Princeton Neuroscience Institute, Princeton University, Department of Psychology
In many tasks, such as mazes or chess, effective decision making typically requires enumerating the expected outcomes of candidate actions over a series of subsequent events. Because of the computational complexity of such evaluation, it is believed that human and animal brains use a range of shortcuts to simplify or approximate it. I review behavioral and neural evidence that humans rationally trade off exact and approximate evaluation in such sequential decision making. This research offers a new perspective on healthy behaviors, like habits, and pathological ones, like compulsion, which are both viewed as evaluations that fail to incorporate experiences relevant to a decision and instead rely on inappropriate or out-of-date evaluations. I also present new theoretical and experimental work that aims to address the the positive counterpart to such neglect: which particular events are considered, in which circumstances, to support choice. This brings the reach of the framework to many new phenomena, including pre-computation for future choices, nonlocal activity in the hippocampal place system, consolidation during sleep, and a new range of disordered symptoms such as craving, hallucinations, and rumination.
- Daphna Shohamy and Nathaniel D Daw (2015) - Integrating memories to guide decisions. http://www.princeton.edu/~ndaw/sd15.pdf
- Marcelo Gomes Mattar and Nathaniel D Daw (2018) - Prioritized memory access explains planning and hippocampal replay. https://www.biorxiv.org/content/biorxiv/early/2018/01/03/225664.full.pdf