Animals can quickly learn to make appropriate decisions according to their environment that can change over a wide range of timescales. Yet the neural computation underling the adaptive decision making is not well understood. To investigate basic computational principles and neural mechanisms, here we study simple neural network models for decision making with learning on multiple timescales, and we test our model's predictions in experimental data. We provide basic network models for value-based decision making under uncertainty
Abstract The value of the environment determines animals’ motivational states and sets expectations ...
Abstract. Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a...
This paper reviews some basic issues and methods involved in using neural networks to respond in a d...
Recent experiments have shown that animals and humans have a remarkable ability to adapt their learn...
SummaryVolitional behavior relies on the brain's ability to remap sensory flow to motor programs whe...
Behavior deviating from our normative expectations often appears irrational. For example, even thoug...
Behavior deviating from our normative expectations often appears irrational. For example, even thoug...
The matching law constitutes a quantitative description of choice behavior that is often observed in...
According to a prominent view of sensorimotor processing in primates, selection and specification of...
Neurophysiological experiments on monkeys and rodents have highlighted the neural mechanisms of deci...
Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral d...
Thesis (Master's)--University of Washington, 2021A salient difference between artificial and biologi...
Neural networks with a single plastic layer employing reward modulated spike time dependent plastici...
How do animals represent their environment? Which representations would best enable decision making...
SummaryWhen making a decision, one must first accumulate evidence, often over time, and then select ...
Abstract The value of the environment determines animals’ motivational states and sets expectations ...
Abstract. Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a...
This paper reviews some basic issues and methods involved in using neural networks to respond in a d...
Recent experiments have shown that animals and humans have a remarkable ability to adapt their learn...
SummaryVolitional behavior relies on the brain's ability to remap sensory flow to motor programs whe...
Behavior deviating from our normative expectations often appears irrational. For example, even thoug...
Behavior deviating from our normative expectations often appears irrational. For example, even thoug...
The matching law constitutes a quantitative description of choice behavior that is often observed in...
According to a prominent view of sensorimotor processing in primates, selection and specification of...
Neurophysiological experiments on monkeys and rodents have highlighted the neural mechanisms of deci...
Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral d...
Thesis (Master's)--University of Washington, 2021A salient difference between artificial and biologi...
Neural networks with a single plastic layer employing reward modulated spike time dependent plastici...
How do animals represent their environment? Which representations would best enable decision making...
SummaryWhen making a decision, one must first accumulate evidence, often over time, and then select ...
Abstract The value of the environment determines animals’ motivational states and sets expectations ...
Abstract. Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a...
This paper reviews some basic issues and methods involved in using neural networks to respond in a d...