To make decisions, animals must evaluate candidate choices by accessing memories of relevant experiences. Yet little is known about which experiences are considered or ignored during deliberation, which ultimately governs choice. We propose a normative theory predicting which memories should be accessed at each moment to optimize future decisions. Using nonlocal 'replay' of spatial locations in hippocampus as a window into memory access, we simulate a spatial navigation task in which an agent accesses memories of locations sequentially, ordered by utility: how much extra reward would be earned due to better choices. This prioritization balances two desiderata: the need to evaluate imminent choices versus the gain from propagating newly enco...
<div><p>We are remarkably adept at inferring the consequences of our actions, yet the neuronal mecha...
The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an ...
Reinforcement learning systems usually assume that a value function is defined over all states (or s...
To make decisions, animals must evaluate candidate choices by accessing memories of relevant experie...
Executing memory-guided behavior requires storage of information about experience and later recall o...
Effective navigation requires planning extended routes to remembered goal locations. Hippocampal pla...
Animals and humans replay neural patterns encoding trajectories through their environment, both whil...
Theories of neural replay propose that it supports a range of functions, most prominently planning a...
The hippocampus plays a role in spatial navigation, and place cells (cells that fire selectively for...
A modern synthesis of many studies examining hippocampal replay in decision-making tasks suggests th...
SummaryAlthough many preferential choices in everyday life require remembering relevant information,...
Animals and humans replay neural patterns encoding trajectories through their environment, both whil...
Hippocampal place-cell sequences observed during awake immobility often represent previous experienc...
Many decisions are based on an internal model of the world. Yet, how such a model is constructed fro...
Although many preferential choices in everyday life require remembering relevant information, the in...
<div><p>We are remarkably adept at inferring the consequences of our actions, yet the neuronal mecha...
The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an ...
Reinforcement learning systems usually assume that a value function is defined over all states (or s...
To make decisions, animals must evaluate candidate choices by accessing memories of relevant experie...
Executing memory-guided behavior requires storage of information about experience and later recall o...
Effective navigation requires planning extended routes to remembered goal locations. Hippocampal pla...
Animals and humans replay neural patterns encoding trajectories through their environment, both whil...
Theories of neural replay propose that it supports a range of functions, most prominently planning a...
The hippocampus plays a role in spatial navigation, and place cells (cells that fire selectively for...
A modern synthesis of many studies examining hippocampal replay in decision-making tasks suggests th...
SummaryAlthough many preferential choices in everyday life require remembering relevant information,...
Animals and humans replay neural patterns encoding trajectories through their environment, both whil...
Hippocampal place-cell sequences observed during awake immobility often represent previous experienc...
Many decisions are based on an internal model of the world. Yet, how such a model is constructed fro...
Although many preferential choices in everyday life require remembering relevant information, the in...
<div><p>We are remarkably adept at inferring the consequences of our actions, yet the neuronal mecha...
The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an ...
Reinforcement learning systems usually assume that a value function is defined over all states (or s...