Hyperscanning with CGX Quick Systems

Hyperscanning series part 2: How to do hyperscanning with CGX Quick Systems

by Eduardo Bellomo, Ph.D. Scientific Consultant (Brain Products) In the first article of the hyperscanning1 series, we discussed our gold-standard recommendations for hyperscanning with BrainAmp, our stationary, lab-based, modular system, which may be used with passive or active gel-based electrode technology. This is a great solution, but have you ever thought about bringing this setup…

Hyperscanning with BrainAmps (EEG): This figure demonstrates all the different options for hyperscanning with BrainAmps. Solid images indicate the minimum requirement, whereas transparent images show you optional additions, such as the ControlBox when using active electrodes. Note that PowerPacks can power up to two devices, but cannot be shared between participants. The fiberoptic cables from all the BrainAmps need to be connected to the BUA corresponding to the participant sequence. An optional trigger source is connected to the BUA via the TriggerBox and all triggers and signals are synchronized and saved on one single recording computer in a single file.

Hyperscanning series part 1: How to do hyperscanning with BrainAmps

by Dr. Alex Kreilinger Strategic Product Manager (Brain Products) This first part of the hyperscanning series introduces our current gold standard hardware solution for this application: the BrainAmps. Combining multiple BrainAmps allows using separate ground and reference channels for each participant and provides perfect clock synchronization in a single EEG recording file. Hyperscanning refers to…

User Research Hyperscanning: Figure 2. A: Topographies displaying mean ERD% across pause deciles for Solo (top) and Duet (bottom). Outliers were not removed for this visualization (but were for data submitted to analyses, see 3b-c). B: ERD% data for Observed (dashed) and Predicted (solid) Solo performance results. C: ERD% data for Observed (dashed) and Predicted Duet performance results. D: Relationship predicted from Linear Mixed Model between standardized pause duration and beta ERD%. All predicted data displayed are computed from the full Linear Mixed Effects Model (see Results). Reproduced from Soc Cogn Affect Neurosci, Volume 16, Issue 1-2, January-February 2021, Pages 31–42, https://doi.org/10.1093/scan/nsaa096.

The sound of silence: an EEG study of how musicians time pauses in individual and joint music performance

by Anna Zamm1, Stefan Debener2, Ivana Konvalinka3, Natalie Sebanz1, Günther Knoblich1 1Department of Cognitive Science, Central European University, Vienna, Austria 2Department of Psychology, University of Oldenburg, Oldenburg, Germany 3Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Lyngby, Denmark Abstract In our recent publication in Social Cognitive and Affective Neuroscience (SCAN) we investigated how…