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Stijn Verdonck

Showing results (1-10 of 22) with videos related to

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Psychological Review|August 5, 2014
The Ising Decision Maker: a binary stochastic network for choice response timeStijn Verdonck, Francis Tuerlinckx
Psychological Review|December 8, 2015
Factoring out nondecision time in choice reaction time data: Theory and implicationsStijn Verdonck, Francis Tuerlinckx
Behavior Research Methods|March 13, 2015
Efficient simulation of diffusion-based choice RT models on CPU and GPUStijn Verdonck, Kristof Meers, Francis Tuerlinckx
Scientific Reports|March 19, 2021
A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracyTim Loossens, Francis Tuerlinckx, Stijn Verdonck
Behavior Research Methods|October 2, 2015
Erratum to: Efficient simulation of diffusion-based choice RT models on CPU and GPUStijn Verdonck, Kristof Meers, Francis Tuerlinckx
Psychological Review|September 11, 2020
The Leaky Integrating Threshold and its impact on evidence accumulation models of choice response time (RT)Stijn Verdonck, Tim Loossens, Marios G Philiastides
Scientific Reports|November 25, 2015
Fingerprint resampling: A generic method for efficient resamplingMerijn Mestdagh, Stijn Verdonck, Kevin Duisters, et al.
Behavior Research Methods|May 8, 2019
DstarM: an R package for analyzing two-choice reaction time data with the D∗M methodDon van den Bergh, Francis Tuerlinckx, Stijn Verdonck
Psychological Methods|September 28, 2021
Informing VAR(1) with qualitative dynamical features improves predictive accuracyTim Loossens, Egon Dejonckheere, Francis Tuerlinckx, et al.
Plos Biology|July 17, 2023
Secondary motor integration as a final arbiter in sensorimotor decision-makingTarryn Balsdon, Stijn Verdonck, Tim Loossens, et al.
Pageof 3

Showing results (1-10 of 22) with videos related to

Sort By:
Pageof 3
Psychological Review|August 5, 2014
The Ising Decision Maker: a binary stochastic network for choice response timeStijn Verdonck, Francis Tuerlinckx
Psychological Review|December 8, 2015
Factoring out nondecision time in choice reaction time data: Theory and implicationsStijn Verdonck, Francis Tuerlinckx
Behavior Research Methods|March 13, 2015
Efficient simulation of diffusion-based choice RT models on CPU and GPUStijn Verdonck, Kristof Meers, Francis Tuerlinckx
Scientific Reports|March 19, 2021
A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracyTim Loossens, Francis Tuerlinckx, Stijn Verdonck
Behavior Research Methods|October 2, 2015
Erratum to: Efficient simulation of diffusion-based choice RT models on CPU and GPUStijn Verdonck, Kristof Meers, Francis Tuerlinckx
Psychological Review|September 11, 2020
The Leaky Integrating Threshold and its impact on evidence accumulation models of choice response time (RT)Stijn Verdonck, Tim Loossens, Marios G Philiastides
Scientific Reports|November 25, 2015
Fingerprint resampling: A generic method for efficient resamplingMerijn Mestdagh, Stijn Verdonck, Kevin Duisters, et al.
Behavior Research Methods|May 8, 2019
DstarM: an R package for analyzing two-choice reaction time data with the D∗M methodDon van den Bergh, Francis Tuerlinckx, Stijn Verdonck
Psychological Methods|September 28, 2021
Informing VAR(1) with qualitative dynamical features improves predictive accuracyTim Loossens, Egon Dejonckheere, Francis Tuerlinckx, et al.
Plos Biology|July 17, 2023
Secondary motor integration as a final arbiter in sensorimotor decision-makingTarryn Balsdon, Stijn Verdonck, Tim Loossens, et al.
Pageof 3