Investigation and modification of atypical dynamic brain activity underlying perceptual inflexibility of autism spectrum disorders

Informations projet

AutismRigidPercept

N° de convention de subvention: 656161

DOI

10.3030/656161

Projet clôturé

Date de signature de la CE 21 Avril 2015

Date de début 1 Mai 2015

Date de fin 31 Juillet 2017

Financé au titre de

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coût total

€ 195 454,80

Contribution de l’UE

€ 195 454,80

Coordonné par

UNIVERSITY COLLEGE LONDON
United Kingdom

Periodic Reporting for period 1 - AutismRigidPercept (Investigation and modification of atypical dynamic brain activity underlying perceptual inflexibility of autism spectrum disorders)

Période du rapport: 2015-05-01 au 2017-04-30

Résumé du contexte et des objectifs généraux du projet

What is the problem/issue being addressed?
In this project, we investigated neuroanatomical characteristics and functional mechanisms underlying inflexible behavioural and cognitive tendency of autism spectrum disorder (ASD).

Why is it important for society?
Despite its high prevalence, the biology of such cognitive inflexibility in autism has not been sufficiently investigated, which partly results in the difficulty of autistic individuals in adapting themselves to a rapidly changing modern society. Therefore, it should be highly significant to understand neurobiological mechanisms behind this ASD symptom.

What are the overall objectives?
We aimed at deepening biological understanding of this somewhat overlooked core symptom of autism, and building a foundation for future treatments for it.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

From August in 2015 to July in 2017, we published the following five peer-reviewed papers:

1. Watanabe, T., & Rees, G. (2017). Brain network dynamics in high-functioning individuals with autism. Nature Communications, 8, 16048.
In this work, we identified atypically stable brain dynamics in high-functioning autistic adults, and showed the links between such autistic neural dynamics and various ASD behavioural tendencies including their symptoms and IQ.

2. Ezaki, T., Watanabe, T., Ohzeki, M., & Masuda, N. (2017). Energy landscape analysis of neuroimaging data. Philosophical Transactions. Series a, Mathematical, Physical, and Engineering Sciences, 375(2096), 20160287.
In this work, we explained our novel application of “energy-landscape analysis” to human brain imaging data. In particular, we provided the codes for this analysis freely.

3. Watanabe, T., & Rees, G. (2016). Anatomical imbalance between cortical networks in autism. Scientific Reports, 6(1), 31114.
In this work, we identified the significant associations between neuroanatomical balance and autistic symptoms. In particular, we found that autistic cognitive inflexibility could be linked with over-development in the visual cortex.

4. Watanabe, T., & Rees, G. (2015). Age-associated changes in rich-club organisation in autistic and neurotypical human brains. Scientific Reports, 5, 16152.
In this work, we found that autistic individuals have underdeveloped rich-club network architectures in their brains. Such atypical brain network structures were linked with the severity of autism.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

In this project, we further developed our original energy-landscape analysis, one of the state of the art technique to probe large-scale neural dynamics. This method is now being disseminated by freely providing the analysis codes with our review paper.
Also, we also developed several original indices to quantify autistic neurobiological characteristics. For example, the neuroanatomical balance used in our paper (2016, Sci Reports) can be seen as a new and robust neuroanatomical indicator to detect autism. Moreover, the resting-state inter-network transition frequency (see Watanabe & Rees, 2017, Nature Communications) achieved a high sensitivity and specificity to identify autism from typically developing adults.
Such new indices to quantify the autistic tendency in human brains are expected to contribute far earlier, easier, and more robust diagnosis of the prevalent neurodevelopmental disorder.