The neural circuitry mediating the influence of motivation on long-term declarative or episodic memory formation is delineated in young adults, but its status is unknown in healthy aging. We examined the effect of reward and punishment anticipation on intentional declarative memory formation for words using an event-related functional magnetic resonance imaging (fMRI) monetary incentive encoding task in twenty-one younger and nineteen older adults. At 24-hour memory retrieval testing, younger adults were significantly more likely to remember words associated with motivational cues than neutral cues. Motivational enhancement of memory in younger adults occurred only for recollection ("remember" responses) and not for familiarity ("familiar" responses). Older adults had overall diminished memory and did not show memory gains in association with motivational cues. Memory encoding associated with monetary rewards or punishments activated motivational (substantia nigra/ventral tegmental area) and memory-related (hippocampus) brain regions in younger, but not older, adults during the target word periods. In contrast, older and younger adults showed similar activation of these brain regions during the anticipatory motivational cue interval. In a separate monetary incentive delay task that did not require learning, we found evidence for relatively preserved striatal reward anticipation in older adults. This supports a potential dissociation between incidental and intentional motivational processes in healthy aging. The finding that motivation to obtain rewards and avoid punishments had reduced behavioral and neural influence on intentional episodic memory formation in older compared to younger adults is relevant to life-span theories of cognitive aging including the dopaminergic vulnerability hypothesis.
Pubmed ID: 29274503 RIS Download
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Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.
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