Artificial grammar learning in Williams syndrome and in typical development: the role of rules, familiarity and prosodic cues

Artificial grammar learning (AGL) is an empirical paradigm which investigates basic pattern- and structural processing in different populations. It can inform how higher cognitive functions, such as language use, take place. Our study used AGL to assess how children with Williams syndrome (WS) (n=16) extract patterns in structured sequences of synthetic speech, how they compare to typically developing (TD) children (n=60), and how prosodic cues affect learning. The TD group was divided into: a group whose non-verbal abilities (NVMA) were within the range of the WS group, and a group whose chronological age (CA) was within the range of the WS group. TD children relied mainly on rule-based generalization when making judgements about sequence acceptability, whereas children with WS relied on familiarity with specific stimulus combinations. The TD participants whose NVMA were similar to the WS group, showed less evidence of relying on grammaticality than TD participants whose CA was similar to the WS group. In absence of prosodic cues, the children with WS did not demonstrate evidence of learning. Results suggest that, in WS children, the transition to rule-based processing in language does not keep pace with TD children and may be an indication of differences in neuro-cognitive mechanisms

Proceedings of the OHBM Brainhack 2022

International audienceOHBM Brainhack 2022 took place in June 2022. The first hybrid OHBM hackathon, it had an in-person component taking place in Glasgow and three hubs around the globe to improve inclusivity and fit as many timezones as possible. In the buzzing setting of the Queen Margaret Union and of the virtual platform, 23 projects were presented for development. Following are the reports of 14 of those, as well as a recapitulation of the organisation of the event

Proceedings of the OHBM Brainhack 2021

The global pandemic presented new challenges and op-portunities for organizing conferences, and OHBM 2021was no exception. The OHBM Brainhack is an event thatoccurs just prior to the OHBM meeting, typically in-per-son, where scientists of all levels of expertise and interestgather to work and learn together for a few days in a col-laborative hacking-style environment on projects of com-mon interest (1). Building off the success of the OHBM2020 Hackathon (2), the 2021 Open Science SpecialInterest Group came together online to organize a largecoordinated Brainhack event that would take place overthe course of 4 days. The OHBM 2021 Brainhack eventwas organized along two guiding principles, providinga highly inclusive collaborative environment for inter-action between scientists across disciplines and levelsof expertise to push forward important projects thatneed support, also known as the “Hack-Track” of theBrainhack. The second aim of the OHBM Brainhack is toempower scientists to improve the quality of their sci-entific endeavors by providing high-quality hands-ontraining on best practices in open-science approaches.This is best exemplified by the training events providedby the “Train-Track” at the OHBM 2021 Brainhack. Here,we briefly explain both of these elements of the OHBM2021 Brainhack, before continuing on to the Brainhackproceedings