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Related Experiment Video

Updated: May 11, 2026

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

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Published on: March 21, 2019

Networks of task co-activations.

Angela R Laird¹, Simon B Eickhoff, Claudia Rottschy

¹Department of Physics, Florida International University, Miami, FL 33199, USA. alaird@fiu.edu

|May 2, 2013

Summary

This study explores human brain connectomics using neuroimaging data. Researchers analyzed task-based brain activation patterns to understand functional connectivity and brain networks.

Keywords:

BrainMap Co-activations Functional brain networks Functional connectivity Intrinsic connectivity networks Meta-analysis Neuroinformatics Resting state networks Task co-occurrence

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Area of Science:

Neuroimaging Informatics
Cognitive Neuroscience
Connectomics

Background:

Advances in neuroimaging and meta-analysis enable studying task-dependent brain co-activation.
Human brain connectomics research focuses on functional networks across diverse cognitive tasks.

Purpose of the Study:

To review studies using the BrainMap database for brain activation meta-analysis.
To investigate data trends and apply methods like MACM, CPB, and ICA.
To explore functional connectivity of key brain regions and networks.

Main Methods:

Utilized the BrainMap database for meta-analytic connectivity modeling (MACM).
Applied connectivity-based parcellation (CPB) and independent component analysis (ICA).
Analyzed behavioral metadata for functional decoding of brain regions and networks.

Main Results:

Demonstrated applications of MACM, CPB, and ICA to understand functional connectivity.
Provided examples of analyzing the amygdala, default mode network, and visual area V5.
Described methods for local functional decoding using behavioral metadata.

Conclusions:

Co-activation patterns offer insights into brain functional connectivity.
Discussed the relationship between task-based and resting-state connectivity.
Outlined implications for future human brain connectomics research.