Science
Augmem™ Science
RAPID, RELIABLE, AND OBJECTIVE ASSESSMENTS OF MEMORY DECLINE.
Augmem™ uses neural circuit-based approaches backed by proprietary AI to create highly sensitive digital cognitive assessment tools.
The underlying science is informed by over 15 years of research more than 50 peer-reviewed publications.
Augmem™ is based on several decades of computational and empirical research across species that has now reliably demonstrated that memory for everyday events requires a process known as “pattern separation”.
This process allows our brains to create unique memories for similar experiences (for example, where you parked your car today vs. yesterday) and enabling us to store and retain rich, detailed memories of our past.
As we all get older, we begin to struggle with pattern separation, leading to a loss of contextual memories (where certain events occurred or when they occurred). Most of these changes can be benign and part of the normal aging process. Individuals affected by Alzheimer’s disease struggle to a much greater extent.
Work by Dr. Yassa and colleagues has shown that loss of pattern separation can be an early marker of memory loss in Alzheimer’s disease, prior to the onset of clinical symptoms.
Augmem™ is a digital cognitive assessment platform targeting pattern separation, coupled with an artificial intelligence (AI) engine that generates unprecedented insights into the cognitive processes and brain systems that underlie memory loss. It is highly sensitive to even the most subtle shifts in cognition and has been extensively validated using brain imaging studies.
Selected Publications
- Yassa, M.A., Stark, C.E. (2011) Pattern separation in the hippocampus. Trends in Neuroscience, 34(10), 515-25.
- Leal, S. L., & Yassa, M. A. (2018). Integrating new findings and examining clinical applications of pattern separation. Nature Neuroscience, 21(2), 163–173.
- Bakker, A., Krauss, G. L., Albert, M. S., Speck, C. L., Jones, L. R., Stark, C. E., Yassa, M. A., Bassett, S. S., Shelton, A. L., & Gallagher, M. (2012). Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron, 74(3), 467–474.
- Stark, S. M., Yassa, M. A., Lacy, J. W., & Stark, C. E. (2013). A task to assess behavioral pattern separation (BPS) in humans: Data from healthy aging and mild cognitive impairment. Neuropsychologia, 51(12), 2442–2449.
- Reagh, Z. M., Roberts, J. M., Ly, M., DiProspero, N., Murray, E., & Yassa, M. A. (2014). Spatial discrimination deficits as a function of mnemonic interference in aged adults with and without memory impairment. Hippocampus, 24(3), 303–314.
- Roberts, J. M., Ly, M., Murray, E., & Yassa, M. A. (2014). Temporal discrimination deficits as a function of lag interference in older adults. Hippocampus, 24(10), 1189–1196.
Borota, D., Murray, E., Keceli, G., Chang, A., Watabe, J.M., Ly, M., Toscano, J.P., Yassa, M.A. (2014) Post-study caffeine administration enhances memory consolidation in humans. Nature Neuroscience, 17(2):201-3.
Suwabe, K., Byun, K., Hyodo, K., Reagh, Z. M., Roberts, J. M., Matsushita, A., Saotome, K., Ochi, G., Fukuie, T., Suzuki, K., Sankai, Y., Yassa, M. A., & Soya, H. (2018). Rapid stimulation of human dentate gyrus function with acute mild exercise. Proceedings of the National Academy of Sciences of the United States of America, 115(41), 10487–10492.
Papp, K. V., Rentz, D. M., Maruff, P., Sun, C. K., Raman, R., Donohue, M. C., Schembri, A., Stark, C., Yassa, M. A., Wessels, A. M., Yaari, R., Holdridge, K. C., Aisen, P. S., & Sperling, R. A. (2021). The Computerized Cognitive Composite (C3) in an Alzheimer’s Disease Secondary Prevention Trial. The Journal of Prevention of Alzheimer’s Disease, 8(1), 59–67.
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