Article

Age-related neural changes in autobiographical remembering and imagining.

Department of Psychology, The University of Auckland, Auckland, New Zealand.
Neuropsychologia (Impact Factor: 3.48). 09/2011; 49(13):3656-69. DOI:10.1016/j.neuropsychologia.2011.09.021
Source: PubMed

ABSTRACT Numerous neuroimaging studies have revealed that in young adults, remembering the past and imagining the future engage a common core network. Although it has been observed that older adults engage a similar network during these tasks, it is unclear whether or not they activate this network in a similar manner to young adults. Young and older participants completed two autobiographical tasks (imagining future events and recalling past events) in addition to a semantic-visuospatial control task. Spatiotemporal Partial Least Squares analyses examined whole brain patterns of activity across both the construction and elaboration of autobiographical events. These analyses revealed that that both age groups activated a similar network during the autobiographical tasks. However, some key age-related differences in the activation of this network emerged. During the construction of autobiographical events, older adults showed less activation relative to younger adults, in regions supporting episodic detail such as the medial temporal lobes and the precuneus. Later in the trial, older adults showed differential recruitment of medial and lateral temporal regions supporting the elaboration of autobiographical events, and possibly reflecting an increased role of conceptual information when older adults describe their pasts and their futures.

0 0
 · 
0 Bookmarks
 · 
81 Views
  • [show abstract] [hide abstract]
    ABSTRACT: This article considers two recent lines of research concerned with the construction of imagined or simulated events that can provide insight into the relationship between memory and decision making. One line of research concerns episodic future thinking, which involves simulating episodes that might occur in one's personal future, and the other concerns episodic counterfactual thinking, which involves simulating episodes that could have happened in one's personal past. We first review neuroimaging studies that have examined the neural underpinnings of episodic future thinking and episodic counterfactual thinking. We argue that these studies have revealed that the two forms of episodic simulation engage a common core network including medial parietal, prefrontal, and temporal regions that also supports episodic memory. We also note that neuroimaging studies have documented neural differences between episodic future thinking and episodic counterfactual thinking, including differences in hippocampal responses. We next consider behavioral studies that have delineated both similarities and differences between the two kinds of episodic simulation. The evidence indicates that episodic future and counterfactual thinking are characterized by similarly reduced levels of specific detail compared with episodic memory, but that the effects of repeatedly imagining a possible experience have sharply contrasting effects on the perceived plausibility of those events during episodic future thinking versus episodic counterfactual thinking. Finally, we conclude by discussing the functional consequences of future and counterfactual simulations for decisions.
    Neurobiology of Learning and Memory 12/2013; · 3.33 Impact Factor
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Generating predictions during action observation is essential for efficient navigation through our social environment. With age, the sensitivity in action prediction declines. In younger adults, the action observation network (AON), consisting of premotor, parietal and occipitotemporal cortices, has been implicated in transforming executed and observed actions into a common code. Much less is known about age-related changes in the neural representation of observed actions. Using fMRI, the present study measured brain activity in younger and older adults during the prediction of temporarily occluded actions (figure skating elements and simple movement exercises). All participants were highly familiar with the movement exercises whereas only some participants were experienced figure skaters. With respect to the AON, the results confirm that this network was preferentially engaged for the more familiar movement exercises. Compared to younger adults, older adults recruited visual regions to perform the task and, additionally, the hippocampus and caudate when the observed actions were familiar to them. Thus, instead of effectively exploiting the sensorimotor matching properties of the AON, older adults seemed to rely predominantly on the visual dynamics of the observed actions to perform the task. Our data further suggest that the caudate played an important role during the prediction of the less familiar figure skating elements in better-performing groups. Together, these findings show that action prediction engages a distributed network in the brain, which is modulated by the content of the observed actions and the age and experience of the observer.
    PLoS ONE 05/2013; 8(5):e64195. · 3.73 Impact Factor
  • [show abstract] [hide abstract]
    ABSTRACT: What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimer's Disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.
    Progress in Neurobiology 01/2014; · 9.04 Impact Factor

Full-text (2 Sources)

View
11 Downloads
Available from
Dec 30, 2013