NeuroTrax Science Team and Glen M. Doniger, PhD

Many lifestyle interventions purport to improve brain health, but measuring their true impact requires objective, repeatable assessment. NeuroTrax serves as a digital neuromarker that objectively quantifies cognitive performance over time, enabling clinicians and researchers to evaluate how lifestyle choices and wellness interventions influence brain function. By providing precise longitudinal measurements of cognitive efficiency, NeuroTrax can track changes resulting from exercise, nutrition, cognitive training, and other interventions, helping distinguish meaningful improvements from subjective perceptions (1–3). 

Physical activity is among the most well-established lifestyle factors associated with better cognitive health. Research has shown that higher levels of aerobic fitness are linked with better executive function and global cognition, while objectively measured physical activity is positively associated with faster cognitive processing speed (2,4). Even a single session of aerobic or resistance exercise has been shown to produce measurable improvements in attention and executive functioning on NeuroTrax, demonstrating that the brain can respond to healthy activity almost immediately (3,5). Related studies found that a single 30-minute session of balance and coordination exercises significantly improves attention in older adults, highlighting the exceptional ability of physical exercise to maintain cognitive acuity across the lifespan (6).

Beyond physical exercise, NeuroTrax has been used to evaluate the effectiveness of various cognitive training programs. In individuals with mild cognitive impairment, supervised computerized cognitive training yielded significant improvements in memory and information processing speed (1,2). Immersive virtual reality training has resulted in improved visual spatial ability; virtual reality treadmill training enhanced executive function and dual-task performance in children with ADHD (7,8). These findings demonstrate how objective digital cognitive testing can measure the real-world impact of targeted brain-training interventions.

Nutrition also plays an important role in cognitive efficiency. Long-term adherence to a Mediterranean-style diet has been associated with better trajectories for global cognition and executive function on NeuroTrax (9). Notably, even relatively short periods of calorie restriction can measurably affect brain performance. Research has demonstrated that a complete 12 to 16-hour fast resulted in slower cognitive processing speed (10). Similarly, Vaisman and colleagues found that eating a regular, high-protein breakfast significantly improved cognitive efficiency in individuals with liver cirrhosis experiencing minimal hepatic encephalopathy, suggesting that simple nutritional habits can produce measurable improvements in cognitive function by reducing the impact of metabolic stressors such as ammonia accumulation (11).

NeuroTrax also enables the objective monitoring of advanced wellness interventions. Case reports combining NeuroTrax cognitive testing with biological markers have shown that intensive therapies such as hyperbaric oxygen therapy (HBOT) were associated with improvements in global cognition alongside increases in cerebral perfusion and telomere length (12). These metrics provide empirical evidence that lifestyle and wellness interventions may produce meaningful changes in brain health, helping quantify what has been described as the "difference between zero and one."

As interest in preventative brain health continues to grow, objective measurement is becoming increasingly important. NeuroTrax provides a reliable approach for monitoring cognitive efficiency over time, allowing individuals to move beyond subjective impressions and quantify how exercise, nutrition, cognitive training, and wellness programs influence brain performance. Indeed, NeuroTrax serves as a widely used digital neuromarker, empowering clinicians to make more informed decisions while tracking progress throughout their patient’s cognitive wellness journey.

References

[1] Lampit, A., Hallock, H., Moss, R., Kwok, S., Rosser, M., Lukjanenko, M., Kohn, A., Naismith, S., Brodaty, H., and Valenzuela, M. (2014). The timecourse of global cognitive gains from supervised computer-assisted cognitive training: A randomized, active-controlled trial in elderly with multiple dementia risk factors. Journal of Prevention of Alzheimer’s Disease, 1(1), 33–39. DOI: 10.14283/jpad.2014.18

[2] Marinac, C.R., Godbole, S., Kerr, J., Natarajan, L., Patterson, R.E., and Hartman, S.J. (2015). Objectively measured physical activity and cognitive functioning in breast cancer survivors. Journal of Cancer Survivorship, 9(2), 230–238. DOI: 10.1007/s11764-014-0404-0

[3] Dunsky, A., Abu-Rukun, M., Tsuk, S., Dwolatzky, T., Carasso, R., and Netz, Y. (2017). The effects of a resistance vs. an aerobic single session on attention and executive functioning in adults. PloS One, 12(4):e0176092. DOI: 10.1371/journal.pone.0176092

[4] Netz, Y., Dwolatzky, T., Zinker, Y., Argov, E., and Agmon, R. (2011). Fitness and multidomain function in advanced age. International Psychogeriatrics, 23(1), 114–124. DOI: 10.1017/S1041610210000797

[5] Tsuk S., Netz, Y., Dunsky, A., Zeev, A., Carasso, R., Dwolatzky, T., Salem, R., Behar, S., and Rotstein, A. (2019). The acute effect of exercise on executive function and attention: Resistance versus aerobic exercise. Advances in Cognitive Psychology, 15(3), 208–215. DOI: 10.5709/acp-0269-7

[6] Dunsky, A., Unger, L., Carasso, R., and Fox, O. (2023). The effect of a single session of balance and coordination training on cognitive function in older adults. Applied Sciences, 13(6):3598. DOI: 10.3390/app13063598

[7] Delgado, F., and Greenberg, J. (2024). Cognitive and practice effects of immersive virtual reality use in older adults: Preliminary results. Innovation in Aging, 8(S1), 1231. DOI: 10.1093/geroni/igae098.3939

[8] Shema-Shiratzky, S., Brozgol, M., Cornejo-Thumm, P., Geva-Dayan, K., Rotstein, M., Leitner, Y., Hausdorff, J.M., and Mirelman, A. (2019). Virtual reality training to enhance behavior and cognitive function among children with attention-deficit/hyperactivity disorder: Brief report. Developmental Neurorehabilitation, 22(6), 431–436. DOI: 10.1080/17518423.2018.1476602

[9] Lutski, M., Weinstein, G., Ben-Zvi, S., Goldbourt, U., and Tanne, D. (2022). Adherence to Mediterranean diet and subsequent cognitive decline in men with cardiovascular disease. Nutritional Neuroscience,25(1), 91–99. DOI: 10.1080/1028415X.2020.1715049

[10] Doniger, G.M., Simon, E.S., and Zivotofsky, A. (2006). Cognitive sequelae of a complete 12-16 hour fast. Behavioral Neuroscience, 120(4), 804–816. DOI: 10.1037/0735-7044.120.4.804

[11] Vaisman, N., Katzman, H., Carmiel-Haggai, M., Lusthaus, M., and Niv, E. (2010). Breakfast improves cognitive function in cirrhotic patients with cognitive impairment. American Journal of Clinical Nutrition, 92(1), 137–140. DOI: 10.3945/ajcn.2010.29211

[12] Maroon, J.C. (2022). The effect of hyperbaric oxygen therapy on cognition, performance, proteomics, and telomere length – The difference between zero and one: A case report. Frontiers in Neurology, 13:949536. DOI: 10.3389/fneur.2022.949536

NeuroTrax Science Team and Glen M. Doniger, PhD

The eyes have long been described as a window to the brain, but advances in neurometrics are elucidating the linkage between ocular health and cognitive function. Structural and functional measurements of the visual system can provide valuable insights into brain integrity, particularly when paired with objective cognitive assessment. Research using NeuroTrax digital cognitive assessment demonstrates that combining cognitive performance with ocular biomarkers offers clinicians a more complete understanding of neurological health and factors affecting everyday mental acuity (1,2).

Among the best examples comes from optical coherence tomography (OCT), a non-invasive imaging technique that measures retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness. Because retinal neurons are a direct extension of the central nervous system, changes within these structures often mirror neurodegenerative processes occurring in the brain (1).

Studies have shown significant associations between NeuroTrax global cognitive scores and RNFL thickness in people with multiple sclerosis (PwMS). Thinner RNFL measurements were tied to lower performance in attention and motor skills, and GCIPL thickness was strongly related to executive function, attention, and information processing speed (1). These findings suggest that retinal imaging is an early biomarker of cognitive decline that provides clinicians with objective structural evidence to complement cognitive assessment.

Beyond anatomy, efficiency of neural communication can be evaluated with visual evoked potentials (VEPs), which measure the time required for visual signals to travel from the retina to the visual cortex. Prolonged VEP latency reflects slower neural conduction and has been consistently associated with poorer performance in multiple NeuroTrax cognitive domains, including information processing speed, executive function, attention, and motor skills (3). Notably, VEP latency has been shown to predict cognitive performance better than visual acuity alone, highlighting its value as a key indicator of brain health (3).

Research has also demonstrated a relationship between delayed VEP latency and subjective cognitive fatigue. As neural communication efficiency declines, the brain appears to expend greater resources to maintain cognitive performance, contributing to the mental fatigue commonly experienced by individuals with neurological disease (4).

Clinical value is maximized when structural and functional ocular measures are interpreted alongside objective cognitive metrics. Combining OCT-derived retinal biomarkers with VEP latency and NeuroTrax cognitive indices explains substantially more variance in cognitive functioning than any single measure alone (2). This multimodal approach gives a comprehensive picture of nervous system health by capturing both structural integrity, neural conduction efficiency and cognitive profile.

Longitudinal studies demonstrate the predictive value of these biomarkers. Baseline VEP latency and inter-ocular latency have been shown to predict future changes in information processing speed over a two-year period, offering clinicians an opportunity to identify patients with heightened risk of cognitive decline before significant functional impairment develops (5).

Taken together, these findings reflect the concept of the "Mind's Eye." NeuroTrax objective cognitive assessment opens a window on the brain for OCT and VEP measurements, enabling a paradigm shift as clinicians move beyond isolated biomarkers toward an integrated picture of brain function. By evaluating how structural changes, neural signaling, and cognitive metrics interact, healthcare providers can improve monitoring, identify early neurological changes, and ultimately support more informed clinical decision-making.

References

[1] Dreyer-Alster, S., Gal, A., and Achiron, A. (2022). Optical coherence tomography is associated with cognitive impairment in multiple sclerosis. Journal of Neuro-Ophthalmology, 42(1), e14–e21. DOI: 10.1097/WNO.0000000000001326

[2] Covey, T.J., Golan, D., Sergott, R., Wilken, J., Zarif, M., Bumstead, B., Buhse, M., Kaczmarek, O., Doniger, G.M., Penner, I.K., Hancock, L.M., Bogaardt, H., Barrera, M.A., Morrow, S.A., Galetta, S., and Gudesblatt, M. (2024). Peering further into the mind’s eye: Combining visual evoked potential and optical coherence tomography measures enhances insight into the variance in cognitive functioning in multiple sclerosis. Journal of Neurology, 271(2), 658–673. DOI: 10.1007/s00415-023-12075-5

[3] Covey, T.J., Golan, D., Doniger, G.M., Sergott, R., Zarif, M., Srinivasan, J., Bumstead, B., Wilken, J., Buhse, M., Mebrahtu, S., and Gudesblatt, M. (2021). Visual evoked potential latency predicts cognitive function in people with multiple sclerosis. Journal of Neurology, 268(11), 4311–4320. DOI: 10.1007/s00415-021-10561-2

[4] Covey, T.J., Golan, D., Doniger, G.M., Sergott, R., Zarif, M., Bumstead, B., Buhse, M., Kaczmarek, O., Mebrahtu, S., Bergmann, C., Wilken, J., and Gudesblatt, M. (2022). The relationship between cognitive impairment, cognitive fatigue, and visual evoked potential latency in people with multiple sclerosis. Multiple Sclerosis and Related Disorders, 57:103349. DOI: 10.1016/j.msard.2021.103349

[5] Covey, T.J., Golan, D., Doniger, G.M., Sergott, R., Zarif, M., Bumstead, B., Buhse, M., Kaczmarek, O., Mebrahtu, S., Bergmann, C., Wilken, J., and Gudesblatt, M. (2022). Longitudinal assessment of the relationship between evoked potentials and cognitive performance in multiple sclerosis. Clinical Neurophysiology, 137, 66–74. DOI: 10.1016/j.clinph.2022.02.013