Abstract
In modern life, we engage with many sources of information concurrently. To do this, we must continuously switch between different tasks, but this comes at a cost to performance, especially in older adults. Using a large dataset from an online cognitive-training platform, we develop a computational model of task switching that defines distinct latent measures of activating the relevant task, deactivating the irrelevant task, and making a decision. This model shows that, although task practice can improve task-switching performance, persistent costs remain even after extensive practice, and more so in older adults. We show that, with extensive task practice, older people can become functionally similar to less-practiced younger people.
An important feature of human cognition is the ability to flexibly and efficiently adapt behavior in response to continuously changing contextual demands. We leverage a large-scale dataset from Lumosity, an online cognitive-training platform, to investigate how cognitive processes involved in cued switching between tasks are affected by level of task practice across the adult lifespan. We develop a computational account of task switching that specifies the temporal dynamics of activating task-relevant representations and inhibiting task-irrelevant representations and how they vary with extended task practice across a number of age groups. Practice modulates the level of activation of the task-relevant representation and improves the rate at which this information becomes available, but has little effect on the task-irrelevant representation. While long-term practice improves performance across all age groups, it has a greater effect on older adults. Indeed, extensive task practice can make older individuals functionally similar to less-practiced younger individuals, especially for cognitive measures that focus on the rate at which task-relevant information becomes available.
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