Networks of task co-activations
Open accessAbstract
Recent progress in neuroimaging informatics and meta-analytic techniques has enabled a novel domain of human brain connectomics research that focuses on task-dependent co-activation patterns across behavioral tasks and cognitive domains. Here, we review studies utilizing the BrainMap database to investigate data trends in the activation literature using methods such as meta-analytic connectivity modeling (MACM), connectivity-based parcellation (CPB), and independent component analysis (ICA). We give examples of how these methods are being applied to learn more about the functional connectivity of areas such as the amygdala, the default mode network, and visual area V5. Methods for analyzing the behavioral metadata corresponding to regions of interest and to their intrinsically connected networks are described as a tool for local functional decoding. We finally discuss the relation of observed co-activation connectivity results to resting state connectivity patterns, and provide implications for future work in this domain.
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The brain exhibits distinct patterns of activity organization, with segregated yet integrated modules that dynamically interact during rest and task-based activity.
“advancements in the study of structural and functional connectomics have provided substantial evidence of distinct patterns of brain activity organization, with segregated, yet integrated modules that dynamically interact during rest and task-based activity (van den Heuvel et al. 2009; Eickhoff et al. 2011; Laird et al. 2013; Raichle 2015; Margulies et al. 2016; Basile et al. 2022a)”
From Neuroanatomical correlates of peripersonal space: bridging the gap between perception, action, emotion and social cognition (2024) · cites this paper as Laird et al. 2013
The Discovery of ICA-Derived Co-Activation Networks section (page unavailable) describes an intrinsic organization of functional networks with similar topography during rest and tasks. The Comparisons to Resting State Connectivity section (page unavailable) reports both shared core interactions and differences, but says it remains open whether those differences reflect mental-state-dependent interactions or methodological effects. The paper does not establish the claim’s more specific description of segregated yet integrated modules dynamically interacting. (LLM, conf=0.84)
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References 65 · Cited by 168
- Authors
- Laird, A. R., Eickhoff, S. B., Rottschy, C., Bzdok, D., Ray, K. L., & Fox, P. T.
- Affiliations
- Florida International University (US)
- Forschungszentrum Jülich (DE)
- The University of Texas at San Antonio Health Science Center (US)
- Corresponding author
- Laird, Angela R.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 505-514
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3720689
- OpenAlex
- W2096856689
- Cited by
- 168
- References
- 65
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 9 · 2023: 9 · 2022: 17 · 2021: 15 · 2020: 8 · 2019: 14 · 2018: 12 · 2017: 15 · 2016: 21 · 2015: 15 · 2014: 17 · 2013: 6
- FWCI
- 10.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- JuSER (Forschungszentrum Jülich) (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- National Institutes of Mental Health (MH74457, MH084812)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- connectomics, meta-analytic connectivity modeling, connectivity-based parcellation, independent component analysis, functional connectivity, amygdala, default mode network, resting-state functional connectivity
- MeSH terms
- Animals, Brain, Cognition, Humans, Models, Anatomic, Models, Neurological, Nerve Net, Task Performance and Analysis, Meta-Analysis as Topic, Connectome
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