Distal Modeling Framework for Pavlovian Conditioning Phenomena

In this model, Pavlovian phenomena conditioning phenomena (acquisition, extinction, spontaneous recovery and the partial reinforcement extinction effect) emerge from reward predictions of parallel neural circuits that combine according to their time-varying uncertainties. This package provides methods to compute the model for different parameter values and fit parameters to experimental data.

Package:	pdmod
Type:	Package
Version:	1.0
Date:	2014-03-27
License:	GPL (>=2)

For a given set of rewards/non-rewards paired with a signal in a Pavlovian conditioning experiment (specified as a TimedVector), the animal's response for a given set of parameter values can be computed with computeModel. Additionally, if experimental response data is available, the parameter values can be fit to the data using fitModel. Additional methods averageBySession and plot.pdmod are available to manipulate and plot model results.

TimedVector is a class used to associate reward/no-reward with a time schedule with helper methods c, isTimedVector, print, time, and verifyTimedVector.

Chloe Bracis

Maintainer: Chloe Bracis <cbracis@uw.edu>

pdmod documentation built on May 2, 2019, 5:16 a.m.