both of
these scenarios, these enable to contribute towards intense emotions, risk taking, control over
emotions and novelty seeking.
In accordance with neurodevelopmental research, functional neuroimaging has been used
to make study over comparison of different age groups. For the use of fMRI, it relies on the rule
of subtraction. There are different types of elemental processes related with cognitive. Further,
every one of them relies on exact neural circuits. This way, the decision making activation map
enables to get associated with monetary rewards (Crone and Ridderinkhof, 2011). This can be
determined as effective ways through number of studies are carried out. More specifically, it
includes reward related performance, inhibition and working memory. All these type studies are
still in infancy and it do not even need to be examined at different perspectives so that better
understanding of functions.
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In respect with working memory, there are only few studies that are carried out which has
focused on determining attention by making using of functional neuroimaging from the age of 8
to 12 years (Bava and Tapert, 2010). Further, there are significant reduced activities in brain
areas that are associated with attention like temporo parietal areas when compared with controls
on older people. Further, it is identified that there are many areas that are activated among
children. These suggest that networks related with neural are favourable enough to support the
one who are underdeveloped. Most of the studies are focused on visual perception data
somewhat than spoken or object incentives. As per most of the studies, it is initiate that improved
beginning in the age of 8 or 9. Further, the sex difference that is working in memory
performance is high among adolescence (Barendse, Hendriks and Aldenkamp, 2013). When
making comparison with genders, it is identified that male show greater activity in frontopolar
cortex that the time when task for working memory was done. On the other hand, females have
low anterior cingulate.
In the study of response inhibition, there are both combined decreased and increased
regional activations. In this context, there number of paradigms that are used, this includes stop
signal, stroop tasks, no-go and antisaccade. During the performance of antisaccade task, that was
conducted among children (7 to 12) and adolescents (13 to 17). It was found that there are low
rate of activation in superior middle gyrus. On the other hand, there was an increase in activation
of cerebellum, frontal eye field, intra parietal sulcus and striatum. With the help of no-go task,
focused on increase in activation for aging that was found in left inferior frontal gyrus (Hyde,
Samson and Mottron, 2010). Further, there was decrease in activation of middle and superior
frontal gyri (8 to 20). Moreover, it was found that adolescents suggested strengthening of
substrates of mature inhibition but they relied less on immature neural correlates. Further, there
was similar activation that was identified in anterior cingulate and inferior frontal areas, these
were found in other developmental samples (8-20).
With the help of stroop task, it was found that there is increased activation of parietal
cortex among children (7 to 11). In addition to this, there is enhanced beginning in middle frontal
gyrus among young and adolescents (18 to 22). This way, it can be stated that there are variation
in neural maturation qualitatively among adolescents and children (Giedd and Rapoport, 2010).
Apart from this, when comparing the research that was done with 20 children (Age 13.5) and 50
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adults (Age 31.9), it was found that there are greater activation in brain areas among adults and
this way known to be self-regulatory function.
From overall analysis, it can be stated that adults have recruit specific circuit that support
response inhibition (Bjork and Pardini, 2015). There are different parts in the areas of brain that
are developed with time and the type of situation that are faced by individuals. When each of the
condition, the brain gets developed and enhances. Further, from the study that was conducted by
STI, it was found that among adolescents, adults and children show that the rate of radial
diffusivity. This is because, it gets diminishes as fiber bundles mature. Further, this is a way
through which they are able to gather brain stem nuclei and cortex in adolescents. Moreover, this
indicates a raise in integrity of myelin maturation and axon bundles (Pfeifer and Allen, 2012).
When discussed about other pathway, there are supporting interhemispheric and prefrontal
striatal do not get developed until a person becomes adult. Further, there are many studies that
are developed which are focused on raising white matter is dependent on changes in hormones.
In addition to this, the hormonal changes among male and females can also underpin distinct
microstructural development of white matter. Further, there are changes that can be identified in
brain when a person gets depressed or face any other type of emotion. The presentations that are
made to professionals are in such a way that they are able to identify the difference among
disorders (Dosenbach, Nardos and Barnes, 2010). There are variations that are identified among
a person who is normal and the one who is facing injuries. This way, it can be stated that all the
changes are conducted or occur fully when a person grows.
At the time of adolescence, there many dramatic change those take place in relation with
bodily growth, emotional control and behaviour. Further, among some of the people there are
maturational transitions that are firstly manifestation of major disorders related to psychiatric or
this happens at the time of adolescent. Moreover, there are different type of processes of neural
growth and remodelling that take place at different locations at connecting subcortical and
frontal cortex structure.
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REFERENCES
Barendse, E. M., Hendriks, M. P., & Aldenkamp, A. P. (2013). Working memory deficits in
high-functioning adolescents with autism spectrum disorders: neuropsychological and
neuroimaging correlates. Journal of neurodevelopmental disorders, 5(1), 14.
Bava, S., & Tapert, S. F. (2010). Adolescent brain development and the risk for alcohol and
other drug problems. Neuropsychology review, 20(4), 398-413.
Bjork, J. M., & Pardini, D. A. (2015). Who are those “risk-taking adolescents”? Individual
differences in developmental neuroimaging research. Developmental cognitive
neuroscience, 11, 56-64.
Blakemore, S. J. (2012). Imaging brain development: the adolescent brain. Neuroimage, 61(2),
397-406.
Crone, E. A., & Ridderinkhof, K. R. (2011). The developing brain: from theory to neuroimaging
and back. Developmental Cognitive Neuroscience, 1(2), 101-109.
Di Martino, A., Ross, K., & Milham, M. P. (2009). Functional brain correlates of social and
nonsocial processes in autism spectrum disorders: an activation likelihood estimation
meta-analysis. Biological psychiatry, 65(1), 63-74.
Dosenbach, N. U., Nardos, B., & Barnes, K. A. (2010). Prediction of individual brain maturity
using fMRI. Science, 329(5997), 1358-1361.
Giedd, J. N., & Rapoport, J. L. (2010). Structural MRI of pediatric brain development: what have
we learned and where are we going?. Neuron, 67(5), 728-734.
Hyde, K. L., Samson, F., & Mottron, L. (2010). Neuroanatomical differences in brain areas
implicated in perceptual and other core features of autism revealed by cortical thickness
analysis and voxel‐based morphometry. Human brain mapping, 31(4), 556-566.
Pfeifer, J. H., & Allen, N. B. (2012). Arrested development? Reconsidering dual-systems models
of brain function in adolescence and disorders. Trends in cognitive sciences, 16(6), 322-
329.
Zelazo, P. D., & Carlson, S. M. (2012). Hot and cool executive function in childhood and
adolescence: Development and plasticity. Child Development Perspectives, 6(4), 354-
360.
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