July 2025
in
Acta Psychologica
To synthesize current evidence on the multi-object tracking (MOT) paradigm as both an assessment tool and a cognitive training intervention, with a focus on transfer effects and underlying perceptual-cognitive mechanisms.
The authors reviewed experimental and applied studies using MOT and 3D-MOT (including NeuroTracker) paradigms across cognitive science, sports, aging, and clinical research contexts. The review evaluated task parameters, cognitive mechanisms engaged, and evidence for near and far transfer outcomes following MOT training.
The review found consistent evidence supporting near-transfer effects of MOT training on attentional processes, processing speed, and visuospatial tracking. Evidence for far transfer to broader executive functions, sport performance, and real-world tasks was more variable and dependent on study design and contextual factors. The authors conclude that while MOT paradigms reliably engage core perceptual-cognitive systems, further research is needed to clarify mechanisms and optimize transfer to applied domains.
NeuroTracker meets gold standard criteria as a cognitive enhancement tool, corroborated with positive pre-post changes in qEEG measures.
To examine the practical efficacy of cognitive enhancement interventions through a gold-standard template for assessing use of such tools, and to assess NeuroTracker evidence against the template for enhancing attention, working memory and visual information processing speed.
To assess cognitive tools and NeuroTracker specifically against the following gold-standard criteria and with qEEG findings on changes in neuroelectric brain activity: 1. Robust transfer effects, 2. No Side Effects or Risk of Toxicity, 3. Minimal time and monetary investment, 4) Lasting effects, 5) No ethical issues, 6) Can be used in combination with other interventions, 7) Can be applied to any population.
3-hours of training over 5-weeks with NeuroTracker demonstrated robust effects on attention, working memory, and visual information processing speed as measured by neuropsychological tests. Corresponding changes measured by qEEG were also corroborated these intervention effects. NeuroTracker was concluded to meet the gold standard criteria in points 1, 2, 3, and 5, with some evidence to support the other points, but further research needed.
NeuroTracker peer-reviewed research shows promising relevance for broad cognitive enhancement across different populations.
To assess the usefulness of NeuroTracker (3D-MOT) as a cognitive enhancement tool to overcome the common challenges associated with cognitive training products.
The author conducted a comprehensive review of current literature for cognitive enhancement tools, as well as the specific literature on NeuroTracker to probe its strengths and weaknesses as a research tool. Evidence was also examined for the cognitive domains that NeuroTracker addresses.
NeuroTracker was found to have broad scientific relevant for improving a number of cognitive domains, including information processing, attention, working memory, inhibition, and executive functions. Far transfer effects were found in the following human performance domains: visual information processing in healthy adults, biological motion processing in healthy aging subjects, on-field performance in soccer players, and in attention for populations with neurodevelopmental deficits. The author concluded, that while promising peer-reviewed research exists, more investigations are needed to robustly establish the beneficial effects of this method in the context of cognitive enhancement.
NeuroTracker performance is linked fluid reasoning intelligence, particularly so in conditions of high load tracking.
The objective of the study was to examine MOT capability at different levels of cognitive load (tracking 1,2,3, or 4 objects) and its association to higher level processes, particularly fluid reasoning intelligence.
70 adult participants (mean= 23 years of age) completed NeuroTracker and were then assessed on the Weschler Abbreviated Scale of Intelligence 2 test. Participants were asked to track one, two, three and four targets out of a total of 8 spheres for eight seconds.
The results showed that as the number of targets increased, the average speed the participants successfully tracked all the objects decreased. This finding allowed the researchers to confirm that average speed score can be used as a suitable metric for MOT and in turn, attention resource capacity. As a result, the outcomes indicate that visual tracking capability is positively associated with fluid reasoning intelligence. Consequently, this finding demonstrates that there is a link between fluid reasoning intelligence and MOT capability, especially in conditions of high load (tracking 4 out of 8 targets).
Isolated NeuroTracker training with elite professional athletes provides superior baselines and initial learning rates versus dual-task training.
This paper covers foundational concepts of NeuroTracker’s relevance to training of cognitive capacities deemed critical in sports performance, particularly in dynamic team-sports. It also contains a study investigating the effects of attentional loads in learning paradigms, with the aim of understanding optimal load conditions for training perceptual-cognitive ability.
4 elite professional sports teams trained their athletes on NeuroTracker (15-30 sessions) during their competition seasons. An English Premier Team club, a National Hockey League team, and a European Rugby team were all trained in the standard sitting down position to isolate any influence from attentional mechanisms involved in posture control. Another NHL team performed the training in standing position, involving basic balance demands on attention.
Taking the statistical average for learning progression on NeuroTracker, the three professional sports teams training in sitting position showed near identical progression, with rapid early learning slowing down towards longer term but continued learning. The standing sports team showed much lower NeuroTracker scores, but more importantly slower overall learning progression, with a large magnitude of difference to the other teams. The findings clearly demonstrate the link between balance control mechanisms and perceptual-cognitive demands solicited by NeuroTracker training. This demonstrates that cognitive training loads need to be sensitively optimized to attentional thresholds in order to generate effective short and longer term learning adaptations.
AI modelling of NeuroTracker baselines and demographic data effectively predicts learning rate and training intervention outcomes.
To investigate if a NeuroTracker intervention could improve cognitive abilities in older adults with subjective cognitive decline, and determine if AI models could be used to increase training efficacy.
48 participants between 60 and 90 years of age with subjective cognitive complaints, but otherwise healthy, were assigned to NeuroTracker training group (26) or a control group (22). All participants provided detailed socio-demographic information via questionnaires and baseline neuropsychological assessments (California Verbal Learning Test, Digit Span, D-KEFS Trail Making Test, D-KEFS Verbal Fluency Test, and Stroop Test). The NeuroTracker group performed 7 weeks of training, the control group only performed NeuroTracker baseline assessments. Both groups performed follow-up neuropsychological assessments at 8 weeks and 11 weeks. Machine Learning models were used to analyze demographic and assessment data to test if cognitive performance and responsiveness to training could be predicted.
The NeuroTracker group experience a large improvement in scores of around 70%, along with wide and robust performance transfer on the neuropsychological assessments at week 8, with further gains (without training) at week 11. AI models yielded highly accurate predictions of responsiveness to the training intervention. The researchers propose that such models can be used to effectively tailor NeuroTracker programs to the needs of individuals.
NeuroTracker integrated with closed-loop live EEG feedback enhances NeuroTracker learning rates for healthy adults.
To investigate if real-time Neurofeedback can enhance learning rates for NeuroTracker training.
40 healthy adults were assigned to four training groups (ten each), performing either:-
• Standard NeuroTracker training
• No training (control group)
• NeuroTracker with EEG-Neurofeedback
• NeuroTracker with sham Neurofeedback
EEG-Neurofeedback involved closed-loop feedback that automatically detects when a participant has lost track of their targets and immediately reindexes them.
The standard NeuroTracker group, control group and EEG-Neurofeedback groups started a similar level, higher than the sham Neurofeedback group. However the EEG-Neurofeedback showed superior learning rates over all other groups over the course of 10 training sessions. The results show that a closed-loop learning paradigm is highly effective at enhancing learning outcomes on the NeuroTracker task.
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