A research group from University of Houston presented a novel methodology for the neural decoding of intent from freely-behaving infants during unscripted social interaction with an actor. Neural activity was acquired using actiCAP EEG electrodes. Kinematic data was collected with inertial measurement units and supplemented with synchronized video recording.
G. Cruz-Garza, Z. R. Hernandez, T. Tse, E. Caducoy, B. Abibullaev and Contreras-Vidal, J. L. recently presented a novel methodology for the neural decoding of intent from freely-behaving infants during unscripted social interaction with an actor in the Journal of Visualized Experiments.
Published in early October 2015, the article and video protocol introduce a new approach to study infants and young children as they organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment.
The EEG based mobile brain imaging (MoBI) approach that was used to record brain activity and movement, included BrainAmp amplifiers as well as our active electrode system, actiCAP, for the EEG recordings. Additionally, the Brain Products CapTrak was used in the source estimation process to precisely localize the electrode positions and hence the generators of the electric potentials during the behavioral tasks.
The proposed methodology integrates synchronized active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. The described setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.
Therefore the authors e.g. conclude that “the proposed experimental protocol and methods could be deployed in the study of those with developmental disabilities such as infants with probable autism spectrum disorder (ASD).”
For the full publication, please visit the website of the Journal of Visualized Experiments.