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

Passive Filters01:27

Passive Filters

1.0K
Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
1.0K
Active Filters01:25

Active Filters

1.3K
Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
1.3K
What are Estimates?01:06

What are Estimates?

8.9K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
8.9K
Estimation of k and VD of Aminoglycosides01:20

Estimation of k and VD of Aminoglycosides

252
Aminoglycosides are a class of antibiotics used to treat various bacterial infections. Clinicians must determine the elimination rate constant (k) and volume of distribution (VD) to optimize therapeutic efficacy and minimize toxicity. The k value represents the rate at which the drug is removed from the body, and the VD reflects the degree to which the drug distributes into body tissues. Accurately estimating these parameters allows healthcare professionals to tailor drug dosing to individual...
252
Equation of Motion: General Plane motion01:22

Equation of Motion: General Plane motion

590
In the context of a rigid body's movement within a general plane, it is important to understand that this motion is typically triggered by external forces or couple moments exerted onto it. This principle can be explained through Newton's second law, which stipulates the translational motion of the body's center of mass along each axis.
Moreover, the body's center of mass experiences a rotational effect as a result of these couple moments. This rotation can be articulated as the...
590
Integration by Parts: Indefinite Integrals01:26

Integration by Parts: Indefinite Integrals

215
Integration by parts is a fundamental technique in calculus for evaluating integrals involving the product of two functions. It is particularly useful when direct integration is not feasible. The method is based on the product rule for differentiation, which states that the derivative of a product equals the derivative of the first function times the second, plus the first function times the derivative of the second. By integrating this identity and rearranging terms, the integration by parts...
215

You might also read

Related Articles

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

Sort by
Same author

Gamer in the scanner: Event-related analysis of fMRI activity during retro videogame play guided by automated annotations of game content.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Spinal cord structural and functional architecture and its shared organization with the brain across the adult lifespan.

Nature communications·2026
Same author

Spinal cord involvement and cardiovascular autonomic dysfunction in Parkinson's disease.

Scientific reports·2026
Same author

Spine-prints: Transposing brain fingerprints to the spinal cord.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

CNeuroMod-THINGS, a densely-sampled fMRI dataset for visual neuroscience.

Scientific data·2026
Same author

Kubo-Martin-Schwinger states of path-structured flow in directed brain synaptic networks.

Physical review. E·2026
Same journal

Contemporary pharmacological strategies for acute peripheral facial palsy: a narrative review with clinical decision considerations.

Frontiers in neuroscience·2026
Same journal

Physical bacteria-neuron proximity and early cellular responses: a conceptual perspective.

Frontiers in neuroscience·2026
Same journal

Dynamic changes of gut microbiota during progression of three Alzheimer's disease mice models.

Frontiers in neuroscience·2026
Same journal

Evaluation of an open-face 8-channel transmit 64-channel receive 7T head coil for neuroimaging.

Frontiers in neuroscience·2026
Same journal

Acoustic stimulation in pain management: neurobiological mechanisms and clinical applications-a narrative review.

Frontiers in neuroscience·2026
Same journal

Local brain connectome parameters across the spectrum of clinical cognitive decline.

Frontiers in neuroscience·2026
See all related articles

Related Experiment Video

Updated: Feb 10, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K

Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion.

Basile Pinsard1,2,3, Arnaud Boutin1,4, Julien Doyon1,4

  • 1Unité de Neuroimagerie Fonctionelle, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.

Frontiers in Neuroscience
|May 15, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to correct motion and intensity fluctuations during functional MRI scans. This approach improves the stability of brain activity patterns for better analysis in all populations.

Keywords:
BOLDdenoisingdistortion correctionfMRImotion correctionvisualization

More Related Videos

Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform
06:31

Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform

Published on: August 4, 2022

3.7K
Simultaneous fMRI and Electrophysiology in the Rodent Brain
08:22

Simultaneous fMRI and Electrophysiology in the Rodent Brain

Published on: August 19, 2010

14.0K

Related Experiment Videos

Last Updated: Feb 10, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K
Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform
06:31

Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform

Published on: August 4, 2022

3.7K
Simultaneous fMRI and Electrophysiology in the Rodent Brain
08:22

Simultaneous fMRI and Electrophysiology in the Rodent Brain

Published on: August 19, 2010

14.0K

Area of Science:

  • Neuroimaging
  • Biophysics
  • Signal Processing

Background:

  • Functional MRI (fMRI) is susceptible to subject motion, complicating data analysis.
  • Existing preprocessing methods struggle to fully correct motion and intensity variations.
  • Accurate analysis of fMRI data is crucial for understanding brain function.

Purpose of the Study:

  • To develop an integrated method for correcting motion and low-frequency intensity fluctuations in fMRI data.
  • To improve the accuracy and stability of BOLD signal analysis.
  • To provide a robust framework applicable to various fMRI acquisition techniques.

Main Methods:

  • Developed an integrated, slice-level correction method for motion and intensity bias fields.
  • Utilized an Iterated Extended Kalman Filter for online motion registration.
  • Employed non-parametric fitting for intensity bias field correction.
  • Transformed gray-matter BOLD activity to an anatomical group template space, accounting for distortions.

Main Results:

  • Demonstrated a reduction in motion-explained variance and signal variability compared to conventional methods.
  • Showcased improved preservation of fine-scale activity patterns.
  • Validated the unified framework on simulated and real fMRI data.
  • Confirmed generalization to high-resolution multi-slice fMRI techniques.

Conclusions:

  • The proposed method offers more stable fMRI activity patterns.
  • This enhances the investigation of cerebral information representation in both healthy and clinical populations.
  • The integrated approach mitigates motion artifacts, a significant challenge in fMRI research.