Cited by 372Functional Brain Connectivity StudiesMeta-analysis and systematic reviewsAdvanced Neuroimaging Techniques and Applications

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ALE meta-analysis workflows via the BrainMap database: Progress towards a probabilistic functional brain atlas

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Laird, Angela R.·2009·Frontiers in Neuroinformatics

DOI 10.3389/neuro.11.023.2009PMC PMC2715269

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Abstract

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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Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150
Self-citation
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies
Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp055 · Cited by 4,060
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data
Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.034 · Cited by 4,033
Imaging Cognition II: An Empirical Review of 275 PET and fMRI Studies
Cabeza, R., & Nyberg, L. (2000) · Journal of Cognitive Neuroscience · doi:10.1162/08989290051137585 · Cited by 3,598
Positron emission tomographic studies of the cortical anatomy of single-word processing
Petersen, S. E., Fox, P. T., Posner, M. I., Mintun, M., & Raichle, M. E. (1988) · Nature · doi:10.1038/331585a0 · Cited by 2,593
Can cognitive processes be inferred from neuroimaging data?
POLDRACK, R. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.12.004 · Cited by 2,249
The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis
Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.21029 · Cited by 2,143

Show all 79 references

Research works printed but not linked: 3

Frishkoff G. A. Dou D. Frank R. LePendu P. Liu H. (2009). Development of Neural Electromagnetic Ontologies (NEMO): representation and integration of event-related brain potentials. Proc. Int. Conf. Biomed. Ontologies (in press).
Schroeter M. L. Raczka K. Neumann J. Yves von Cramon D. (2007). Towards a nosology for frontotemporal lobar degenerations – a meta-analysis involving 267 subjects. Neuroimage 36, 497– 510 17478101
Xiong J. Parsons L. M. Gao J. H. Fox P. T. (1999). Interregional connectivity to primary motor cortex revealed using MRI resting state images. Hum. Brain Mapp. 6, 151– 156 10524607 PMC6873334

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Ray, K. L., Zald, D. H., Bludau, S., Riedel, M. C., Bzdok, D., Yanes, J. A., Falcone, K. E., Amunts, K., Fox, P. T., Eickhoff, S. B., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.072 · Cited by 35
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Sun, J., Hu, X., Huang, X., Liu, Y., Li, K., Li, X., Han, J., Guo, L., Liu, T., & Zhang, J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.142 · Cited by 33
The hippocampal network model: A transdiagnostic metaconnectomic approach
Kotkowski, E., Price, L. R., Fox, P. M., Vanasse, T. J., & Fox, P. T. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.01.002 · Cited by 33
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Liu, W., Peeters, N., Fernández, G., & Kohn, N. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa073 · Cited by 35
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Langner, R., Cieslik, E. C., Behrwind, S. D., Roski, C., Caspers, S., Amunts, K., & Eickhoff, S. B. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0758-0 · Cited by 31
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Kraljević, N., Schaare, H. L., Eickhoff, S. B., Kochunov, P., Yeo, B. T. T., Masouleh, S. K., & Valk, S. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118561 · Cited by 30
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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)
DOI: 10.3389/neuro.11.023.2009
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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