The overall objective is to understand of the factors mediating and moderating transfer of learning in the context of training Working Memory (WM) systems. There is accumulating evidence that WM training impacts performance in a wide variety of tasks, however, to date, knowledge is extremely limited regarding the underlying mechanisms that mediate plasticity in WM systems, and what components of training give rise to transfer to different tasks. This proposal is transformative in how it applies knowledge derived from plasticity in other brain systems (such as perceptual learning, where there is substantial understanding of mechanisms that dtrive transfer) to test their impact in WM systems (Aim 1), in the creation of novel measures to asses transfer to real-world cognition (Aim 2), and in the use of online ?crowd-sourced? studies to characterize individual differences using a large population (Aim 3). These studies are particularly important and timely given current state of the field, which is fraught with controversy, and the lack of understanding of the relevant attributes of training and individual differences factors that give rise to successful training outcomes. Understanding the factors that mediate successful learning, as well as the individual differences moderating these is critical to resolve the current controversies and to move towards a theoretical model of training and transfer. Potential for knowledge gain and translational impact is substantial. Understanding how our memory systems work and the mechanisms that guide learning has great potential to be applied broadly in society. Our acquisition of knowledge in the world intimately relies on WM processes, thus, improvements in WM can benefit almost all aspects of our lives. This has driven a now billion-dollar commercial market that has provided early generation training approaches, which are extremely controversial in the scientific community. The proposed research can shed light on the factors that mediate and moderate these types of cognitive interventions and address the extent to which some procedures may, and others may not, lead to improvements in real world cognition. This can potentially lead to educational, rehabilitative, and technological advancements. For example, WM deficits exist in a wide range of mental health conditions, cases of disease and brain damage, and in cognitive declines with aging, and training approaches that promote better functioning WM systems can promote health and well-being in these groups. Further this research can elucidate approaches that may not work and help people avoid use of infective procedures. The proposed training software will be created on cross-platform game engines to enable dissemination to diverse populations. In this sense, the research output has innovative and broad impacts that can be directly realized from the proposed research. Many individuals are already using ?brain training? products, however, none incorporate the theoretically-driven approaches designed to optimize WM learning with an aim to transfer that training to real world benefit, and that are systematically researched, as proposed here. Programs created in the proposed work will be made publically available.
The proposed research is relevant to public health in that it will lead to greater understanding of, and creation of more effective, behavioral interventions for those with cognitive impairments. This research is aligned with the NIMH RDoC framework as working memory deficits exist in a wide range of mental health conditions, cases of disease and brain damage, and are associated with age-related cognitive decline. Targeted training to improve working memory has potential to give rise to personalized interventions that can be used on an outpatient basis. In addition to alignment with NIMH, this proposed research cuts across the bounds of numerous NIH agencies, with our framework contributing to the missions of the NCI, NEI, NIA, NIAAA, NINCD, NIDA, NINDS, in that all of these agencies work with populations who can gain direct benefits from successful approaches to mental fitness.
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| Waris, Otto; Soveri, Anna; Ahti, Miikka et al. (2017) A Latent Factor Analysis of Working Memory Measures Using Large-Scale Data. Front Psychol 8:1062 |
