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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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Cites
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Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
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MethodSelf-citationPolymodal Motion Processing in Posterior Parietal and Premotor Cortex
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“In the widely used Dynamic Causal Modeling (DCM) and Structural Equation Modeling (SEM) approaches, this is assessed by taking an explicit network perspective and modeling the interactions between regions as a function of the experimental context (Buchel and Friston, 1997; Stephan et al., 2007).”
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Luppino, G., Matelli, M., Camarda, R., & Rizzolatti, G. (1993) · The Journal of Comparative Neurology · doi:10.1002/cne.903380109 · Cited by 795 · cited 2×
“Supporting this view, connectivity tracing in non-human primates revealed that the preSMA receives afferences from the inferior parietal lobule (Luppino et al., 1993) and the prefrontal cortex.”
BackgroundFunctional connectivity of the insula in the resting brain
Cauda, F., D'Agata, F., Sacco, K., Duca, S., Geminiani, G., & Vercelli, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.049 · Cited by 793 · cited 2×
“Approaches investigating cortical sub-specialization capitalized on this type of inter-regional connectivity, such as for the successful parcellation of the premotor cortex (Kim et al., 2010), insular cortex (Cauda et al., 2011), and thalamus (Zhang et al., 2008).”
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Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex
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“Following earlier reports that cortical modules may be defined by differences in anatomical connectivity (Johansen-Berg et al., 2004; Klein et al., 2007; Tomassini et al., 2007) or resting state correlations (Kim et al.”
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Brodmann, K. (1909) · Cited by 705
Detection of functional connectivity using temporal correlations in MR images
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“The latter correlate regional BOLD signal changes in order to quantify the degree of functional connectivity between them or identify regions that correlate with a particular seed (Hampson et al., 2002; Ramnani et al., 2004; Xiong et al., 1999).”
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“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.”
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Laird, A. R., Eickhoff, S. B., Li, K., Robin, D. A., Glahn, D. C., & Fox, P. T. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.4004-09.2009 · Cited by 561 · cited 7×
“Analysis of the behavioral domain and paradigm class meta-data (Laird et al., 2009a) moreover allowed the delineation of functional characteristics for the ensuing cortical modules.”
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“Based on these observations and functional activation studies, the SMA has been implicated in executive aspects of motor control, e.g. movement initiation (Chouinard and Paus, 2006; Cunnington et al., 2002; Eickhoff et al., 2008a; Picard and Strick, 1996).”
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BackgroundConnectivity-Based Parcellation of Broca's Area
Anwander, A., Tittgemeyer, M., von Cramon, D., Friederici, A., & Knosche, T. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhk034 · Cited by 531 · cited 1×
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BackgroundUnrest at rest: Default activity and spontaneous network correlations
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BackgroundSelf-citationIntrinsic functional relations between human cerebral cortex and thalamus
Zhang, D., Snyder, A. Z., Fox, M. D., Sansbury, M. W., Shimony, J. S., & Raichle, M. E. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90463.2008 · Cited by 437 · cited 2×
“Approaches investigating cortical sub-specialization capitalized on this type of inter-regional connectivity, such as for the successful parcellation of the premotor cortex (Kim et al., 2010), insular cortex (Cauda et al., 2011), and thalamus (Zhang et al., 2008).”
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Laird, A. R. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.023.2009 · Cited by 372
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“DTI, resting state analyses, and MACM each focus on a different aspects of connectivity, and we therefore predict that in spite of their good convergence, each capture different features of cortical organization (Eickhoff et al., 2010; Honey et al., 2007; Ramnani et al., 2004).”
BackgroundSelf-citationThe Primary Motor and Premotor Areas of the Human Cerebral Cortex
Chouinard, P. A., & Paus, T. (2006) · The Neuroscientist · doi:10.1177/1073858405284255 · Cited by 348 · cited 2×
“Based on these observations and functional activation studies, the SMA has been implicated in executive aspects of motor control, e.g. movement initiation (Chouinard and Paus, 2006; Cunnington et al., 2002; Eickhoff et al., 2008a; Picard and Strick, 1996).”
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“…earlier reports that cortical modules may be defined by differences in anatomical connectivity (Johansen-Berg et al., 2004; Klein et al., 2007; Tomassini et al., 2007) or resting state correlations (Kim et al., 2010) we demonstrated that SMA and pre-SMA may be distinguished by amodel-free…”
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Riecker, A., Mathiak, K., Wildgruber, D., Erb, M., Hertrich, I., Grodd, W., & Ackermann, H. (2005) · Neurology · doi:10.1212/01.wnl.0000152156.90779.89 · Cited by 327 · cited 2×
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BackgroundPrefrontal involvement in imitation learning of hand actions: Effects of practice and expertise
Vogt, S., Buccino, G., Wohlschläger, A. M., Canessa, N., Shah, N. J., Zilles, K., Eickhoff, S. B., Freund, H., Rizzolatti, G., & Fink, G. R. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.005 · Cited by 300 · cited 1×
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Friston, K. J., Frith, C., Fletcher, P. C., Liddle, P. F., & Frackowiak, R. S. J. (1996) · Cerebral Cortex · doi:10.1093/cercor/6.2.156 · Cited by 276
Quantitative Analysis of Cyto- and Receptor Architecture of the Human Brain
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“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-citationNew approaches for exploring anatomical and functional connectivity in the human brain
Ramnani, N., Behrens, T. E. J., Penny, W. D., & Matthews, P. M. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.02.004 · Cited by 230 · cited 4×
“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).”
BackgroundMethodInfluentialCytoarchitecture of the cerebral cortex—More than localization
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“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-citationDynamic causal models of neural system dynamics: current state and future extensions
Stephan, K. E., Harrison, L. M., Kiebel, S. J., Olivier David, A., Penny, W. D., & Friston, K. J. (2007) · Journal of Biosciences · doi:10.1007/s12038-007-0012-5 · Cited by 222 · cited 1×
“In the widely used Dynamic Causal Modeling (DCM) and Structural Equation Modeling (SEM) approaches, this is assessed by taking an explicit network perspective and modeling the interactions between regions as a function of the experimental context (Buchel and Friston, 1997; Stephan et al., 2007).”
MethodKlein, J. C., Behrens, T. E. J., Robson, M. D., Mackay, C. E., Higham, D. J., & Johansen‐Berg, H. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.08.022 · Cited by 189 · cited 4×
“Following earlier reports that cortical modules may be defined by differences in anatomical connectivity (Johansen-Berg et al., 2004; Klein et al., 2007; Tomassini et al., 2007) or resting state correlations (Kim et al., 2010) we demonstrated that SMA and pre-SMA may be distinguished by amodel-free…”
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Charron, S., & Koechlin, É. (2010) · Science · doi:10.1126/science.1183614 · Cited by 186 · cited 2×
“, a functional differentiation between two regions (Reddy and Kanwisher, 2006) or a dichotomy between the neural correlates of two processes (Charron and Koechlin, 2010).”
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“, a functional differentiation between two regions (Reddy and Kanwisher, 2006) or a dichotomy between the neural correlates of two processes (Charron and Koechlin, 2010).”
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“…that diffusion-based tractography does not provide information about anatomical connectivity sensu stricto, i.e. axonal connectivity as revealed by tracer studies in macaques (Pons and Kaas, 1985), but can merely assess the presence and strength of macroanatomical fiber bundles between regions.”
BackgroundJakobs, O., Wang, L. E., Dafotakis, M., Grefkes, C., Zilles, K., & Eickhoff, S. B. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.065 · Cited by 117 · cited 4×
“We then assessed whether the two original regions could be recovered in a model-free analysis from this merged, i.e., single, VOI based on similarities between co-activation patterns of the individual seed voxels across neuroimaging experiments.”
BackgroundMethodInfluentialSelf-citationOrganizational Principles of Human Visual Cortex Revealed by Receptor Mapping
Eickhoff, S. B., Rottschy, C., Kujovic, M., Palomero‐Gallagher, N., & Zilles, K. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn024 · Cited by 71 · cited 2×
“Based on these observations and functional activation studies, the SMA has been implicated in executive aspects of motor control, e.g. movement initiation (Chouinard and Paus, 2006; Cunnington et al., 2002; Eickhoff et al., 2008a; Picard and Strick, 1996).”
BackgroundSelf-citationLaminar distribution and co-distribution of neurotransmitter receptors in early human visual cortex
Eickhoff, S. B., Rottschy, C., & Zilles, K. (2007) · Brain Structure and Function · doi:10.1007/s00429-007-0156-y · Cited by 59 · cited 2×
“Sets of voxels that feature similar brain-wide coactivation profiles were identified by hierarchical cluster analysis (Eickhoff et al., 2007; Timm, 2002).”
MethodSelf-citationEickhoff, S. B., Dafotakis, M., Grefkes, C., Shah, N. J., Zilles, K., & Piza‐Katzer, H. (2008) · Experimental Neurology · doi:10.1016/j.expneurol.2008.03.025 · Cited by 43 · cited 2×
“Based on these observations and functional activation studies, the SMA has been implicated in executive aspects of motor control, e.g. movement initiation (Chouinard and Paus, 2006; Cunnington et al., 2002; Eickhoff et al., 2008a; Picard and Strick, 1996).”
BackgroundSelf-citationNuding, S. C., Segers, L. S., Baekey, D. M., Dick, T. E., Solomon, I. C., Shannon, R., Morris, K. F., & Lindsey, B. G. (2009) · Journal of Neurophysiology · doi:10.1152/jn.91305.2008 · Cited by 32 · cited 2×
“It thus summarizes any analysis that assesses correlations among brain signals without the explicit modeling of the underlying networks (as in effective connectivity), ranging from spike train correlations (Nuding et al., 2009) to EEG coherence (Gross et al., 2001) and various fMRI basedmethods.”
BackgroundRizzolatti, G., & Wolpert, D. M. (2005) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2005.10.018 · Cited by 24
Xiong (1999) · doi:10.1002/(sici)1097-0193(1999)8:2/3
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- Vogt, 1919, Allgemeinere Ergebnisse unserer Hirnforschung, J. Psychol. Neurol., 25, 279
Cited by
Sorted by citations
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 3,083
“…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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