Most of us probably know the situation that we tried to navigate through a crowded space, let’s say a shopping street on a Saturday afternoon, and ended up forgetting some of our shopping list items, because we had to evade several obstacles in our way. This phenomenon is called cognitive-motor interference. It is due to the capacity limit of human cognitive resources that can be allocated to all the different processes our brain is calculating at any point in time.
The problem of increasing cognitive-motor interference might become even more evident in the future working life. Workplace technologization enables humans to have a continuous stream of additional visual and/or auditory information using tablets or data glasses while on the go (as it is already established for some logistics warehouse workers). This scenario has the potential to overload processing capacities. The question is how to avoid such situations that can, in the worst case, lead to fatal errors or accidents? The research field of mobile neuroergonomics is dealing with questions like this. For the last three years I was working on a PhD project in this area.
Focus: Electrophysiological measures within real-world settings
I started with a challenging question: How can one gather information about resource capacities without interfering with the individual’s behavior? The problem is that the construct of cognitive load is not continuously quantifiable in real-time with traditional measurement techniques (surveys and reaction times). I found the answer to be more obvious than expected: we can have a look at the head or – more specifically – the scalp surface itself. Over decades electrophysiological measures like the EEG have been used to investigate neural correlates of processing capacities. But these experiments are hardly comparable to real-world environments, as they are conducted only in dimly lit, electrically shielded laboratory settings.
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The PhD project I have been working on for three years has dealt with the validation and applicability of well-known electrophysiological measures within real-world settings.
Mobile EEG for outdoor use
For example, I investigated how walking on an obstacle course on the institute’s outside premises changed the dynamics of cognitive processing in well-known cognitive laboratory paradigms. To do so, we used a mobile EEG setup (you can watch me walking the obstacle course in the video above). We found (read the Scientific Reports paper here) that in real environments cognitive processes were impaired when in natural motion as compared to standing still. This held true for an easy and more challenging cognitive task and has quite profound implications for concurrent cognitive and motor task execution.
Still, to get a more detailed understanding of interference processes, we need to collect more diverse and fine-grained movement and cognition data which will be my major focus in the years to come using the IfADo’s new GRAIL laboratory (see the hyperlink below for more info).