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

You might also read

Related Articles

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

Sort by

Same author

Adaptive Gaussian graph-spectral filtering for scale-specific connectivity inference.

NeuroImage·2026

Same author

Transcranial acoustoelectric imaging (tABI) of seizure activity in human head model with neuronavigation.

Journal of neural engineering·2026

Same author

Plasma inflammatory markers and brain white matter microstructure in late middle-aged and older adults.

medRxiv : the preprint server for health sciences·2026

Same author

Reduced cortical brain perfusion following COVID-19 infection: impact of COVID-19 severity and relation to memory performance.

Frontiers in human neuroscience·2026

Same author

Analysis of Quantitative Susceptibility Mapping Data for Multi-Site and Multi-Modal Brain Imaging Studies: For Measuring Brain Iron and Its Changes with Age.

Gerontology·2026

Same author

Spatially resolved EEG reveals theta-band network modulation following iTBS in aging and mild cognitive impairment.

Frontiers in human neuroscience·2026

Same journal

Quantitative Susceptibility Mapping MRI with Computer Vision Metrics to Reduce Scan Time for Brain Hemorrhage Assessment.

International journal of imaging systems and technology·2025

Same journal

Radiomic feature reliability of amide proton transfer-weighted MR images acquired with compressed sensing at 3T.

International journal of imaging systems and technology·2024

Same journal

Non-invasive prediction of overall survival time for glioblastoma multiforme patients based on multimodal MRI radiomics.

International journal of imaging systems and technology·2024

Same journal

NOSER: An Algorithm for Solving the Inverse Conductivity Problem.

International journal of imaging systems and technology·2023

Same journal

COVID-19 lung infection segmentation from chest CT images based on CAPA-ResUNet.

International journal of imaging systems and technology·2023

Same journal

Application of a novel T1 retrospective quantification using internal references (T1-REQUIRE) algorithm to derive quantitative T1 relaxation maps of the brain.

International journal of imaging systems and technology·2023

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 11, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

A Study of Long-Term fMRI Reproducibility Using Data-Driven Analysis Methods.

Xiaomu Song¹, Lawrence P Panych², Ying-Hui Chou³

¹Department of Electrical Engineering, School of Engineering, Widener University, Chester, PA 19013.

International Journal of Imaging Systems and Technology

|May 30, 2015

Summary

This summary is machine-generated.

This study investigated long-term functional magnetic resonance imaging (fMRI) reproducibility using different data analysis methods. Wavelet smoothing and support vector machine (SVM) analysis showed moderate to substantial within-subject reproducibility over 1.5 years.

Keywords:

quantitative fMRI reproducibility support vector machine wavelet

More Related Videos

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

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

Related Experiment Videos

Last Updated: Apr 11, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

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

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

Area of Science:

Neuroscience
Medical Imaging
Biostatistics

Background:

Reproducibility of functional magnetic resonance imaging (fMRI) is critical for neuroscience and clinical applications.
Previous studies highlight variability in fMRI activation, often limited by short durations and analysis techniques.
Assessing fMRI reproducibility is complex due to the influence of data analysis methods.

Purpose of the Study:

To investigate long-term fMRI reproducibility focusing on data analysis methods.
To evaluate the impact of spatial smoothing techniques (wavelet-domain Bayesian vs. Gaussian) on reproducibility.
To compare multivariate support vector machine (SVM)-based activation detection with the general linear model (GLM) for reproducibility assessment.

Main Methods:

Long-term fMRI reproducibility study using multisession data from eight healthy adults over 1.5 years.
Evaluation of wavelet-domain Bayesian and Gaussian spatial smoothing techniques.
Comparison of SVM-based and GLM-based methods for identifying active voxels at the group level.
Analysis focused on three motor task-related regions-of-interest (ROIs).

Main Results:

Different spatial smoothing techniques yield varying reproducibility measures.
Wavelet-based spatial smoothing combined with SVM-based activation detection demonstrated good reproducibility.
Moderate to substantial within-subject long-term reproducibility was observed, along with reasonable inter-subject reproducibility.
Short-term reproducibility generally exceeds long-term reproducibility.
High contrast-to-noise ratio in brain regions does not guarantee high reproducibility.

Conclusions:

The choice of spatial smoothing and activation detection methods significantly impacts fMRI reproducibility findings.
Wavelet smoothing and SVM offer a robust combination for assessing long-term fMRI reproducibility.
Findings provide insights for optimizing fMRI study design, implementation, and data interpretation.