Developmental EEG
Recording EEG from infants and children presents its own set of requirements in terms of preparation time and flexibility. Our active electrodes provide the highest signal quality with a low preparation time, while our salt-water based sponge electrodes are even faster, without leaving gel residues behind. Our all-in-one lab amplifier offers the flexibility to switch between active and passive recordings; however, when mobility and portability are required, our wireless amplifier is the perfect choice. Fully synchronized video and EEG recordings are made possible with a network camera, directly integrated into our recording software.
Recommended solutions
Below you will find some of our recommended solutions for this application field. Depending on your research paradigm, other solutions may be more appropriate. For the optimal setup for your research goals, please contact your local distributor.
actiCHamp Plus
LiveAmp
actiCAP slim/snap
R-Net
BrainVision Video Recorder Kit
BrainVision Analyzer
More resources
Reference labs
We enjoy the close contact we have with research groups using Brain Products equipment. In fact, these collaborations often help us improve our solutions, not just for one specific application field, but for all. We greatly appreciate the ongoing collaboration with these labs.
Baby Sleep Laboratory
(Fribourg, Switzerland)
website | Baby Sleep Laboratory
website | Université de Fribourg (Psychology)
BabyBRAIN group
(Nijmegen, Netherlands)
website
Publications
Here are some papers related to this application field (published by the above mentioned reference labs):
- Meyer, M., Lamers, D., Kayhan, E., Hunnius, S., & Oostenveld, R. (2021). Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes. Developmental Cognitive Neuroscience, 52, 101036. https://doi.org/10.1016/j.dcn.2021.101036
- Monroy, C. D., Meyer, M., Schröer, L., Gerson, S. A., & Hunnius, S. (2019). The infant motor system predicts actions based on visual statistical learning. NeuroImage, 185, 947–954. https://doi.org/10.1016/j.neuroimage.2017.12.016