Taking a closer look at how the cerebellum is linked to autism

By Alexander Albury

According to the NHS, autism spectrum disorder is a neurological and developmental disorder that affects how people interact with others, communicate, behave, and learn. The cerebellum, a dense structure of neurons at the back of the brain, is typically associated with behaviors involving movement such as balance, gait, and fine motor movements. But it also plays a role in attention, emotional regulation, and social cognition. Because of this, it’s thought to play a key role in autism, with several studies showing a relationship between autism and the cerebellum, particularly the gray matter volume or thickness of the cerebellum. However, current research findings are inconsistent, with different studies and research groups reporting results of different sizes, highlighting different parts of the cerebellum, or finding no connection between the cerebellum and autism at all.

A group of researchers led by Charles Laidi set out to determine whether parts of the cerebellum are implicated in autism, or if previous findings are simply the byproduct of inconsistent research methods and small sample sizes. In a paper published in Biological Psychiatry, the authors compared the cerebellums of a large sample of people with autism and control subjects not diagnosed with autism.

One of the common issues in neuroscience research, particularly magnetic resonance imaging (MRI), is how to define the boundaries of the brain areas researchers are studying. This process, known as parcellation, segments areas of the brain into smaller sections that are believed to have unique functions or structures. This is particularly important for parts of the brain such as the cerebellum that have very dense bundles of neurons because, for example, two parts of the brain even a millimeter away could have totally different functions.

The problem is, there’s no single, standardized way to perform parcellation. Although there are common practices, it is ultimately up to each individual research team to decide how they segment the brain based on the question they’re asking. Unfortunately, this freedom can make it hard to compare the results from different studies. For example, if two researchers don’t segment the cerebellum in the same way, it’s hard to tell if any differences in their results are genuine differences or are only present because they analyzed the brain in different ways.

Laidi et al. compared two common parcellation techniques of the cerebellum and examined how they influenced the relationship between brain structure and autism. To do this, they compared gray matter volume in the cerebellum to the patient scores on common diagnostic tests for autism.

They found no changes in the structure of the cerebellum in people with autism, even in areas of the cerebellum that have previously been implicated in autism. They also found no relationship between cerebellum structure and results of clinical tests of autism, and the results didn’t change when considering age and sex. Even when using a machine learning model trained on patients’ brain scans, the researchers were unable to accurately distinguish people with autism from control subjects without autism.

This is one of the first large-scale studies to investigate the relationship between cerebellar structure and autism, and it calls into question previous findings linking the cerebellum and autism spectrum disorder. Although autism is frequently studied, many of the research findings related to the disorder can often differ, or at worst, contradict each other. The authors highlight the need for larger sample sizes and more standardized techniques across research labs. Large-scale studies like Laidi et al. allow researchers to be more confident in their findings and make better recommendations about how to further study autism.

Original Research:

Laidi, C., Floris, D. L., Tillmann, J., Elandaloussi, Y., Zabihi, M., Charman, T., Wolfers, T., Durston, S., Moessnang, C., Dell’Acqua, F., Ecker, C., Loth, E., Murphy, D., Baron-Cohen, S., Buitelaar, J. K., Marquand, A. F., Beckmann, C. F., Frouin, V., Leboyer, M., … Simonoff, E. (2022). Cerebellar Atypicalities in Autism? Biological Psychiatry, 92(8), 674–682. https://doi.org/10.1016/j.biopsych.2022.05.020

Charles Laidi is the winner of the 2023 OHBM Replication Award

Previous
Previous

Network Neuroscience: A hands-on guide

Next
Next

Zooming in on Alzheimer’s: Ex vivo mapping of the dentate gyrus using 16.4T MRI