Citation

Jungnickel E, Gramann K. Front. Hum. Neurosci. 2016; 10: e306.

Affiliation

Department of Psychology and Ergonomics, Biological Psychology and Neuroergonomics, Institute of Psychology and Ergonomics, Berlin Institute of TechnologyBerlin, Germany; Center for Advanced Neurological Engineering, University of CaliforniaSan Diego, CA, USA.

Copyright

(Copyright © 2016, Frontiers Research Foundation)

DOI

10.3389/fnhum.2016.00306

PMID

27445747

Abstract

The non-invasive recording and analysis of human brain activity during active movements in natural working conditions is a central challenge in Neuroergonomics research. Existing brain imaging approaches do not allow for an investigation of brain dynamics during active behavior because their sensors cannot follow the movement of the signal source. However, movements that require the operator to react fast and to adapt to a dynamically changing environment occur frequently in working environments like assembly-line work, construction trade, health care, but also outside the working environment like in team sports. Overcoming the restrictions of existing imaging methods would allow for deeper insights into neurocognitive processes at workplaces that require physical interactions and thus could help to adapt work settings to the user. To investigate the brain dynamics accompanying rapid volatile movements we used a visual oddball paradigm where participants had to react to color changes either with a simple button press or by physically pointing towards a moving target. Using a mobile brain/body imaging approach (MoBI) including independent component analysis (ICA) with subsequent backprojection of cluster activity allowed for systematically describing the contribution of brain and non-brain sources to the sensor signal. The results demonstrate that visual event-related potentials (ERPs) can be analyzed for simple button presses and physical pointing responses and that it is possible to quantify the contribution of brain processes, muscle activity and eye movements to the signal recorded at the sensor level even for fast volatile arm movements with strong jerks. Using MoBI in naturalistic working environments can thus help to analyze brain dynamics in natural working conditions and help improving unhealthy or inefficient work settings.

Language: en