Zachary Kilpatrick

Evidence accumulation and change rate inference in dynamic environments

The paper develops an ideal observer model to infer environmental state and change rate in dynamic environments, using a moment closure approximation and neural network models with plasticity rules.

Extending Levelt’s Propositions to perceptual multistability involving interocular grouping

The paper tests if Levelt's Propositions apply to interocular grouping perceptual multistability and finds they do, with a hierarchical model explaining the results.

Networks that learn the precise timing of event sequences

This paper introduces a recurrent network model that learns both the order and precise timing of event sequences through long-term plasticity and short-term facilitation.