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I've been specializing in the world of biofeedback and Neurofeedback for 15 years now, both on the scientific research side, and in clinical practice. In the early days I was lucky enough to work with the Biofeedback Federation of Europe, an organization with the goal of educating professionals on use of these neurotechnologies across many different types of practices. It was a privilege to access many types of international experts, which helped me learn a lot about all the different applications from medical uses to applied sports performance. Here I’ll cover how this led me to NeuroTracker, and to discovering why it provides an ideal synergy with Neurofeedback.
Working with the Biofeedback Foundation connected with Dr. Len Zaichkowsky, a highly distinguished expert in the cognitive domain of elite sports performance, and also Sports Science Director of the Vancouver Canucks. As a world-leader in his field, he put NeuroTracker to use at its genesis, and so it was working with him and the Canucks where I actually discovered NeuroTracker. Right away it occurred to me this was a really interesting tool because of how effectively it elicits attentional resources, working memory, and information processing.
From my background I know this was exactly what a lot of clinical populations like children with ADHD and learning disabilities needed. So I started a scientific collaboration with Professor Jocelyn Faubert at the Faubert Lab, who is the creator of NeuroTracker and was very active in applying it across different studies to expand the frontiers of psychophysics. One challenge he faced was how to objectively demonstrate positive changes in the brain from this type of task. My go-to tool at that point was Quantitative EEG, essentially a highly detailed functional brain scan, which I believed would be a nice solution.
As part of my master's thesis, we undertook an experimental study with healthy university students. The aim was to investigate what functional changes we saw with training effects in terms of neuropsychological performance. In a nutshell we found evidence of clear gains in multiple types of attention, working memory, visual information processing speed, along with indications of heightened neuroplasticity. We used a combination of pre- and post-standardized neuropsychological assessments, alongside qEEG assessments, which corroborated each other very well.
An interesting aspect is both of these measures showed that the NeuroTracker doesn't necessarily train cognitive abilities in one particular skill, instead it actually improves more of a broad layer of cognitive attributes and cognitive functions. In particular we found gains crossing over modalities, where the benefits from this form of visual attention training transferred to auditory attention (a shared resource pool), and also to frontal lobe areas involved in decision-making performance. This paved the way for a real-world study by the Faubert Lab, which found that 3 hours of distributed NeuroTracker training provided far transfer to competitive soccer play, reducing passing decision-making errors by 42%.
It was clear that combining the two techniques of cognitive training stimulation and measures of functional changes had a lot to offer. Of particular interest was that fact that biofeedback and Neurofeedback can also be used to train physiological, cognitive, emotional, and behavioral resources.
For example, when we apply Neurofeedback interventions for patients with severe dyslexia, we can isolate where specific dysfunctional issues reside in the brain, and effectively recover them by normalizing those functions with training. Although Neurofeedback is a wonderful system to isolate cognitive resources that need to be improved, it doesn't necessarily tax them directly. We need to apply training tasks which reliably transfer to the development of those resources.
So, with the already promising evidence of NeuroTracker’s ability to transfer training widely across high-level cognitive systems, it was clearly ideal to pair with both biofeedback and Neurofeedback techniques. I like to think of it as doing the landscaping before building the house, and the beauty is we can apply both of these approaches concurrently.
We can also see the advantage for specialists already using NeuroTracker. It’s particularly relevant for dual-task training methodologies, because Professor Faubert’s research has shown that adding these extra neurophysical loads is sensitive to cognitive consolidation.
If extra neurophysical loads are added before adequate learning adaptations have taken place, then the benefits of the training will be diminished.
This is where biofeedback and neurofeedback fit perfectly, as they can be used not only to measure precisely when to introduce varying difficulties of dual-tasks for optimal learning, but also to reveal the actual neurological effects of training over time.
The evident complementarity of these two approaches evolved into the idea of what I call ‘closing the loop’, that is, using real-time Neurofeedback to iteratively amplify learning responses on a moment-by-moment basis throughout actual NeuroTracker training.
The idea is that if you use feedback to more accurately and rapidly adapt the exercise to a user’s needs, it triggers an altered cognitive state. Then the feedback can be used repeatedly to adjust the training continuously, and with progressively increasing accuracy, to facilitate a proximal zone of development. The key advantage of this concept is the acute nature of how it can adapt temporally, based on a person's responsive performance level, regardless of their variability in cognitive state.
For my PhD. thesis Professor Faubert and I collaborated to test the closed-loop theory in another experimental study with university students, published in Nature Scientific Reports. For this project we used a ProComp Infiniti Encoder, which is ideal for incorporating biofeedback and neurofeedback modalities into the NeuroTracker training context.
Specifically, we found that live changes in certain brainwaves signatures could reliably detect the moment when a person’s attention is either drifting-off during the NeuroTracker task, or when they have effectively lost track of the targets. So we implemented an automatic re-indexing technique where the software would kind of say, ‘Hey, you need to refocus right now - here are your targets’, at any precise moment there was a lapse in attention.
With this integrated training method, we found clear effects that it did indeed boost NeuroTracking performance on-the-fly. And more importantly, that with training across 30 sessions, it produced superior learning rates compared to conventional NeuroTracker training, which was already very effective. We included an active-control group using sham Neurofeedback (random signals), which ruled out placebo effects.
The key takeaway from this study was that active cognitive training, adapted in live fashion via closed-loop Neurofeedback, is an effective means to achieve the zone of proximal development – the ‘sweet spot’ between being over-stimulated or under-stimulated. Naturally this leads to the question, who is this important for?
There are many practitioners and coaches around the world already using NeuroTracker, who maybe aren't quite familiar with biofeedback and neurofeedback. This ranges from specialists working at the high-end of human performance like elite athletes, F1 drivers, eSports athletes, jet pilots and military forces, all the way through to low-functioning populations, such as children with neurodevelopment disorders, or elderlies with cognitive impairments associated with aging.
For all these groups, applying biometric data will certainly help with more effectively adapting the NeuroTracker paradigm to the specific needs of individuals. This will result in more rapid and efficient development of core cognitive functions like attentional processes, information processing speed, executive functions and working memory – known to be critical factors in almost all aspects of human performance.
Then getting more into the nuances of NeuroTracker, this is a task that activates a number of different cognitive systems, which means it is also sensitive to factors such as fatigue, sleep quality, diet, emotional state, breathing techniques, and so on. These are typically things which are difficult to assess or simply be aware of, which biofeedback and Neurofeedback technologies can be excellent for revealing. EEG, heart rate (BVP or EKG), respiration, skin conductance, sEMG, and HEG are key examples of measures that are pair very nicely with this form of training.
Lastly, the great thing here is that the biometric data is also self-validating, because it shows objective changes from a neurobiological perspective. This extra dimension of assessment delivers additional and highly valuable insights to NeuroTracker scores, facilitating a better understanding of how they relate to functional changes, and ultimately to real-world performance.
There are all kinds of specialists also working in the biofeedback paradigm, which similarly spans high-performance domains through to low-functioning populations - children with ADHD being one of the most common. As I mentioned earlier, NeuroTracker fits really well here, principally because it provides a very useful ‘active ingredient’ to the intervention side, or to come back to the analogy – building the house.
However, even when using Neurofeedback and biofeedback purely to assess different populations or patients, NeuroTracker also provides an effective, safe, and practical way to stimulate high-level cognitive systems. This is because it is known to activate attentional resources in what we call a threshold state, with the science showing it can be used to simulate the perceptual-cognitive demands of real-world situations, such as performing on the sports field or driving a car. This was part of Professor Faubert’s original goal in developing this psychophysics tool, and a key reason why it was designed to elicit higher-order binocular stereo 3D visual systems, which we rely on in everyday life.
For these specialists the tool provides a simple and very quick way to trigger cognitive states which can reveal neurobiological effects relevant to real-world demands.
One of the most exciting aspects of this particular field of neuroscience is how fast things are evolving. Research is growing exponentially on both sides, as too is the research into the integration I’ve laid out in this blog. Following Moore’s Law, this is fueled by an exponential growth in neurotechnologies and AI-based machine learning, not just making them more powerful, but also smaller, cheaper, and more practical.
A nice example here is the eVU-TPS, recently developed by Thought Technology. It's a triple physiological sensor which monitors heart rate variability, skin conductance, and skin temperature, through a tiny finger-tip device paired with a smartphone.
This emergent synergy between neuroscience and neurotechnologies will bring these kinds of human optimization solutions into our everyday lives.
Welcome to the Research and Strategy Services at in today's fast-paced.
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