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. 2019 Jul 17:11:173.
doi: 10.3389/fnagi.2019.00173. eCollection 2019.

Incidental Learning: A Systematic Review of Its Effect on Episodic Memory Performance in Older Age

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Incidental Learning: A Systematic Review of Its Effect on Episodic Memory Performance in Older Age

Carole C Wagnon et al. Front Aging Neurosci. .

Abstract

Episodic memory is the capacity to encode, store, and retrieve information of specific past events. Several studies have shown that the decline in episodic memory accompanies aging, but most of these studies assessed memory performance through intentional learning. In this approach, the individuals deliberately acquire knowledge. Yet, another method to evaluate episodic memory performance-receiving less attention by the research community-is incidental learning. Here, participants do not explicitly intent to learn. Incidental learning becomes increasingly important over the lifespan, since people spend less time in institutions where intentional learning is required (e.g., school, university, or at work). Yet, we know little how incidental learning impacts episodic memory performance in advanced age. Likewise, the neural mechanisms underlying incidental learning in older age remain largely unknown. Thus, the immediate goal of this review was to summarize the existing literature on how incidental learning changes with age and how neural mechanisms map onto these age-related changes. We considered behavioral as well as neuroimaging studies using incidental learning paradigms (alone or in combination with intentional learning) to assess episodic memory performance in elderly adults. We conducted a systematic literature search on the Medline/PubMed, Cochrane, and OVID SP databases and searched the reference lists of articles. The search yielded 245 studies, of which 34 concerned incidental learning and episodic memory in older adults. In sum, these studies suggest that aging particularly affects episodic memory after incidental learning for cognitively demanding tasks. Monitoring deficits in older adults might account for these findings since cognitively demanding tasks need increased attentional resources. On a neuronal level, dysregulation of the default-mode-network mirrors monitoring deficits, with an attempt to compensate through increased frontal activity. Future (neuroimaging) studies should systematically evaluate retrieval tasks with diverging cognitive load and consider the influence of attention and executive functions in more detail.

Keywords: aging; episodic memory; incidental learning; intentional learning; neural mechanisms; systematic review.

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Figures

Figure 1
Figure 1
The influence of incidental or intentional encoding on the three stages of episodic memory. During encoding, both deep incidental as well as intentional learning lead to a strong memory trace. During storage, weak memory traces following shallow encoding are more vulnerable to interference than strong memory traces after deep encoding. The disadvantage of shallow incidental encoding on later memory performance is mostly visible during free and cued recall and is almost eliminated during recognition.
Figure 2
Figure 2
Flow chart of the identification and inclusion of studies in the current review.
Figure 3
Figure 3
Figure of the most important functional magnetic resonance imaging results of the reviewed studies when applying incidental encoding in older compared to younger adults. DMN, default mode network; fMRI, functional Magnetic Resonance Imaging.

References

    1. Adler D. H., Wisse L. E. M., Ittyerah R., Pluta J. B., Ding S., Xie L., et al. . (2018). Characterizing the human hippocampus in aging and Alzheimer's disease using a computational atlas derived from ex vivo MRI and histology. Proc. Natl. Acad. Sci. U.S.A. 115, 4252–4257. 10.1073/pnas.1801093115 - DOI - PMC - PubMed
    1. Aine C. J., Adair J. C., Knoefel J. E., Hudson D., Qualls C., Kovacevic S., et al. . (2005). Temporal dynamics of age-related differences in auditory incidental verbal learning. Brain Res. Cogn. Brain Res. 24, 1–18. 10.1016/j.cogbrainres.2004.10.024 - DOI - PubMed
    1. Bäckman L., Nyberg L., Lindenberger U., Li S., Farde L. (2006). The correlative triad among aging, dopamine, and cognition. Current status and future prospects. Neurosci. Biobehav. Rev. 30, 791–807. 10.1016/j.neubiorev.2006.06.005 - DOI - PubMed
    1. Balota D. A., Cortese M. J., Duchek J. M., Adams D., Roediger H. L., McDermott K. B., et al. (1999). Verdical and false memories in healthy older adults and in dementia of the Alzheimer‘s type. Cogn. Neuropsychol. 16, 361–384. 10.1080/026432999380834. - DOI
    1. Baltes P. B., Cornelius S. W., Spiro A., Nesselroade J. R., Willis S. L. (1980). Integration versus differentiation of fluid/crytallized intelligence in old age. Dev. Psychol. 16, 625–635. 10.1037/0012-1649.16.6.625 - DOI

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