Package index • rcicr

Generating stimuli

Build a stimulus set for a 2IFC task. The .Rdata file written here is the only link to the analysis half, so keep it.

generateStimuli2IFC(): Generates 2IFC stimuli
simulateNoiseIntensities(): Simulate pixel intensity range for noise

Classification images

Turn collected responses into classification images, and render them.

generateCI(): Generates classification image
generateCI2IFC(): Generates 2IFC classification image
batchGenerateCI(): Generates multiple classification images by participant or condition
batchGenerateCI2IFC(): Generates multiple 2IFC classification images by participant or condition
autoscale(): Determines optimal scaling constant for a list of CIs
plotZmap(): Plots a Z-map
computeCumulativeCICorrelation(): Computes cumulative trial CIs correlations with final/target CI

Informational value

How much signal a classification image carries, against a simulated null.

computeInfoVal2IFC(): Computes Informational Value
generateReferenceDistribution2IFC(): Generates reference distribution

Noise basis

The sinusoid and Gabor machinery the stimuli are built from. Exported so the noise can be inspected and reused; most analyses never call these directly.

generateNoisePattern(): Generate sinusoid noise pattern
generateNoiseImage(): Generate single noise image based on parameter vector
generateCINoise(): Generate classification image noise pattern based on set of stimuli (matrix: trials, parameters), responses (vector), and sinusoid
generateSinusoid(): Generate single sinusoid patch
generateGabor(): Generate single gabor patch
deg2rad(): Convert angle in degrees to radians

Package

rcicr rcicr-package: rcicr: Reverse-Correlation Image-Classification Toolbox