Promoting Simple and Engaging Brain-Computer Interface Designs for Children by Evaluating Contrasting Motion Techniques.

Purpose: There is an increasing focus on using motion in augmentative and alternative communication (AAC) systems. In considering brain-computer interface access to AAC (BCI-AAC), motion may provide a simpler or more intuitive avenue for BCI-AAC control. Different motion techniques may be utilized in supporting competency with AAC devices including simple (e.

Convolutional neural networks can decode eye movement data: A black box approach to predicting task from eye movements.

Previous attempts to classify task from eye movement data have relied on model architectures designed to emulate theoretically defined cognitive processes and/or data that have been processed into aggregate (e.g., fixations, saccades) or statistical (e.

Variability in the analysis of a single neuroimaging dataset by many teams.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data.