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Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation
Open accessAbstract
The organization of the cerebral cortex into distinct modules may be described along several dimensions, most importantly, structure, connectivity and function. Identification of cortical modules by differences in whole-brain connectivity profiles derived from diffusion tensor imaging or resting state correlations has already been shown. These approaches, however, carry no task-related information. Hence, inference on the functional relevance of the ensuing parcellation remains tentative. Here, we demonstrate, that Meta-Analytic Connectivity Modeling (MACM) allows the delineation of cortical modules based on their whole-brain co-activation pattern across databased neuroimaging results. Using a model free approach, two regions of the medial pre-motor cortex, SMA and pre-SMA were differentiated solely based on their functional connectivity. Assessing the behavioral domain and paradigm class meta-data of the experiments associated with the clusters derived from the co-activation based parcellation moreover allows the identification of their functional characteristics. The ensuing hypotheses about functional differentiation and distinct functional connectivity between pre-SMA and SMA were then explicitly tested and confirmed in independent datasets using functional and resting state fMRI. Co-activation based parcellation thus provides a new perspective for identifying modules of functional connectivity and linking them to functional properties, hereby generating new and subsequently testable hypotheses about the organization of cortical modules.
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“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 Eickhoff et al. 2011
Experimental — accuracy not yet measuredIn the citing paper
“The localization of our (pre)SMA VOI corresponds to the localization of both the anterior and posterior cluster of the SMA identified by functional characterization (Eickhoff et al., 2011), which were associated to cognitive and executive aspects of motor behavior, respectively.”
From Neural network of cognitive emotion regulation—an ALE meta-analysis and MACM analysis (2014) · cites this paper as Eickhoff et al., 2011
In the citing paper
“This procedure should effectively balance inference on reliable areas of activation without generating a bias toward false positives (Laird et al., 2005;Eickhoff et al., 2011).”
From Informatic parcellation of the network involved in the computation of subjective value (2014) · cites this paper as Eickhoff et al., 2011
In the citing paper
“Using a binomial test, Bonferroni-corrected for multiple comparisons, the functional roles of the convergent network as a whole were identified”
From Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy (2012) · cites this paper as Eickhoff et al. 2011
In the citing paper
“These resulting non-parametric p values were thresholded at p < 0.001.”
From Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy (2012) · cites this paper as Eickhoff et al. 2011
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Citations
Cites
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
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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 · cited 5×
“…physiology of correlations in the absence of a structured task remains somewhat elusive, it seems plausible that “resting” state, as a mixture of various cognitive processes, may likewise sample the repertoire of operations brain networks can perform (Buckner and Vincent, 2007; Smith et al., 2009).”
BackgroundResultInfluentialSelf-citationFriston, K. J., Harrison, L., & Penny, W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00202-7 · Cited by 4,583 · cited 1×
“Other approaches such as psychophysiological interactions or Granger causalitymapping are used to identify regions, showing a context-dependent change in their coupling with a particular seed region (Friston et al., 1997; Goebel et al., 2003) under the assumptions of the employed model.”
MethodMapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · cited 2×
“…likely conveying meaningful functional relationships between brain regions are illustrated by the fact that they were reported to widely correspond with both task-state networks (Biswal et al., 1995; Smith et al., 2009) and structural connectivity (Greicius et al., 2009; Hagmann et al., 2008).”
BackgroundA 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 · cited 1×
“In addition, a necessary step toward understanding cortical organization is to relate connectivity-defined modules and functional differentiations to microstructural maps of the human cerebral cortex (Amunts et al., 2007; Eickhoff et al., 2005; Eickhoff et al., 2008b; Zilles et al., 2002).”
BackgroundSelf-citationPsychophysiological and Modulatory Interactions in Neuroimaging
Friston, K. J., Buechel, C., Fink, G. R., Morris, J., Rolls, E., & Dolan, R. J. (1997) · NeuroImage · doi:10.1006/nimg.1997.0291 · Cited by 3,097 · cited 1×
“Other approaches such as psychophysiological interactions or Granger causalitymapping are used to identify regions, showing a context-dependent change in their coupling with a particular seed region (Friston et al., 1997; Goebel et al., 2003) under the assumptions of the employed model.”
MethodCharacterization and propagation of uncertainty in diffusion-weighted MR imaging
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038 · cited 1×
“On these, tractography algorithms may be employed to derive information about the most likely fiber tract direction from particular seed or the course and strength of pathways connecting two different regions of the cortex (Behrens et al., 2003; Ramnani et al., 2004).”
MethodCan 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
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn059 · Cited by 2,175 · cited 2×
“…likely conveying meaningful functional relationships between brain regions are illustrated by the fact that they were reported to widely correspond with both task-state networks (Biswal et al., 1995; Smith et al., 2009) and structural connectivity (Greicius et al., 2009; Hagmann et al., 2008).”
BackgroundEickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009) · Human Brain Mapping · doi:10.1002/hbm.20718 · Cited by 1,924 · cited 2×
“…described co-activation parcellation of the seed region, ALE scores for the MACM analysis of this cluster were compared to a null-distribution that reflects a random spatial association between experiments, but regards the within-experiment distribution of foci as fixed (Eickhoff et al., 2009).”
MethodResultSelf-citation
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Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhx179 · Cited by 3,657
Self-citationThe Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture
Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., Yang, Z., Chu, C., Xie, S., Laird, A. R., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw157 · Cited by 3,047
“…brain region or provide more comprehensive maps of the cerebral cortex (Tzourio-Mazoyer et al. 2002; Desikan et al. 2006; Cohen, Fair, et al. 2008; Cohen, Lombardo, et al. 2008; Eickhoff et al. 2011; Wang et al. 2012; Fan et al. 2014; Wig et al. 2014; Laumann Timothy et al. 2015; Figure 4.”
InfluentialSelf-citationIdentification of a Common Neurobiological Substrate for Mental Illness
Goodkind, M., Eickhoff, S. B., Oathes, D. J., Jiang, Y., Chang, A., Jones-Hagata, L. B., Ortega, B. N., Zaiko, Y. V., Roach, E. L., Korgaonkar, M. S., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.2206 · Cited by 1,404
Self-citationModelling neural correlates of working memory: A coordinate-based meta-analysis
Rottschy, C., Langner, R., Dogan, I., Reetz, K., Laird, A. R., Schulz, J. B., Fox, P. T., & Eickhoff, S. B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.050 · Cited by 951
“Differences between conditions were tested by first performing separate ALE analyses for each condition and computing the voxel-wise difference between the ensuing ALE maps (cf. Eickhoff et al., 2011b).”
Self-citationNeural network of cognitive emotion regulation—an ALE meta-analysis and MACM analysis
Kohn, N., Eickhoff, S. B., Scheller, M., Laird, A. R., Fox, P. T., & Habel, U. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.001 · Cited by 956
“MACM is based on assessing the brain-wise co-activation patterns of a seed region across a large number of data based neuroimaging results (Eickhoff et al., 2011; Laird et al., 2009b).”
BackgroundMethodSelf-citation
Metadata
- Authors
- Eickhoff, S. B., Bzdok, D., Laird, A. R., Roski, C., Caspers, S., Zilles, K., & Fox, P. T.
- Affiliations
- Forschungszentrum Jülich (DE)
- The University of Texas at San Antonio Health Science Center (US)
- Corresponding author
- Eickhoff, Simon B.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2011-08
- Volume
- 57
- Issue
- 3
- Pages
- 938-949
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3129435
- OpenAlex
- W2001483470
- Cited by
- 484
- References
- 60
- Citations by year
- 2026: 20 · 2025: 20 · 2024: 38 · 2023: 22 · 2022: 40 · 2021: 40 · 2020: 27 · 2019: 25 · 2018: 27 · 2017: 41 · 2016: 43 · 2015: 48 · 2014: 34 · 2013: 27 · 2012: 23
- FWCI
- 14.62
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- JuSER (Forschungszentrum Jülich) (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- Human Brain Project (R01-MH074457-01A1)
- Helmholtz Alliance on Systems Biology
- DFG (IRTG 1328)
- Helmholtz Alliance for Mental Health in an Aging Society
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- cortical modules, co-activation patterns, meta-analytic connectivity modeling, whole-brain functional connectivity, pre-supplementary motor area, supplementary motor area, functional parcellation
- MeSH terms
- Algorithms, Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neural Pathways, Cluster Analysis
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