Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Testing a Claim about Population Proportion

Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...

Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

You might also read

Related Articles

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

Sort by

Same author

Causal mediation analysis with one or multiple mediators: A comparative study.

Psychological methods·2026

Same author

NeuroConText: Contrastive learning for neuroscience meta-analysis with rich text representation.

Imaging neuroscience (Cambridge, Mass.)·2026

Same author

Individual Brain Charting: fifth release of high-resolution fMRI data for cognitive mapping.

Scientific data·2026

Same author

Subject fingerprinting and task classification rely on distinct functional connectivity features.

Brain structure & function·2026

Same author

An Interactive Brain Atlas of Knowledge.

bioRxiv : the preprint server for biology·2025

Same author

A non-monotonic code for event probability in the human brain.

Nature communications·2025

Same journal

Segmentation of the parasagittal dura mater on multi-center 3D-FLAIR MRI.

NeuroImage·2026

Same journal

Spatial frequency channels implement a mental ruler in spatial vision.

NeuroImage·2026

Same journal

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

NeuroImage·2026

Same journal

Closed-loop adaptation of transcranial magnetic stimulation intensity with electroencephalography feedback.

NeuroImage·2026

Same journal

Volumetric postmortem MRI of the medial temporal lobe in Alzheimer's disease and related disorders: methodological advances and implications for in vivo biomarker development.

NeuroImage·2026

Same journal

Neural responses to equity and inequity when receiving vicarious rewards for self and charity during adolescence.

NeuroImage·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 3, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Notip: Non-parametric true discovery proportion control for brain imaging.

Alexandre Blain¹, Bertrand Thirion², Pierre Neuvial³

¹Inria, CEA, Université Paris-Saclay, Paris, France; Institut de Mathématiques de Toulouse, UMR 5219, Université de Toulouse, CNRS, UPS, Toulouse, France.

|July 23, 2022

Summary

This summary is machine-generated.

We introduce Notip, a non-parametric method for brain mapping that accurately estimates the proportion of activated voxels within data-derived clusters. This approach offers improved statistical power and detection compared to existing methods in fMRI analysis.

Keywords:

Brain mapping False discovery proportion control Selective inference fMRI

More Related Videos

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Related Experiment Videos

Last Updated: Sep 3, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Area of Science:

Neuroimaging
Statistical inference
Brain mapping

Background:

Cluster-level inference is standard in brain mapping but lacks signal strength information.
Existing methods like All-Resolutions Inference can be conservative due to parametric assumptions.

Purpose of the Study:

To develop a non-parametric method for estimating the true discovery proportion within data-derived clusters.
To address the circularity issue in cluster definition and inference.
To improve statistical power in fMRI analyses.

Main Methods:

Leveraging randomization methods for data adaptation.
Developing Notip (Non-parametric True Discovery Proportion control).
Utilizing post hoc estimation of activated voxel proportions.

Main Results:

Notip provides statistically valid guarantees on the proportion of activated voxels.
Demonstrated substantial gains in detection numbers compared to state-of-the-art methods.
Numerical experiments on 36 fMRI datasets confirmed method's efficacy.

Conclusions:

Notip offers a powerful, non-parametric alternative for cluster-level inference in brain mapping.
The method enhances statistical validity and detection power in fMRI studies.
Further discussion on conditions benefiting Notip is provided.