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

Projektinformationen

AutismRigidPercept

ID Finanzhilfevereinbarung: 656161

DOI

10.3030/656161

Projekt abgeschlossen

EK-Unterschriftsdatum 21 April 2015

Startdatum 1 Mai 2015

Enddatum 31 Juli 2017

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 195 454,80

EU-Beitrag

€ 195 454,80

Koordiniert durch

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)

Berichtszeitraum: 2015-05-01 bis 2017-04-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

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.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

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.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

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.