Individuals with autism spectrum disorder show deficits in social interactions, communication and behavior. These deficits are accompanied by widespread differences in brain structures and activation patterns between individuals with autism and healthy individuals. Magnetic resonance imaging (MRIs) of healthy volunteers and individuals with autism show differences in the volumes of multiple brain regions including:
- The frontal cortex, which is involved in social and cognitive (intellectual) functions tends to be thicker.
- The temporal lobe involved in speech processing tends to be thinner in individuals with autism.
- The nucleus accumbens, which is a part of the reward processing pathway, and the amygdala, involved in emotional behaviors, tend to have a smaller volume in individuals with autism.
While MRI scans are used to evaluate differences in the structure of brain regions, a functional MRI, or fMRI shows how different brain regions respond while performing a certain behavior. During an fMRI scan, individuals are asked to perform a task while in a scanner. Changes in brain activity levels while performing the test are measured by evaluating changes in blood flow to different brain regions.
These fMRI scans can thus show how brain regions and pathways respond differently to the same stimulus in individuals with autism versus healthy volunteers. Such scans indicate that areas involved in social behavior, like the amygdala, show lower levels of activation upon exposure to social stimuli.
Other studies have shown that there is a delay in the shift in patterns of activation of brain regions in individuals with autism. This may be responsible for their impaired ability to adapt to changes.
Differences in Brain Structure and Reward Pathways
According to the social motivation model of autism, individuals with autism may lack the motivation to engage in social interactions and may find social interaction less rewarding.
The brain reward pathway also plays an important role in learning in both social and non-social contexts. These motivational deficits may lead to impaired social skills.
Functional magnetic resonance imaging studies show a reduced volume of the nucleus accumbens which is a brain region in the reward pathway. Brain regions consisting of neuronal cell bodies communicate with other neurons by means of axons. The cell bodies of neurons constitute gray matter, whereas white matter is composed of axonal tracts.
A recent neuroimaging study showed that white matter tracts between brain regions within the reward pathway showed abnormalities i.e. the brain regions in the reward pathway showed weaker connectivity in individuals with autism. Furthermore, the study also showed that weaker connectivity was associated with more severe social deficits.
Can MRIs Detect Autism?
There has been an upsurge of studies that have detected differences in brain scans of individuals with autism relative to healthy volunteers in the past decade. These studies suggest that it may be possible to detect autism with the help of MRI scans in the future. However, these studies need to be replicated before their results can be translated for clinical diagnosis.
Besides being replicated, the results from these studies must have a low rate of error to be used for clinical diagnosis and the methodology must be practical. For example, a study in 2017 reportedly used MRI scans to measure the surface area and volume of multiple brain regions in infants with a familial history of autism. The voluminous data obtained from the scans were analyzed using algorithms and the study showed that the computer could distinguish infants who had autism from those who did not. The infants underwent two scans, with one scan at the age of 6 months and the other at 12 months.
However, the infants had to be still while in the MRI scanner for the data from the MRI scan to be meaningful. Such pragmatic considerations may restrict the utility of MRI scans in very young children.
Besides such pragmatic concerns, there are theoretical issues that need to be addressed before MRIs can be used to detect autism. However, brain scans using MRI and other methods do indeed help to recognize targets for the treatment of autism and may even help to diagnose autism in the future.
Ongoing Studies and Research
Brain imaging studies conducted using various methods, including MRIs and fMRIs, will continue to enhance our understanding of the relationship between autism and changes in brain structure, connectivity and function. These brain imaging methods are now being combined with other approaches to further enhance our understanding of autism. With an increase in computing power, it has now become possible to analyze a large amount of data in a very short time.
Individuals with autism often show variable symptoms in terms of severity and intensity. There is an ongoing study that is using a big data approach in combination with MRI scans to investigate the link between the variation in symptoms among individuals with autism and the brain structures underlying these symptoms.
There are also studies that are currently investigating the association between variation in gene expression and differences in structural and functional connectivity in individuals with autism. Autism spectrum disorder can sometimes co-occur with substance use disorders.
Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K. “The implications of brain connectivity in the neuropsychology of autism.” Neuropsychology Review, March 2014. Accessed September 26, 2019.
Van Rooij, Daan; et al. “Cortical and subcortical brain morphometry differences between patients with autism spectrum disorder and healthy individuals across the lifespan: results from the ENIGMA ASD Working Group.” American Journal of Psychiatry, November 2017. Accessed September 26, 2019.
Supekar, Kaustubh; et al. “Deficits in mesolimbic reward pathway underlie social interaction impairments in children with autism.” Brain, September 2018. Accessed September 26, 2019.
Spectrum News. “Autism brains show widespread alterations in structure.” June 2018. Accessed September 26, 2019.