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

Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

428
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
428
Laminar Flow01:27

Laminar Flow

2.3K
Laminar flow represents a smooth, orderly fluid motion where particles move along parallel paths, resulting in minimal mixing between layers. Streamlined particle paths characterize this flow regime and occur under conditions where viscous forces dominate over inertial forces. The distinction between laminar, transitional, and turbulent flow is primarily determined by the Reynolds number, a dimensionless quantity calculated as:
2.3K
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

530
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
530
Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

11.2K
Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the...
11.2K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

507
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
507
Steady, Laminar Flow Between Parallel Plates01:17

Steady, Laminar Flow Between Parallel Plates

892
Understanding steady, laminar flow between parallel plates is essential for analyzing and designing flow in narrow rectangular channels, commonly found in various water conveyance and drainage systems. The Navier-Stokes equations govern fluid motion and are generally challenging to solve due to their nonlinearity. However, simplifications are possible in certain cases, like the steady laminar flow between parallel plates. For this scenario, we assume steady, incompressible, laminar flow.
892

You might also read

Related Articles

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

Sort by
Same author

The Spatiotemporal Neural Dynamics of Intersensory Attention Capture of Salient Stimuli: A Large-Scale Auditory-Visual Modeling Study.

Frontiers in computational neuroscience·2022
Same author

Identifying suicidal young adults.

Nature human behaviour·2019
Same author

Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation.

Brain connectivity·2018
Same author

Chronometry on Spike-LFP Responses Reveals the Functional Neural Circuitry of Early Auditory Cortex Underlying Sound Processing and Discrimination.

eNeuro·2018
Same author

Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

Journal of cognitive neuroscience·2017
Same author

The Functional Overlap of Executive Control and Language Processing in Bilinguals.

Bilingualism (Cambridge, England)·2016
Same journal

Lifespan Trajectories of the Brain's Functional Complexity Characterized by Multiscale Sample Entropy.

NeuroImage·2026
Same journal

Pleasant fragrance modulates dyadic social sharing of positive emotion: Sharer-centered socioemotional enhancement effect and its neural couplings.

NeuroImage·2026
Same journal

Altered Functional Hierarchical and Sequential Organization in Individuals with Schizophrenia during Auditory Processing.

NeuroImage·2026
Same journal

Mechanical Deformation Explains Distinct Neuroimaging Patterns and Etiologies in Brain Trauma.

NeuroImage·2026
Same journal

Ventral striatum temporal interference brain stimulation enhances the reward-positivity event-related potential and reduces anxiety.

NeuroImage·2026
Same journal

NeuroHarm‑Kit: An Open‑Source Toolbox for Benchmarking Deep‑Learning Harmonization of Multi‑Site T1‑Weighted MRI.

NeuroImage·2026
See all related articles

Related Experiment Video

Updated: Feb 14, 2026

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
08:06

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

Published on: June 18, 2018

7.7K

Simulating laminar neuroimaging data for a visual delayed match-to-sample task.

Paul T Corbitt1, Antonio Ulloa2, Barry Horwitz1

  • 1Brain Imaging & Modeling Section, National Institute on Deafness & Other Communication Disorders, National Institutes of Health, Bethesda, MD, USA.

Neuroimage
|February 25, 2018
PubMed
Summary
This summary is machine-generated.

Laminar neuroimaging offers a new window into the human brain. Biologically realistic simulations help interpret layer-specific fMRI data, revealing finer details of neural activity and connectivity.

Keywords:
Computational modelingCortical layersHigh-resolution fMRIHumanLaminar fMRINeural mass models

More Related Videos

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K
Revised and Neuroimaging-Compatible Versions of the Dual Task Screen
07:52

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen

Published on: October 5, 2020

4.0K

Related Experiment Videos

Last Updated: Feb 14, 2026

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
08:06

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

Published on: June 18, 2018

7.7K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K
Revised and Neuroimaging-Compatible Versions of the Dual Task Screen
07:52

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen

Published on: October 5, 2020

4.0K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Neuroimaging

Background:

  • Invasive studies in mammals reveal layer-dependent neural processing.
  • Noninvasive functional neuroimaging (fMRI) can potentially resolve cortical layers in humans.
  • Human fMRI data is noisy, necessitating computational models for interpretation.

Purpose of the Study:

  • To upgrade a neural model for simulating laminar-specific fMRI.
  • To investigate the potential of laminar neuroimaging for understanding human brain function.
  • To relate simulated neural activity to observed fMRI signals.

Main Methods:

  • Developed a laminar-based neural unit with distinct cell populations across cortical layers.
  • Simulated neural activity and translated it into local field potential-like data.
  • Generated conventional and laminar fMRI data using a modified hemodynamic model.

Main Results:

  • The laminar model replicated existing model findings and revealed finer structures in fMRI activity and connectivity.
  • Laminar differences in neural activity magnitude were observed and reflected in simulated fMRI.
  • Task vs. control conditions showed distinct fMRI signals and interregional laminar connectivity patterns.

Conclusions:

  • Multi-layer computational models can aid in interpreting layer-specific fMRI.
  • Laminar fMRI holds promise for unique insights into human neuroscience.
  • Further adoption of laminar fMRI could advance our understanding of brain function.