Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study.

Researchers studied brain scans from over 400 people (some autistic, some not) to understand how brain structure and function differ in autism. They found one key difference related to how a specific brain area (fusiform gyrus) connects with other regions. This area is important for recognizing faces and objects. The study suggests that differences in how brain regions communicate, rather than brain structure itself, may be more important in understanding autism.

This multimodal neuroimaging study integrated structural and functional brain data from 206 autistic and 196 non-autistic participants in the EU-AIMS LEAP project. Using advanced analytical techniques combining grey matter density, white matter connectivity, and functional connectivity patterns, researchers identified one significant brain component that differed between groups. This component was primarily driven by functional connectivity patterns in the right fusiform gyrus, a brain region important for face and object recognition. The findings suggest that functional brain organization, rather than structural differences, may be the primary distinguishing feature in autism brain phenotypes, expanding on previous single-modality neuroimaging studies.

The identification of fusiform gyrus connectivity differences provides potential neurobiological targets for understanding autism. However, the lack of clear brain-behavior relationships limits immediate clinical applications. Further research is needed to determine if these connectivity patterns could inform diagnostic or intervention approaches.

The study found limited brain-behavior correlations after statistical correction. The clinical significance of the identified brain component remains unclear. Longitudinal data was available for only a subset of participants, potentially limiting developmental insights.

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants.

Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour.

We identified one component that differed significantly between groups (coefficient = 0.33, p = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism.

These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.