The primary goal of the proposed research is to identify differences between young and old adults in the neural processes underlying implicit learning. Implicit learning is the non-conscious acquisition of information that occurs without intent or awareness of what has been learned. Research in aging has mostly focused on explicit learning, and thus, the effects of healthy age-related brain changes on implicit learning have remained largely ignored, limiting the scope of the cognitive neuroscience of aging. This is unfortunate because sensitivity to regularities in the environment makes it possible to anticipate and process future events more effectively and this ability is essential throughout the lifespan. Whether implicit learning declines with healthy aging is unclear, though age-related deficits are observed when the stimuli to be learned are complex and when people are given extended training. Here, 24 young and 24 old adults will undergo functional magnetic resonance imaging (fMRI) while they learn and practice a complex, probabilistic sequential implicit skill. It is predicted that old adults will learn as well as the young early in training, but with more practice, age-related deficits will emerge (Specific Aim 1), making this proposed study the first to assess brain activity during implicit learning when behavior is both spared and impaired. The dissociation between early and practiced implicit learning is important to cognitive neuroscience for two reasons. First, previous imaging studies suggest that skill learning involves different brain regions as learning progresses;early learning involves the medial temporal lobes (i.e. hippocampus) and later, practiced learning involves the striatum (i.e. caudate). The proposed study will be among the first to examine whether these same learning-activation relationships are characteristic of implicit learning (Specific Aim 2), by using a paradigm in which explicit learning can be ruled out. Second, the brain regions underlying early and practiced learning differ in the extent to which they are compromised by aging. In the proposed study, functional connectivity analyses will examine relationships between brain activity and early versus practiced learning to assess how age-related differences in neural recruitment vary with the level of practice (Specific Aim 3). It is predicted that early implicit learning will activate the hippocampus or MTL networks in both age groups, reflecting the relatively preserved MTL in healthy aging. In practiced learning, younger adults will demonstrate activation in caudal or striatal networks. Due to aging- related declines, caudate activation will not be as dominant in older adults;older adults will rely on their intact learning-related brain regions, including the hippocampus and surrounding MTL. These findings would be consistent with the view that healthy aging affects the striatum more than the MTL.

Public Health Relevance

Implicit learning of subtle sequential events can promote independent living by supporting cognitive flexibility and can help older adults anticipate and adapt to an ever-changing world (i.e. new settings, people, and technologies). Thus, establishing the kinds of implicit learning that are intact versus impaired may be useful for designing educational programs or enhancing rehabilitation efforts, because such training could take advantage of the older persons'spared capacities and compensate for those that have declined in order to maximize successful aging. Defining normal age differences in brain function may also help in early detection of common age-related diseases, such as Alzheimer's and Parkinson's.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Predoctoral Individual National Research Service Award (F31)
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Special Emphasis Panel (ZRG1-F12A-E (20))
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Wagster, Molly V
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Georgetown University
Schools of Arts and Sciences
United States
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Simon, Jessica R; Vaidya, Chandan J; Howard, James H et al. (2012) The effects of aging on the neural basis of implicit associative learning in a probabilistic triplets learning task. J Cogn Neurosci 24:451-63
Simon, Jessica R; Stollstorff, Melanie; Westbay, Lauren C et al. (2011) Dopamine transporter genotype predicts implicit sequence learning. Behav Brain Res 216:452-7
Simon, Jessica R; Howard Jr, James H; Howard, Darlene V (2011) Age differences in implicit learning of probabilistic unstructured sequences. J Gerontol B Psychol Sci Soc Sci 66:32-8