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

Project Information

AutismRigidPercept

Grant agreement ID: 656161

DOI

10.3030/656161

Project closed

EC signature date 21 April 2015

Start date 1 May 2015

End date 31 July 2017

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 195 454,80

EU contribution

€ 195 454,80

Coordinated by

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)

Reporting period: 2015-05-01 to 2017-04-30

Summary of the context and overall objectives of the project

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.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

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.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

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.