RaceModel
RaceModel is a MATLAB package for stochastic modelling of multisensory reaction times (RTs). It is suitable for analyzing empirical data or running simulations, and can handle datasets of unequal sizes and with missing values (NaNs). The toolbox can be used to build parallel models of multisensory information processing for both OR and AND task designs (e.g., the race model; Miller, 1982), as well as bisensory and trisensory paradigms. Parallel models can be generated under the assumption that RTs on separate sensory channels are stochastically independent (independent race model), perfectly negatively dependent (Miller's bound) or perfectly positively dependent (Grice's bound), and can be tested using either the vertical or horizontal method. Separate functions compute geometric measures of multisensory gain (violation), multisensory benefit (Otto et al., 2013) and modality switch effects.
RaceModel also includes a systems factorial technology framework for inferring system architecture and measuring the workload capacity of a system (Townsend & Nozawa, 1995). The latter can also be assessed for OR/AND tasks and bisensory/trisensory paradigms. System architecture can also be examined using a novel framework for biasing the stopping rule (Crosse et al., 2019). The toolbox also includes an outlier correction procedure for cleaning data prior to testing. For statistical analyses, we recommend using multivariate permutation tests with tmax correction. This method provides strong control of family-wise error rate, even for small sample sizes, and is much more powerful than traditional methods (Gondan, 2010). We provide a separate MATLAB toolbox for multivariate permutation testing here.
Documentation
Crosse MJ, Foxe JJ, Molholm S (2019) RaceModel: A MATLAB Package for Stochastic Modelling of Multisensory Reaction Times (In prep).
Contents
Redundant signals (OR) task
Bisensory
* ormodel.m - compute parallel (race) model
* ormre.m - compute multisensory response enhancement
* orgain.m - compute multisensory gain (violation)
* orbenefit.m - compute empirical and predicted benefits
* orcapacity.m - compute capacity coefficient and bounds
Trisensory
* ormodel3.m - compute parallel (race) model
* ormre3.m - compute multisensory response enhancement
* orgain3.m - compute multisensory gain (violation)
* orbenefit3.m - compute empirical and predicted benefits
* orcapacity3.m - compute capacity coefficient and bounds
Exhaustive search (AND) task
Bisensory
* andmodel.m - compute parallel (AND) model
* andmre.m - compute multisensory response enhancement
* andgain.m - compute multisensory gain (violation)
* andbenefit.m - compute empirical and predicted benefits
* andcapacity.m - compute capacity coefficient and bounds
Trisensory
* andmodel3.m - compute parallel (AND) model
* andmre3.m - compute multisensory response enhancement
* andgain3.m - compute multisensory gain (violation)
* andbenefit3.m - compute empirical and predicted benefits
* andcapacity3.m - compute capacity coefficient and bounds
System Architecture
* sft.m - systems factorial technology framework
* biasmodel.m - compute bias model
* biasgain.m - compute multisensory gain (violation)
* biasbenefit.m - compute empirical and predicted benefits
Modality Switch Effects
* trialhistory.m - separate RTs based on trial history
* switchcost.m - compute modality switch effects
Accuracy
* f1score.m - compute F1 score of a test's detection accuracy
Preprocessing
* clearnrts.m - perform outlier correction procedures
* rt2pdf.m - convert RTs to a probability density function
* rt2cdf.m - convert RTs to a cumulative distribution function
* rt2cfp.m - convert RTs to a cumulative frequency polygon
* cfp2q.m - convert a cumulative frequency polygon to quantiles
* getauc.m - compute the area under the curve
Zitieren als
Mick Crosse (2024). RaceModel (https://github.com/mickcrosse/RaceModel), GitHub. Abgerufen .
Crosse MJ, Foxe JJ, Molholm S (2019) RaceModel: A MATLAB Package for Stochastic Modelling of Multisensory Reaction Times (In prep).
Kompatibilität der MATLAB-Version
Plattform-Kompatibilität
Windows macOS LinuxTags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Live Editor erkunden
Erstellen Sie Skripte mit Code, Ausgabe und formatiertem Text in einem einzigen ausführbaren Dokument.
and_task
or_task
preprocessing
system_architecture
Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden
Version | Veröffentlicht | Versionshinweise | |
---|---|---|---|
1.0.0 |
|