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>
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