A Model-Based Approach to Understanding Memory Impairments in Normal Aging

描述（由申请人提供）：正常衰老最具破坏性的影响之一是回忆最近发生的事件越来越困难，特别是当这些事件受到在不同环境中所学到的相关记忆的干扰时。尽管形成和回忆情景记忆的困难是衰老过程的一个标志，但其背后的机制在很大程度上仍然未知。我们采用计算建模方法来帮助阐明三个主要的实验室记忆任务和更自然的“现实世界”任务中的这些机制。该应用程序的关键创新之处在于，它建议拟合在多时段实验中获得的高分辨率个体受试者数据，并根据最佳拟合参数的分布来检查年龄差异，这将使我们能够检测出表现出不同损伤特征的老年人亚组。由于高性能计算技术的进步，提供了足够高分辨率的数据，这种研究老龄化的新方法已经变得可行。对受年龄影响的记忆系统进行计算建模，不仅可以帮助我们更好地理解衰老记忆，而且还可以为建立与年龄有关的记忆障碍的老年人记忆修复方案提供理论基础。

DESCRIPTION (provided by applicant): One of the most damaging effects of normal aging is an increasing difficulty in recalling recent events especially when those events are subject to interference from related memories learned in different contexts. Although this difficulty in forming and recalling episodic memories is a hallmark of the aging process, the mechanisms that underlie it remain largely unknown. We adopt a computational modeling approach to help elucidate these mechanisms in three major laboratory memory tasks and in more naturalistic "real world" tasks. The key innovation of this application is in its proposal to fit high-resolutio individual subject data obtained in multisession experiments and to examine age-differences in terms of the distributions of best fitting parameters, which will allow us to detect subgroups of older adults that show different profiles of impairment. Given data of sufficiently high resolution this novel approach to aging research has become feasible thanks to advances in high-performance computing. Computational modeling of age-affected memory systems could lead not only to a better understanding of aging memory, but also provide a theoretical basis on which to build potential schemes for memory remediation among older adults suffering age-related memory impairment.