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Eric-jan Wagenmakers - One of the best experts on this subject based on the ideXlab platform.
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Modeling across-trial variability in the Wald Drift Rate parameter
Behavior Research Methods, 2020Co-Authors: Helen Steingroever, Dominik Wabersich, Eric-jan WagenmakersAbstract:The shifted-Wald model is a popular analysis tool for one-choice reaction-time tasks. In its simplest version, the shifted-Wald model assumes a constant trial-independent Drift Rate parameter. However, the presence of endogenous processes—fluctuation in attention and motivation, fatigue and boredom—suggest that Drift Rate might vary across experimental trials. Here we show how across-trial variability in Drift Rate can be accounted for by assuming a trial-specific Drift Rate parameter that is governed by a positive-valued distribution. We consider two candidate distributions: the truncated normal distribution and the gamma distribution. For the resulting distributions of first-arrival times, we derive analytical and sampling-based solutions, and implement the models in a Bayesian framework. Recovery studies and an application to a data set comprised of 1469 participants suggest that (1) both mixture distributions yield similar results; (2) all model parameters can be recovered accuRately except for the Drift variance parameter; (3) despite poor recovery, the presence of the Drift variance parameter facilitates accuRate recovery of the remaining parameters; (4) shift, threshold, and Drift mean parameters are correlated.
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Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates
Computational Brain & Behavior, 2020Co-Authors: Catherine Manning, Eric-jan Wagenmakers, Anthony M. Norcia, Gaia Scerif, Udo BoehmAbstract:Children make faster and more accuRate decisions about perceptual information as they get older, but it is unclear how different aspects of the decision-making process change with age. Here, we used hierarchical Bayesian diffusion models to decompose performance in a perceptual task into sepaRate processing components, testing age-related differences in model parameters and links to neural data. We collected behavioural and EEG data from 96 6- to 12-year-old children and 20 adults completing a motion discrimination task. We used a component decomposition technique to identify two response-locked EEG components with ramping activity preceding the response in children and adults: one with activity that was maximal over centro-parietal electrodes and one that was maximal over occipital electrodes. Younger children had lower Drift Rates (reduced sensitivity), wider boundary separation (increased response caution) and longer non-decision times than older children and adults. Yet, model comparisons suggested that the best model of children’s data included age effects only on Drift Rate and boundary separation (not non-decision time). Next, we extracted the slope of ramping activity in our EEG components and covaried these with Drift Rate. The slopes of both EEG components related positively to Drift Rate, but the best model with EEG covariates included only the centro-parietal component. By decomposing performance into distinct components and relating them to neural markers, diffusion models have the potential to identify the reasons why children with developmental conditions perform differently to typically developing children and to uncover processing differences inapparent in the response time and accuracy data alone.
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Modeling Across-Trial Variability in the Wald Drift Rate Parameter
2018Co-Authors: Helen Steingroever, Dominik Wabersich, Eric-jan WagenmakersAbstract:The shifted-Wald model is a popular analysis tool for one-choice reaction time tasks. In its simplest version, the shifted-Wald model assumes a constant trial-independent Drift Rate parameter. However, the presence of endogenous processes –fluctuation in attention and motivation, fatigue and boredom– suggest that Drift Rate might vary across experimental trials. Here we show how across-trial variability in Drift Rate can be accounted for byassuming a trial-specific Drift Rate parameter that is governed by a positive valued distribution.
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A test of the diffusion model explanation for the worst performance rule using preregistration and blinding
Attention Perception & Psychophysics, 2017Co-Authors: Gilles Dutilh, Joachim Vandekerckhove, Alexander Ly, Dora Matzke, Andreas Pedroni, Renato Frey, Jörg Rieskamp, Eric-jan WagenmakersAbstract:People with higher IQ scores also tend to perform better on elementary cognitive-perceptual tasks, such as deciding quickly whether an arrow points to the left or the right Jensen ( 2006 ). The worst performance rule (WPR) finesses this relation by stating that the association between IQ and elementary-task performance is most pronounced when this performance is summarized by people’s slowest responses. Previous research has shown that the WPR can be accounted for in the Ratcliff diffusion model by assuming that the same ability parameter—Drift Rate—mediates performance in both elementary tasks and higher-level cognitive tasks. Here we aim to test four qualitative predictions concerning the WPR and its diffusion model explanation in terms of Drift Rate. In the first stage, the diffusion model was fit to data from 916 participants completing a perceptual two-choice task; crucially, the fitting happened after randomly shuffling the key variable, i.e., each participant’s score on a working memory capacity test. In the second stage, after all modeling decisions were made, the key variable was unshuffled and the adequacy of the predictions was evaluated by means of confirmatory Bayesian hypothesis tests. By temporarily withholding the mapping of the key predictor, we retain flexibility for proper modeling of the data (e.g., outlier exclusion) while preventing biases from unduly influencing the results. Our results provide evidence against the WPR and suggest that it may be less robust and less ubiquitous than is commonly believed.
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Generalising the Drift Rate distribution for linear ballistic accumulators
Journal of Mathematical Psychology, 2015Co-Authors: Andrew Terry, Eric-jan Wagenmakers, A. A. J. Marley, Avinash Barnwal, Andrew Heathcote, Scott D. BrownAbstract:The linear ballistic accumulator model is a theory of decision-making that has been used to analyse data from human and animal experiments. It represents decisions as a race between independent evidence accumulators, and has proven successful in a form assuming a normal distribution for accumulation ("Drift") Rates. However, this assumption has some limitations, including the corollary that some decision times are negative or undefined. We show that various Drift Rate distributions with strictly positive support can be substituted for the normal distribution without loss of analytic tractability, provided the candidate distribution has a closed-form expression for its mean when truncated to a closed interval. We illustRate the approach by developing three new linear ballistic accumulation variants, in which the normal distribution for Drift Rates is replaced by either the lognormal, Frechet, or gamma distribution. We compare some properties of these new variants to the original normal-Rate model.
Heather Ratcliffe - One of the best experts on this subject based on the ideXlab platform.
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large scale simulations of solar type iii radio bursts flux density Drift Rate duration and bandwidth
Astronomy and Astrophysics, 2014Co-Authors: Heather Ratcliffe, Eduard P Kontar, Hamish A S ReidAbstract:Non-thermal electrons acceleRated in the solar corona can produce intense coherent radio emission, known as solar type III radio bursts. This intense radio emission is often observed from hundreds of MHz in the corona down to the tens of kHz range in interplanetary space. It involves a chain of physical processes from the generation of Langmuir waves to non-linear processes of wave-wave interaction. We develop a self-consistent model to calculate radio emission from a non-thermal electron population over a large frequency range, including the effects of electron transport, Langmuir wave-electron interaction, the evolution of Langmuir waves due to non-linear wave-wave interactions, Langmuir wave conversion into electromagnetic emission, and finally escape of the electromagnetic waves. For the first time we simulate escaping radio emission over a broad frequency range from 500 MHz down to a few MHz and infer key properties of the radio emission observed: the onset (starting) frequency, identification as fundamental or harmonic emission, peak flux density, instantaneous frequency bandwidth, and timescales for rise and decay. By comparing these large-scale simulations with the observations, we can identify the processes governing the major type III solar radio burst characteristics.
Hamish A S Reid - One of the best experts on this subject based on the ideXlab platform.
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large scale simulations of solar type iii radio bursts flux density Drift Rate duration and bandwidth
Astronomy and Astrophysics, 2014Co-Authors: Heather Ratcliffe, Eduard P Kontar, Hamish A S ReidAbstract:Non-thermal electrons acceleRated in the solar corona can produce intense coherent radio emission, known as solar type III radio bursts. This intense radio emission is often observed from hundreds of MHz in the corona down to the tens of kHz range in interplanetary space. It involves a chain of physical processes from the generation of Langmuir waves to non-linear processes of wave-wave interaction. We develop a self-consistent model to calculate radio emission from a non-thermal electron population over a large frequency range, including the effects of electron transport, Langmuir wave-electron interaction, the evolution of Langmuir waves due to non-linear wave-wave interactions, Langmuir wave conversion into electromagnetic emission, and finally escape of the electromagnetic waves. For the first time we simulate escaping radio emission over a broad frequency range from 500 MHz down to a few MHz and infer key properties of the radio emission observed: the onset (starting) frequency, identification as fundamental or harmonic emission, peak flux density, instantaneous frequency bandwidth, and timescales for rise and decay. By comparing these large-scale simulations with the observations, we can identify the processes governing the major type III solar radio burst characteristics.
Christian Monstein - One of the best experts on this subject based on the ideXlab platform.
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Electron Density And Drift Rate Of Solar Burst Type II During 1 st June 2015
International Letters of Chemistry Physics and Astronomy, 2016Co-Authors: Zety Sharizat Hamidi, N. N. M. Shariff, M. O. Ali, Christian MonsteinAbstract:This event allows us to investigate the electron density and Drift Rate of solar burst type II During 1 st June 2015. It is believed that the plasma-magnetic field interactions in the solar corona can produce suprathermal electron populations over periods from tens of minutes to several hours, and the interactions of wave-particle and wave-wave lead to characteristic fine structures of the emission. An intense and broad solar radio burst type II was recorded by CALLISTO spectrometer from 25-80 MHz. Using data from a the Blein observatory, the complex structure of solar burst type III can also be found in the early stage of the formation of type II solar burst type event due to active region AR2358. The Drift Rate of solar burst type II exceeds 0.03 MHz/s with a density of electron in the solar corona. There are 18 CMEs occurring that day and the distributions of CME speed are between 200 ms -1 to 1100 ms -1 so that the average velocity of the CMEs that occur that day is 1025 m/s. This is one of the largest number of sunspots that have recorded in this year. However, all of these sunspots are quiet and stable and the solar activity remains low. Therefore, it can be observed that only B class of flare from the X-Ray Flux Data.
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Investigation of Drift Rate of Solar Radio Burst Type II due to Coronal Mass Ejections Phenomenon
International Letters of Chemistry Physics and Astronomy, 2015Co-Authors: N. H. Zainol, Zety Sharizat Hamidi, N. N. M. Shariff, S. Arifin, Christian MonsteinAbstract:The formation of detected solar radio burst type II occurred was captured using Compound Astronomical Low Cost Frequency Spectrometer Transportable Observatory (CALLISTO) system which gives a better resolution of a wonderful image than other countries. The phenomenon was found on 2 nd November 2014 at 09:39 [UT] in Switzerland. CALLISTO spectrometer device detects and traces a Coronal Mass Ejections (CMEs) phenomenon that causes the occurrence of the solar burst type II. As it happened, the Drift Rate of the solar radio burst Type II is calculated and discussed in details. Plasma frequency (fp), Langmuir waves and type II radiation relates each other in the establishment of this phenomenon. This paper presents a study of Drift Rate selected event of solar radio burst type II based on CMEs. The Drift Rate at this moment was about 3.2 MHz/s which has low Drift Rate thus the velocity OF THE CMEs was just about 695 km/s shown from NOAA.
Helen Steingroever - One of the best experts on this subject based on the ideXlab platform.
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Modeling across-trial variability in the Wald Drift Rate parameter
Behavior Research Methods, 2020Co-Authors: Helen Steingroever, Dominik Wabersich, Eric-jan WagenmakersAbstract:The shifted-Wald model is a popular analysis tool for one-choice reaction-time tasks. In its simplest version, the shifted-Wald model assumes a constant trial-independent Drift Rate parameter. However, the presence of endogenous processes—fluctuation in attention and motivation, fatigue and boredom—suggest that Drift Rate might vary across experimental trials. Here we show how across-trial variability in Drift Rate can be accounted for by assuming a trial-specific Drift Rate parameter that is governed by a positive-valued distribution. We consider two candidate distributions: the truncated normal distribution and the gamma distribution. For the resulting distributions of first-arrival times, we derive analytical and sampling-based solutions, and implement the models in a Bayesian framework. Recovery studies and an application to a data set comprised of 1469 participants suggest that (1) both mixture distributions yield similar results; (2) all model parameters can be recovered accuRately except for the Drift variance parameter; (3) despite poor recovery, the presence of the Drift variance parameter facilitates accuRate recovery of the remaining parameters; (4) shift, threshold, and Drift mean parameters are correlated.
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Modeling Across-Trial Variability in the Wald Drift Rate Parameter
2018Co-Authors: Helen Steingroever, Dominik Wabersich, Eric-jan WagenmakersAbstract:The shifted-Wald model is a popular analysis tool for one-choice reaction time tasks. In its simplest version, the shifted-Wald model assumes a constant trial-independent Drift Rate parameter. However, the presence of endogenous processes –fluctuation in attention and motivation, fatigue and boredom– suggest that Drift Rate might vary across experimental trials. Here we show how across-trial variability in Drift Rate can be accounted for byassuming a trial-specific Drift Rate parameter that is governed by a positive valued distribution.
