Whether it's choosing between dinner locations, health plans or investment vehicles for our savings, many
decisions involve a tradeoff between exploring options that are unknown and exploiting options we know well.
Making such explore-exploit decisions “correctly”, i.e. in such a way as to maximize long-term gain, is
surprisingly difficult and mathematically optimal solutions are intractable in most cases. Despite this difficulty,
we have recently shown that young people make remarkably effective explore-exploit decisions using a
mixture of two strategies: directed exploration, in which information seeking drives exploration by choice, and
random exploration, in which adaptive behavioral variability drives exploration by chance. Despite this
progress, little is known about how directed and random exploration are implemented in the brain, and almost
nothing is known about how these strategies change with age. Given the ubiquity of these decisions in daily
life, this is a critical omission if we are to understand decision making in aging and cognitive decline.
The objective of this proposal is to develop and test a neurocomputational model that describes explore-exploit
decision making throughout the lifespan. In this model, we propose that the overall balance between
exploration and exploitation is set by activity in a specific set of brain areas. Our central hypothesis is that age-
related changes in explore-exploit behavior can be accounted for by age-related changes in this circuit. To test
this hypothesis we will pursue three Specific Aims that test key predictions of this neurocomputational model
as it applies to healthy aging. Aim 1 will test the behavioral predictions of this model by characterizing the
explore-exploit behavior of a large sample of healthy older and younger adults. Aim 2 will map the brain areas
involved in directed and random exploration using functional and structural magnetic resonance imaging.
Finally, in Aim 3 we will manipulate directed and random exploration using transcranial magnetic stimulation to
perturb neural firing in key areas of the explore-exploit network.
The proposed research is innovative as the first to study directed and random exploration in older adults, the
first to probe the neural correlates of these strategies, and the first to manipulate explore-exploit behavior in
older adults with transcranial magnetic stimulation. In addition, by testing the predictions of the circuit model,
this work will build towards a neurocomputational account of explore-exploit behavior. This model will have
significant impact on our understanding of decision making in old age and provide a framework for
understanding how these decisions change with cognitive decline and Alzheimer's disease. Finally, if our
single-session TMS manipulations are successful, we will open the possibility of using multi-session neural
stimulation to enhance explore-exploit decision making in cases where it is impaired.