Related Experiment Video
Updated: Aug 29, 2025
09:27
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
Published on: October 13, 2018
10.1K
Change of Variable-Foreperiod Effects within an Experiment: A Bayesian Modeling Approach
Tianfang Han1, Robert W Proctor1
1Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA.
Journal of Cognition
|September 8, 2022
Summary
The sequential foreperiod effect, influenced by event files, shows asymmetry over time. Findings support multiple trace theory, except in short foreperiod conditions where repetition priming dominates.
Area of Science:
- Cognitive Psychology
- Neuroscience
- Human Behavior
Background:
- The Binding and Retrieval in Action Control (BRAC) framework suggests trial element repetition triggers memory retrieval.
- The sequential foreperiod (SFP) effect arises from retrieving temporal relations stored in event files.
Purpose of the Study:
- To investigate the temporal dynamics of the SFP effect using Bayesian modeling.
- To test predictions from multiple trace theory and repetition priming accounts.
Main Methods:
- Bayesian modeling of data from four experiments.
- Analysis of sequential foreperiod effects under different temporal distributions.
Main Results:
- Experiments 1, 3, and 4 supported multiple trace theory with asymmetric SFP effects.
- Experiment 2, with very short foreperiods, supported the repetition priming account.
- Asymmetry developed gradually in non-aging distributions (Exp. 1, 3) but was immediate in uniform distributions (Exp. 4).
Conclusions:
- The SFP effect's temporal dynamics vary depending on foreperiod distribution.
- Findings refine temporal preparation models and the BRAC framework.
Related Concept Videos
01:13Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
117
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
117
01:14Parametric Survival Analysis: Weibull and Exponential Methods
556
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
556
01:13Randomized Experiments
7.1K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
7.1K
01:11Variability: Analysis
181
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
181
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
193
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
193
01:16Experimental Designs
11.7K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
11.7K