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ALE meta-analysis workflows via the BrainMap database: Progress towards a probabilistic functional brain atlas
Open accessAbstract
With the ever-increasing number of studies in human functional brain mapping, an abundance of data has been generated that is ready to be synthesized and modeled on a large scale. The BrainMap database archives peak coordinates from published neuroimaging studies, along with the corresponding metadata that summarize the experimental design. BrainMap was designed to facilitate quantitative meta-analysis of neuroimaging results reported in the literature and supports the use of the activation likelihood estimation (ALE) method. In this paper, we present a discussion of the potential analyses that are possible using the BrainMap database and coordinate-based ALE meta-analyses, along with some examples of how these tools can be applied to create a probabilistic atlas and ontological system of describing function-structure correspondences.
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“previous approaches have relied heavily on researchers’ manual efforts (e.g., 7,8)”
From Large-scale automated synthesis of human functional neuroimaging data. (2011) · cites this paper as [8]
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Large-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686
The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture
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“Further filtering and meta-analysis of the experiments was carried out using BrainMap's software applications (Laird et al., 2009), as described below.”
MethodSelf-citationActivation Likelihood Estimation meta-analysis revisited
Eickhoff, S., Bzdok, D., Laird, A., Kurth, F., & Fox, P. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.017 · Cited by 1,448
Self-citation
Metadata
- Authors
- Laird, A. R.
- Affiliations
- The University of Texas at San Antonio Health Science Center (US)
- Corresponding author
- Laird, Angela R.
- ORCID
- Laird, Angela R.
- Venue
- Frontiers in Neuroinformatics
- Publisher
- Frontiers Media SA
- Published
- 2009
- Volume
- 3
- Pages
- 23-23
- ISSN
- 1662-5196 (ISSN-L)
- PMC
- PMC2715269
- OpenAlex
- W1979958927
- Cited by
- 372
- References
- 79
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 17 · 2023: 23 · 2022: 20 · 2021: 22 · 2020: 29 · 2019: 17 · 2018: 26 · 2017: 15 · 2016: 25 · 2015: 26 · 2014: 29 · 2013: 28 · 2012: 29
- FWCI
- 10.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neuroinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- RWTH Publications (RWTH Aachen) (submittedVersion, other-oa)
- Funders
- National Institutes of Health (5r01mh084812-03)
- National Institute of Mental Health (R01‐MH084812, R01MH074457, MH084812, MH074457)
- National Institute on Deafness and Other Communication Disorders (F32DC009116)
- National Institute of Neurological Disorders and Stroke (T35NS051166)
- National Center for Research Resources (U24RR021992, RR021992)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- activation likelihood estimation, ontological systems
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