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: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

331
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
331

You might also read

Related Articles

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

Sort by
Same author

Prospective Head Motion Correction in T1- and T2-Weighted Long Echo Train Sequences Using Servo Navigation.

Magnetic resonance in medicine·2026
Same author

Direct MRI of collagen.

eLife·2026
Same author

The sinking dynamics of a solid intruder in concentrated cornstarch suspensions studied using ultra-fast magnetic resonance imaging.

Soft matter·2026
Same author

Core-shell particles with tailored magnetic susceptibility for signal-efficient magnetic resonance imaging of granular systems.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same author

Autonomy for MRI Field Cameras: Synchronization, Self-Calibration, and Sequence Detection.

Magnetic resonance in medicine·2026
Same author

Evaluating the quality of brainstem ROI registration using structural and diffusion MRI.

Frontiers in neuroscience·2026

Related Experiment Video

Updated: Mar 12, 2026

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.9K

The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data.

Lars Kasper1, Steffen Bollmann2, Andreea O Diaconescu3

  • 1Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Wilfriedstrasse 6, 8032 Zurich, Switzerland; Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Gloriastrasse 35, 8092 Zurich, Switzerland.

Journal of Neuroscience Methods
|November 12, 2016
PubMed
Summary

Physiological noise correction in fMRI is now automated and accessible with the PhysIO Toolbox. This open-source tool standardizes preprocessing, improving data quality for large studies.

Keywords:
Heart ratePhysiological noise correctionRETROICORRVHRCORRespiratory volumeSPM toolboxfMRIfMRI preprocessing

More Related Videos

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
07:05

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Published on: August 24, 2017

11.5K
Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

1.8K

Related Experiment Videos

Last Updated: Mar 12, 2026

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.9K
A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
07:05

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Published on: August 24, 2017

11.5K
Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

1.8K

Area of Science:

  • Neuroimaging
  • Biomedical Engineering

Background:

  • Physiological noise is a major confound in fMRI data.
  • Current correction methods face challenges with data quality, format standardization, and automation.

Purpose of the Study:

  • Introduce the PhysIO Toolbox for automated physiological noise correction in fMRI.
  • Provide a flexible and robust solution for preprocessing physiological recordings.

Main Methods:

  • The PhysIO Toolbox preprocesses physiological recordings (ECG, respiration).
  • It implements noise models like RETROICOR and RVT/HRV.
  • The toolbox automates steps from data import to GLM regressor creation.

Main Results:

  • Demonstrated functionality across diverse fMRI datasets (vendors, devices, field strengths, populations).
  • Achieved automated physiological noise correction and performance evaluation in a group study (N=35).
  • Outperformed vendor-provided peak detection for physiological cycles, enhancing modeling robustness.

Conclusions:

  • PhysIO Toolbox makes physiological noise correction an accessible fMRI preprocessing step.
  • Its platform-independent, open-source, and modular design facilitates widespread adoption.
  • Offers integrated, automated, and flexible physiological noise correction.