NeuroTrax Science Team and Glen M. Doniger, PhD
As the global population ages, there is an urgent need to identify individuals at risk for cognitive decline before the emergence of significant symptoms. Traditional cognitive screening provides valuable information, but combining objective cognitive metrics with measures of brain physiology offers a more complete view of brain health. A 2026 study by Zifman and colleagues demonstrates this potential by pairing NeuroTrax digital cognitive neurometrics with combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate the relationship between brain connectivity and cognitive risk in older adults (1).
The study evaluated 454 community-dwelling older adults with a mean age of 61.4 years. Researchers focused on interhemispheric connectivity (IHC) within the dorsolateral prefrontal cortex (DLPFC), a brain region involved in executive control and working memory. Using the non-invasive Delphi-MD TMS-EEG system, researchers magnetically stimulated one side of the prefrontal cortex and recorded the millisecond-level electrical response traveling across the brain’s hemispheres.
Participants also completed a comprehensive cognitive evaluation that included NeuroTrax digital neurometrics. Based on the cognitive scores, researchers applied K-means clustering to classify participants into cognitively normal and cognitively impaired groups and examined brain connectivity in these groups.
The results revealed a strong relationship between DLPFC connectivity and cognitive status. Participants classified as cognitively impaired had significantly lower interhemispheric connectivity than cognitively normal participants. A single-unit decrease in right DLPFC connectivity was associated with 4.35-fold higher odds of cognitive impairment, while a unit decrease in left DLPFC connectivity was associated with 3.03-fold higher odds. These relationships remained significant after adjusting for age and sex.
The link between objective cognitive metrics and underlying brain physiology is supported by prior research with NeuroTrax. Sasson and colleagues used diffusion tensor imaging (DTI) to examine white matter integrity in normal aging, demonstrating associations between specific cognitive domains and the microstructural integrity of corresponding white matter pathways. Executive function, for example, was associated with integrity of the superior longitudinal fasciculus (2). While structural imaging provides data on brain anatomy, longitudinal cognitive assessment tracks how function changes over time. In research on brain plasticity, Lampit and colleagues paired NeuroTrax with functional MRI in healthy older adults engaged in computerized cognitive training. The study identified functional and structural brain changes associated with training, with these changes relating to improvements in NeuroTrax global cognition (3). Together, these findings illustrate the power of combining objective cognitive testing with physiologic measures, albeit impractical for routine clinical use.
Enter the 2026 Zifman study, which demonstrates a practical approach for integrating digital cognitive neurometrics with sophisticated brain network measurements. Indeed, pairing NeuroTrax with technologies like in-clinic TMS-EEG offers an unprecedented opportunity to examine how brain function translates into measurable cognitive performance. Rather than relying on a single measure, this multimodal approach offers a more complete picture of cognitive aging. The Zifman study represents a compelling example of this direction, demonstrating that reduced prefrontal interhemispheric connectivity is strongly associated with cognitive impairment as defined by objective neurometrics.
With advances in technologies for early identification and longitudinal monitoring of cognitive decline, integrating clinically viable measures of brain physiology with NeuroTrax testing bridges the gap between advanced neuroscience and cognitive assessment. By linking measurable cognitive performance with the neuroanatomy and networks supporting it, researchers and clinicians can better understand how the aging brain changes over time, bringing brain science into their routine work.
References
[1] Zifman, N., Fogel, H., Rosenberg, R., Levy-Lamdan, O., Verhovski, N., Strauss, T., Bischof, E., and Goshen, A. (2026) Interhemispheric connectivity measured with transcranial magnetic stimulation and EEG as an objective marker of cognitive risk. Brain Communications, 8(4):fcag251. DOI: 10.1093/braincomms/fcag251
[2] Sasson, E., Doniger, G.M., Pasternak, O., Tarrasch, R., and Assaf, Y. (2012). Structural correlates of cognitive domains in normal aging with diffusion tensor imaging. Brain Structure and Function, 217(2), 503–515. DOI: 10.1007/s00429-011-0344-7
[3] Lampit, A., Hallock, H., Suo, C., Naismith, S.L., and Valenzuela, M. (2015). Cognitive training-induced short-term functional and long-term structural plastic change is related to gains in global cognition in healthy older adults: A pilot study. Frontiers in Aging Neuroscience, 7:14. DOI: 10.3389/fnagi.2015.00014
