The Experts below are selected from a list of 246 Experts worldwide ranked by ideXlab platform
Jakob Heinzle - One of the best experts on this subject based on the ideXlab platform.
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The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades
PLoS computational biology, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the early decision process postulated by the SERIA model is, to a large extent, insensitive to the cue presented in a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (pro- or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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the stochastic early Reaction Inhibition and late action seria model for antisaccades seria a model for errors and Reaction times in the antisaccade task
bioRxiv, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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The Stochastic Early Reaction, Inhibition, and Late Action (SERIA) Model for Antisaccades
2017Co-Authors: Eduardo A Aponte, Klaas E. Stephan, Dario Schoebi, Jakob HeinzleAbstract:Abstract The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades. Author summary One widely replicated finding in schizophrenia research is that patients tend to make more errors in the antisaccade task, a psychometric paradigm in which participants are required to look in the opposite direction of a visual cue. This deficit has been suggested to be an endophenotype of schizophrenia, as first order relatives of patients tend to show similar but milder deficits. Currently, most models applied to experimental findings in this task are limited to fit average Reaction times and error rates. Here, we propose a novel statistical model that fits experimental data from the antisaccade task, beyond summary statistics. The model is inspired by the hypothesis that antisaccades are the result of several competing decision processes that interact nonlinearly with each other. In applying this model to a relatively large experimental data set, we show that mean Reaction times and error rates do not fully reflect the complexity of the processes that are likely to underlie experimental findings. In the future, our model could help to understand the nature of the deficits observed in schizophrenia by providing a statistical tool to study their biological underpinnings.
Eduardo A Aponte - One of the best experts on this subject based on the ideXlab platform.
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The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades
PLoS computational biology, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the early decision process postulated by the SERIA model is, to a large extent, insensitive to the cue presented in a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (pro- or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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the stochastic early Reaction Inhibition and late action seria model for antisaccades seria a model for errors and Reaction times in the antisaccade task
bioRxiv, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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The Stochastic Early Reaction, Inhibition, and Late Action (SERIA) Model for Antisaccades
2017Co-Authors: Eduardo A Aponte, Klaas E. Stephan, Dario Schoebi, Jakob HeinzleAbstract:Abstract The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades. Author summary One widely replicated finding in schizophrenia research is that patients tend to make more errors in the antisaccade task, a psychometric paradigm in which participants are required to look in the opposite direction of a visual cue. This deficit has been suggested to be an endophenotype of schizophrenia, as first order relatives of patients tend to show similar but milder deficits. Currently, most models applied to experimental findings in this task are limited to fit average Reaction times and error rates. Here, we propose a novel statistical model that fits experimental data from the antisaccade task, beyond summary statistics. The model is inspired by the hypothesis that antisaccades are the result of several competing decision processes that interact nonlinearly with each other. In applying this model to a relatively large experimental data set, we show that mean Reaction times and error rates do not fully reflect the complexity of the processes that are likely to underlie experimental findings. In the future, our model could help to understand the nature of the deficits observed in schizophrenia by providing a statistical tool to study their biological underpinnings.
Haim Breitbart - One of the best experts on this subject based on the ideXlab platform.
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Remodeling of the Actin Cytoskeleton During Mammalian Sperm Capacitation
2016Co-Authors: Acrosome Reaction, Gili Cohen, Ephraim Brener, Keren Shternall, Joel Rivlin, Sara Rubinstein, Haim BreitbartAbstract:The sperm acrosome Reaction and penetration of the egg fol-low zona pellucida binding only if the sperm has previously un-dergone the poorly understood maturation process known as capacitation. We demonstrate here that in vitro capacitation of bull, ram, mouse, and human sperm was accompanied by a time-dependent increase in actin polymerization. Induction of the acrosome Reaction in capacitated cells initiated fast F-actin breakdown. Incubation of sperm in media lacking BSA or meth-yl-b-cyclodextrin, Ca21, or NaHCO3, components that are all required for capacitation, prevented actin polymerization as well as capacitation, as assessed by the ability of the cells to undergo the acrosome Reaction. Inhibition of F-actin formation by cytochalasin D blocked sperm capacitation and reduced the in vitro fertilization rate of metaphase II-arrested mouse eggs. It has been suggested that protein tyrosine phosphorylation may represent an important regulatory pathway that is associated with sperm capacitation. We show here that factors known to stimulate sperm protein tyrosine phosphorylation (i.e., NaHCO3, cAMP, epidermal growth factor, H2O2, and sodium vanadate) were able to enhance actin polymerization, whereas Inhibition of tyrosine kinases prevented F-actin formation. These data sug-gest that actin polymerization may represent an important reg-ulatory pathway in with sperm capacitation, whereas F-actin breakdown occurs before the acrosome Reaction. acrosome Reaction, gamete biology, in vitro fertilization, sperm, sperm capacitatio
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remodeling of the actin cytoskeleton during mammalian sperm capacitation and acrosome Reaction
Biology of Reproduction, 2003Co-Authors: Ephraim Brener, Gili Cohen, Keren Shternall, Joel Rivlin, Sara Rubinstein, Haim BreitbartAbstract:The sperm acrosome Reaction and penetration of the egg follow zona pellucida binding only if the sperm has previously undergone the poorly understood maturation process known as capacitation. We demonstrate here that in vitro capacitation of bull, ram, mouse, and human sperm was accompanied by a time-dependent increase in actin polymerization. Induction of the acrosome Reaction in capacitated cells initiated fast F-actin breakdown. Incubation of sperm in media lacking BSA or methyl-b-cyclodextrin, Ca21, or NaHCO3, components that are all required for capacitation, prevented actin polymerization as well as capacitation, as assessed by the ability of the cells to undergo the acrosome Reaction. Inhibition of F-actin formation by cytochalasin D blocked sperm capacitation and reduced the in vitro fertilization rate of metaphase II-arrested mouse eggs. It has been suggested that protein tyrosine phosphorylation may represent an important regulatory pathway that is associated with sperm capacitation. We show here that factors known to stimulate sperm protein tyrosine phosphorylation (i.e., NaHCO3, cAMP, epidermal growth factor, H2O2, and sodium vanadate) were able to enhance actin polymerization, whereas Inhibition of tyrosine kinases prevented F-actin formation. These data suggest that actin polymerization may represent an important regulatory pathway in with sperm capacitation, whereas F-actin breakdown occurs before the acrosome Reaction. acrosome Reaction, gamete biology, in vitro fertilization, sperm, sperm capacitation
Yu Seung Kim - One of the best experts on this subject based on the ideXlab platform.
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Cation–Hydroxide–Water Coadsorption Inhibits the Alkaline Hydrogen Oxidation Reaction
The journal of physical chemistry letters, 2016Co-Authors: Hoon T Chung, Ulises Martinez, Ivana Matanovic, Yu Seung KimAbstract:Rotating disk electrode voltammograms and infrared reflection absorption spectra indicate that the hydrogen oxidation Reaction of platinum in 0.1 M tetramethylammonium hydroxide solution is adversely impacted by time-dependent and potential-driven cation–hydroxide–water coadsorption. Impedance analysis suggests that the hydrogen oxidation Reaction Inhibition is mainly caused by the hydrogen diffusion barrier of the coadsorbed trilayer rather than intuitive catalyst site blocking by the adsorbed cation species. These results give useful insights on how to design ionomeric binders for advanced alkaline membrane fuel cells.
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cation hydroxide water coadsorption inhibits the alkaline hydrogen oxidation Reaction
Journal of Physical Chemistry Letters, 2016Co-Authors: Hoon T Chung, Ulises Martinez, Ivana Matanovic, Yu Seung KimAbstract:Rotating disk electrode voltammograms and infrared reflection absorption spectra indicate that the hydrogen oxidation Reaction of platinum in 0.1 M tetramethylammonium hydroxide solution is adversely impacted by time-dependent and potential-driven cation–hydroxide–water coadsorption. Impedance analysis suggests that the hydrogen oxidation Reaction Inhibition is mainly caused by the hydrogen diffusion barrier of the coadsorbed trilayer rather than intuitive catalyst site blocking by the adsorbed cation species. These results give useful insights on how to design ionomeric binders for advanced alkaline membrane fuel cells.
Klaas E. Stephan - One of the best experts on this subject based on the ideXlab platform.
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The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades
PLoS computational biology, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the early decision process postulated by the SERIA model is, to a large extent, insensitive to the cue presented in a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (pro- or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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the stochastic early Reaction Inhibition and late action seria model for antisaccades seria a model for errors and Reaction times in the antisaccade task
bioRxiv, 2017Co-Authors: Eduardo A Aponte, Dario Schobi, Klaas E. Stephan, Jakob HeinzleAbstract:The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades.
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The Stochastic Early Reaction, Inhibition, and Late Action (SERIA) Model for Antisaccades
2017Co-Authors: Eduardo A Aponte, Klaas E. Stephan, Dario Schoebi, Jakob HeinzleAbstract:Abstract The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and Reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and Reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in Reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower Inhibition and the probability of generating late voluntary prosaccades. Author summary One widely replicated finding in schizophrenia research is that patients tend to make more errors in the antisaccade task, a psychometric paradigm in which participants are required to look in the opposite direction of a visual cue. This deficit has been suggested to be an endophenotype of schizophrenia, as first order relatives of patients tend to show similar but milder deficits. Currently, most models applied to experimental findings in this task are limited to fit average Reaction times and error rates. Here, we propose a novel statistical model that fits experimental data from the antisaccade task, beyond summary statistics. The model is inspired by the hypothesis that antisaccades are the result of several competing decision processes that interact nonlinearly with each other. In applying this model to a relatively large experimental data set, we show that mean Reaction times and error rates do not fully reflect the complexity of the processes that are likely to underlie experimental findings. In the future, our model could help to understand the nature of the deficits observed in schizophrenia by providing a statistical tool to study their biological underpinnings.
