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Related Experiment Video

Updated: May 12, 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

NeuroStream: an interactive platform for exploratory visualization and harmonization of multicohort brain MRI data.

Myeongji Cho¹, Byung Soo Park¹, Hye Ryeong Nam¹

¹Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju-si 28159, Republic of Korea.

Bioinformatics Advances

|May 11, 2026

Summary

NeuroStream offers interactive visualization and harmonization for multicohort brain MRI data, simplifying batch effect identification and preprocessing assessment for researchers. This tool enhances the analysis of large-scale neuroimaging studies by integrating exploration and correction.

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Area of Science:

Neuroimaging and computational neuroscience.

Background:

Large-scale neuroimaging studies integrate multicohort brain MRI data, necessitating tools for batch effect identification and harmonization.
Existing visualization tools are often cohort-specific, static, or separate harmonization from data exploration.

Purpose of the Study:

To introduce NeuroStream, an interactive application for real-time visualization and harmonization of multicohort brain MRI quantitative data.
To enable exploration of quantitative imaging features alongside demographic and clinical variables.

Main Methods:

NeuroStream utilizes the Streamlit framework for interactive exploration of structural MRI quantitative imaging features.
The platform supports various preprocessing and harmonization techniques, including log transformation, intracranial volume normalization, and ComBat-based batch correction.
It offers principal component analysis, distributional plots, group comparison statistics, and covariate-adjusted regression for site effect evaluation.

Main Results:

NeuroStream facilitates interactive comparison of preprocessing and harmonization options through dynamic visualizations.
The application enables quantitative and visual assessment of cohort-related variability across different preprocessing settings.
Demonstrates intuitive inspection of batch-related variance and harmonization outcomes using example datasets from BICWALZS and KoGES multicohort MRI data.

Conclusions:

NeuroStream provides a unified platform for exploring and harmonizing multicohort brain MRI data.
The tool simplifies the identification and mitigation of batch effects, improving the reliability of large-scale neuroimaging analyses.
It empowers researchers to perform complex data assessment and harmonization without custom scripting.