If you have heard of NeuroTracker, but don’t know much about it other than balls bouncing around a screen, then this blog is a chance to get a grasp of the fundamentals of this unique cognitive training method.
The NeuroTracker methodology evolved out of many years of neuroscience research at the Faubert Lab (University of Montreal). There were two principle aims for its development.
The first was to devise a way to simulate the mental demands of ‘dynamic scenes’ – such as those found when playing sports, driving a car, or even walking through a busy shopping mall. These scenes involve complex, fast-moving, and sometimes chaotic visual stimulation that draw significant cognitive resources.
The second was to simulate these demands in a way that isolated only the fundamental properties of dynamic scenes. In order to measure performance, this is essential. It is also necessary to be able to modify cognitive loads in precise ways.
Solving these two aims involved synthesizing the following characteristics into a single task.
- Multiple object tracking
- Why? To engage multiple streams of attention at the same time and to generate scene complexity.
- Stereoscopic 3D
- Why? To realistically engage higher-order visual functions in the brain, allowing stimulation at higher levels than achievable with non-stereo 2D.
- Wide field of view
- Why? To place demands on peripheral vision systems, stimulating larger visual networks in the brain.
- Speed thresholds
- Why? To optimize difficulty closely to each individual’s level, and to measure task performance with scientific precision.
One other thing is that NeuroTracker also uses a sports science technique known as a ‘visual pivot’. It’s essentially a dot in the middle of the screen – a point of reference as a visual anchor for the eyes. This helps with tracking targets simultaneously so that attention can be spread widely to make use of peripheral vision (something that is not so intuitive).
Overall, this combination of characteristics delivers a powerful tool for the training of high-level cognitive abilities using a neutral and abstract task. These abilities are enhanced in a top-down fashion, positively influencing broad skills such as concentration and decision-making.
Each NeuroTracker session contains 20 ‘trials’ – these are essentially a sequence of mini-tests. Every time you achieve a correct or incorrect trial, the software adjust tracking speed to your ability. This is an adaptive staircase algorithm, that makes each session uniquely difficult for each person.
What does this mean? When a user correctly identifies all the targets on a trial, the speed of the balls in the subsequent trial will increase, when a user does not correctly identify all the targets, the speed of the balls will decrease in the subsequent trial. NeuroTracker continuously identifies the ideal speed at which the user can track the targets at. It quickly narrows in on each user’s optimal zone, so the fluctuations of speed between the trials become smaller as the session goes on. In effect, it is never too easy and never too hard – a recipe for improvement.
If you’d like to try a demo in 2D, you can try NeuroTracker for free here. Don’t worry, it will go easy on you!
Or you can watch this short video where Professor Faubert introduces the basics concepts of NeuroTracker.
The score given at the end of each session is the speed at which a user is able to track all targets correctly around 50% of the time (their ‘speed threshold’). This is a unique NeuroTracker metric that can be used to assess a person’s cognitive capacity on day one, and across improvements through training over time.
This scientific measure represents an individual’s high-level cognitive capacities, and has been used in lots of research to assess the cognitive state of different populations, or the influences of certain activities. For example, one study tested jet pilots on NeuroTracker while in live flight so they could measure the mental demands of complex flight maneuvers.
Every individual is different, and with NeuroTracker every individual has their own expertise level and learning curve. Therefore, each person’s NeuroTracker scores may differ from others.
For example, a study published in Nature Scientific Reports by Professor Faubert (the inventor of NeuroTracker), showed that professional athletes, varsity athletes, and non-athletes university students perform and improve at NeuroTracker at different levels. In particular, the study demonstrated that elite athletes have superior learning capacities for this type of cognitive task. However, pretty much everybody who trains sees major improvements with training over time, so experience with NeuroTracker is a key factor measuring where an individual is at cognitively. Another study by Professor Faubert showed that even though healthy older people initially tend to have much lower speed thresholds than a young person, but with just a few hours distributed NeuroTracker they can match them.
A number of NeuroTracker studies with athletes and other populations show that people training on NeuroTracker typically improve their speed thresholds by 50% or more within 3 hours of distributed. Taking into account that the task involves negligible technique or practice related effects, these gains represent large improvements in actual brain functions.
Therefore, the key thing for anyone is not how they start off, but how much they improve, especially as there are studies which show that NeuroTracker training transfers to gain in real world performance.
Core training is just the beginning. When it comes to evolving both assessment and performance, there are lots of ways to transform NeuroTracker training.
Once users show continuous improvement, similar to the curve we reviewed earlier, you can advance the training depending on your training objectives.
We recommend that NeuroTracker training advances after 15 to 30 sessions, after what we call the ‘consolidation phase’ – in Professor Faubert’s words ‘this prepares the brain for learning’. Once this is completed, activities such as performing dual-tasks while NeuroTracking, such as practicing balance skills or dribbling a basketball can be efficiently learned. However, the difficulty of these tasks needs to be progressed from simple to complex over time.
If you’d like to get an overview of where advanced training can go, you can read this earlier blog.
Share this Post