Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

888
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
888
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

712
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
712
Two-Compartment Open Model: Overview01:05

Two-Compartment Open Model: Overview

752
Multicompartmental models are crucial tools in pharmacokinetics, providing a framework to understand how drugs move within the body. The two-compartment model is a crucial subtype, segmenting the body into central and peripheral compartments. The central compartment represents areas with high blood flow, such as plasma and highly perfused organs like the kidneys and liver, while the peripheral compartment signifies tissues with lower blood flow, like adipose tissue and muscle tissue.
The...
752
Three-Compartment Open Model01:06

Three-Compartment Open Model

1.2K
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
1.2K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

333
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
333
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

727
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
727

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Modeling Rare Events and Nonmonotone Nonignorable Missingness of Time-Varying Outcomes and Predictors in Binary Time-Series Daily Diary Data: A Bayesian Selection Model.

Psychometrika·2026
Same author

An Iterative GLMM-XGBoost Algorithm with Group-Aware Conditional Permutation Importance for Explaining Multilevel Item Response Data.

Psychometrika·2026
Same author

Mixed-Effects XGBoost with Group-Aware Permutation Importance and Cross-Validation for Multilevel Cross-Classified Continuous Outcomes.

Psychometrika·2026
Same author

Moderate-severe traumatic brain injury disrupts core mechanisms of online language processing and use.

Cortex; a journal devoted to the study of the nervous system and behavior·2026
Same author

A nap consolidates generalized perceptual learning.

Frontiers in sleep·2025
Same author

Is that true? Examining the effects of question wording on the effectiveness of political fact checks.

Journal of experimental psychology. Applied·2025
Same journal

Intranasal stromal cell-derived factor-1α mitigates parkinsonian deficits via dual modulation of neuroinflammation and gut microbiota in MPTP-induced models.

Brain research·2026
Same journal

Emotions, the amygdala, and the right hemisphere.

Brain research·2026
Same journal

Electroacupuncture treatment enhances hippocampal growth hormone level and restores mitochondrial function in vascular dementia rats.

Brain research·2026
Same journal

Effects of transcutaneous auricular nerve stimulation on thalamic relay: A randomized brain imaging study in chronic low back pain patients.

Brain research·2026
Same journal

Adaptive reconfiguration of prefrontal networks during prolonged cognitive interference: Evidence from fNIRS.

Brain research·2026
Same journal

Horizontal image compression significantly impairs human face identity recognition.

Brain research·2026
See all related articles

Related Experiment Video

Updated: Apr 30, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

9.9K

Modeling spatio-temporal patterns in intensive binary time series eye-tracking data using Generalized Additive Mixed

Sarah Brown-Schmidt1, Sun-Joo Cho1, Kimberly M Fenn2

  • 1Vanderbilt University, Department of Psychology & Human Development, United States.

Brain Research
|February 20, 2025
PubMed
Summary
This summary is machine-generated.

Generalized Additive Mixed Models (GAMM) analyze intensive binary time-series eye-tracking data. This method reveals how speech perception dynamics and spatial relationships influence fixation probabilities over time.

Keywords:
Dynamic GLMMSpatio-temporal GAMMSpeech perceptionVisual-world eye-tracking

More Related Videos

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

173
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

682

Related Experiment Videos

Last Updated: Apr 30, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

9.9K
Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

173
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

682

Area of Science:

  • Psycholinguistics
  • Cognitive Science
  • Computational Linguistics

Background:

  • Eye-tracking studies often generate intensive binary time-series data.
  • Analyzing such data requires methods that can handle autoregressive patterns and complex temporal dependencies.
  • Existing methods may not fully capture the dynamic interplay between spatial information and time during language processing.

Purpose of the Study:

  • To introduce and demonstrate Generalized Additive Mixed Models (GAMM) for analyzing intensive binary time-series eye-tracking data.
  • To illustrate how spatio-temporal GAMM can reveal time-varying effects in speech perception.
  • To showcase a novel technique for modeling complex spatial-temporal relationships in visual-world eye-tracking.

Main Methods:

  • Application of spatio-temporal Generalized Additive Mixed Models (GAMM).
  • Analysis of intensive binary time-series eye-tracking data during speech perception.
  • Modeling of crossed random effects (by person and item) and autoregressive patterns.

Main Results:

  • Identified that fixed condition effects and temporal contingencies vary over time during speech perception.
  • Demonstrated that spatial relationships between fixation points and referents modulate target fixation probability.
  • Showed that the influence of spatial relationships on fixations changes dynamically as speech unfolds.

Conclusions:

  • GAMM provides a powerful framework for analyzing complex eye-tracking data.
  • This technique allows for the modeling of dynamic, time-varying effects in language processing.
  • The approach enables new research questions regarding the interplay of space, time, and language comprehension.