What is NeuroTracker?
NeuroTracker is a 3D visual exercise that trains the brain using a multiple-object tracking test. Weekly virtual training sessions aim to build fundamental cognitive abilities, including attention, executive function, working memory, and processing speed. Students with and without learning abilities — as well as professional athletes — use multiple-object tracking to heighten academic or physical performance.
How Does NeuroTracker Work?
Participants wear anaglyph glasses to visually track a set of targets moving dynamically in a 3D space, and attempt to avoid being distracted by a separate set of virtual objects moving within that space. Selecting the correct targets after tracking increases the speed at which the targets move, thereby increasing the difficulty. 18 minutes of training per week is suggested to optimally boost fundamental cognitive abilities. It takes about 3 months to complete the core training program, which comprises 30 sessions.
Who Can Use NeuroTracker?
NeuroTracker was designed to improve the attention and processing speed of athletes who have to remain aware of the quick and spontaneous movements of both opponents and teammates. It is also used by students seeking to improve executive functions, working memory, and processing speed
Can I try NeuroTracker?
NeuroTracker offers varying subscriptions, including personal, remote, and professional; prices vary. Click here to try the NeuroTracker demo.
View Article Sources
Neurotracker (2020). https://neurotracker.net/
Corbin-Berrigan, Laurie-Ann. Three-dimensional multiple object tracking in the pediatric population. NeuroReport (2018). https://pubmed.ncbi.nlm.nih.gov/29481522/
Corbin-Berrigan, Laurie-Ann. Could Neurotracker be used as a clinical marker of recovery following pediatric mild traumatic brain injury? An exploratory study. Brain Injury Journal (2020) https://pubmed.ncbi.nlm.nih.gov/32013583/
Tullo, Domenico. The cognitive benefits of NeuroTracker training across neurodevelopmental disorders: Who benefits from training attention with multiple object-tracking? (2017) https://jov.arvojournals.org/article.aspx?articleid=2652173
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