When dealing with demanding tasks, the best results come when we’re neither too stressed nor too relaxed. New research from Columbia Engineering (CE) shows, for the first time, how biofeedback loops can be used to keep a participant in that sweet-spot of arousal.
Feelings of fear, agitation, or calm can have a profound effect on our ability to make decisions and perform tasks in real-world conditions. You’d have a much easier time walking across a beam that’s a few centimeters or inches off the ground than one tens of feet or meters up in the air. That state of calm would help you traverse the beam faster and with a lower chance of falling off.
This example illustrates how too much arousal can be bad for business. However, too little arousal also impairs our ability to perform tasks, as we’re simply not engaged enough to perform. New research is looking into ways to keep arousal at moderate levels in order to improve performance in difficult sensory-motor tasks, such as flying a plane or driving a car in rough conditions.
The sweet spot
“The whole question of how you can get into the zone, whether you’re a baseball hitter or a stock trader or a fighter pilot, has always been an intriguing one,” says Paul Sajda, professor of biomedical engineering (BME) and a study co-author.
“Our work shows that we can use feedback generated from our own brain activity to shift our arousal state in ways that significantly improve our performance in difficult tasks — so we can hit that home run or land on a carrier deck without crashing.”
The team used a brain computer interface (BCI) to monitor the arousal state of participants in real time via electroencephalography (EEG). The 20 participants were students at CE who were pitted against a virtual-reality aerial navigation task (i.e. a video game where you have to fly planes). As part of the task, participants had to fly the simulated airplane through rectangular boundaries. To further ‘cultivate’ their feelings of stress and arousal, the scenario made the boxes narrower every 30 seconds; this, needless to say, made the students fail the task pretty quickly.
However, the system also generated a neurofeedback signal based on each participant’s state. One of three feedback scenarios (BCI, sham, and silence / no feedback) was randomly assigned to each participant for every new flight attempt. In the BCI conditions, participants heard the sound of a low-rate, synthetic heartbeat. This was actively modulated in loudness, based on the participant’s arousal as measured by the EEG: the higher the arousal levels, the louder the heartbeats became. The sham feedback didn’t take arousal levels into account, while the silence scenario simply offered no feedback at all to the participants.
All in all, the results are encouraging, the team writes. Participants’ task performance in the BCI condition, measured as time and distance over which the subject can navigate before crashing into one of the boundaries, was increased by around 20% compared to the baseline.
“Simultaneous measurements of pupil dilation and heart rate variability showed that the neurofeedback indeed reduced arousal, causing the subjects to remain calm and fly beyond the point at which they would normally fail,” says Josef Faller, the study’s lead author and a postdoctoral research scientist in BME.
“Our work is the first demonstration of a BCI system that uses online neurofeedback to shift arousal state and improve task performance in accordance with the Yerkes-Dodson law.”
The Yerkes-Dodson law describes the relationship between arousal and performance. Boiled down, it says that performance will increase with arousal up to a point, after which it will quickly start to drop — in other words, there is an ‘optimal’ level of arousal that causes peak performance in any given task. The authors of this present study used their neurofeedback loop to effectively make participants more productive than what their arousal state would predict as based on the Yerkes-Dodson curve.
“What’s exciting about our new approach is that it is applicable to different task domains,” Sajda adds. “This includes clinical applications that use self-regulation as a targeted treatment, such as mental illness.”
The team is also interested in studying whether and how their feedback loop can be used to regulate arousal and emotions for patients with clinical conditions such as PTSD. Another exciting avenue of research that the team is considering is using online arousal and cognitive monitoring in human-robot interactions. In high-stress situations, such as search and rescue operations, supplying the robot information on a human’s arousal state could help it choose its tasks in a way that reduces it’s teammate’s arousal.
“Good human-agent teams, like the Navy SEALS, do this already, but that is because the human-agents can read facial expressions, voice patterns, etc., of their teammates to infer arousal and stress levels,” Sajda says. “We envision our system being a better way to communicate not just this type of information, but much more to a robot-agent.”
The paper “Regulation of arousal via online neurofeedback improves human performance in a demanding sensory-motor task” has been published in the journal Proceedings of the National Academy of Sciences.