Enhancing Cognitive Function Using Perceptual-Cognitive Training

To investigate if NeuroTracker training can improve perceptual-cognitive skills related to decision-making skills for law enforcement officers.

40 elite law enforcement officers completed a pre-post test experiment on a video based simulated task environment to establish baseline scores for situational awareness, anticipation and decision-making skills. Participants were randomly assigned to training, control and passive groups. The training group completed NeuroTracker sessions around duty schedules over a period of three-weeks. Pre- and post-testing was scored by five police procedures subject-matter-experts.

The simulated task results showed an average decline in scores, the control participants remained unchanged, while the NeuroTracker group showed moderate increases. Improvements in NeuroTracker scores were observed overall, but varied atypically. Although some far transfer effects to law enforcement decision-making abilities were seen, fatigue and stress-related effects of active duty may have influenced results.

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.

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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.

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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.

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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.

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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To examine if cognitive assessments using NeuroTracker could be predictive of daily trader performance metrics.

29 professional male traders aged between 35 and 65 years old were recruited NeuroStreet Trading Academy over a 9-month period. Using the remote NeuroTrackerX software and anaglyph 3D glasses the traders completed 6-minute assessments each work day, following standardized research protocols. Data from the Ninjatrader Trading Platform was used to record 7 key performance metrics across each day of trading.

NeuroTracker data revealed a high learning response across a total of 624 days of trading. Data analyses showed a strong correlational relationship between daily NeuroTracker baselines and 5 of the trading performance metrics, with Total Net Profit being the most significant. The researchers concluded that a 6-minute NeuroTracker assessment was effective at predicting real-world trading performance on any given day.

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To investigate the feasibility of using a remote therapeutic cognitive intervention for brain injury survivors using an at-home training program.

20 older female and male adults were assessed for cognitive health status using a self-report questionnaire and the Mini-Mental State Examination (MMSE) and deemed cognitively healthy. The at-home participants were provided with NeuroTracker training and completed 20 training sessions over 5 weeks. Participant recruitment, retention, adherence, and experience were used as markers of feasibility. Individual session scores, overall improvement, and learning rates between groups was also assessed.

The remote intervention was found to have strong feasibility overall. This was supported by high recruitment and retention, 90% participant adherence, along with ease of use of the program. Differences in screen size and 3D technology showed no differences on cognitive benefits achieved from training, with significant improvements in task performance across the program, which was also equivalent to lab-based training. The researchers concluded that NeuroTracker provides a promising at-home option for cognitive training for cognitively healthy adults and brain injury survivors.