Cerebellar anatomical alterations and attention to eyes in autism

Abstract

The cerebellum is implicated in social cognition and is likely to be involved in the pathophysiology of autism spectrum disorder (ASD). The goal of our study was to explore cerebellar morphology in adults with ASD and its relationship to eye contact, as measured by fixation time allocated on the eye region using an eye-tracking device. Two-hundred ninety-four subjects with ASD and controls were included in our study and underwent a structural magnetic resonance imaging scan. Global segmentation and cortical parcellation of the cerebellum were performed. A sub-sample of 59 subjects underwent an eye tracking protocol in order to measure the fixation time allocated to the eye region. We did not observe any difference in global cerebellar volumes between ASD patients and controls; however, regional analyses found a decrease of the volume of the right anterior cerebellum in subjects with ASD compared to controls. There were significant correlations between fixation time on eyes and the volumes of the vermis and Crus I. Our results suggest that cerebellar morphology may be related to eye avoidance and reduced social attention. Eye tracking may be a promising neuro-anatomically based stratifying biomarker of ASD.

A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective

“…This suggests that a heterogeneous range of ASD symptoms could be estimated with regression models from each patients’ earliest MRI scan, allowing treatment strategies to be tailored based on estimated impairments. Interestingly, many of the studies reporting stronger correlations found that increases in volume (Eisenberg et al, 2015; Fredo et al, 2014; Joseph et al, 2014; Laidi et al, 2017) or cortical thickness (Gebauer et al, 2015) were associated with poorer outcomes, which is consistent with the overgrowth hypothesis of ASD…”

“…This suggests that a heterogeneous range of ASD symptoms could be estimated with regression models from each patients' earliest MRI scan, allowing treatment strategies to be tailored based on estimated impairments. Interestingly, many of the studies reporting stronger correlations found that increases in volume (Eisenberg et al, 2015;Fredo et al, 2014;Joseph et al, 2014;Laidi et al, 2017) or cortical thickness (Gebauer et al, 2015) were associated with poorer outcomes, which is consistent with the overgrowth hypothesis of ASD One common limitation of the reviewed studies is the aggregation of a large number of features on an underpowered sample size, leading to models overfitting to the small dataset and generalising poorly when applied to new MR data. Although aggregating large-scale datasets would help to minimise issues around limited statistical power and lead to improved model performance, future studies should also look towards enforcing model sparsity to minimise model overfitting, such as the Akaike information criterion (Sugiura, 2007), recursive feature elimination (RFE) in SVMs (De Martino et al, 2008), LASSO (Tibshirani, 1996), or minimum Redundancy Maximum Relevance (mRMR) which has been applied to the ABIDE dataset (Demirhan, 2018;Ghiassian et al, 2016).…”

Cerebellar atrophy and its contribution to cognition in frontotemporal dementias

“…Structural and functional abnormalities of the cerebellum are present in numerous developmental and acquired neurological conditions, such as developmental dyslexia, autism spectrum disorders, alcohol‐related brain damage, movement disorders (eg, Friedreich ataxia, Parkinson disease, Huntington disease), dementia (eg, Alzheimer disease [AD], dementia with Lewy bodies, frontotemporal dementia), and psychiatric disorders . The contribution of the cerebellum to motor coordination and motor planning is well known, but many studies have downplayed its involvement in other domains despite the mounting evidence over the past 30 years (eg, language, social cognition, interoception).…”

Adults with High-functioning Autism Process Web Pages With Similar Accuracy but Higher Cognitive Effort Compared to Controls

“…People with autism often exhibit idiosyncratic visual attention patterns. This is evidenced by eye tracking studies, where they are reported to focus on smaller bits of infor-mation to the exclusion of the bigger picture [10]. Such differences in attention shifting, when present, are found throughout the entire spectrum.…”