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Peer-reviewedCC BY

Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function

  • Jingnan Du1,2
  • Lauren M. DiNicola1,2
  • Peter A. Angeli1,2
  • Noam Saadon‐Grosman1,2
  • Wendy Sun1,2
  • Stéphanie Kaiser1,2
  • Joanna Ladopoulou1,2
  • Aihuiping Xue3
  • B.T. Thomas Yeo3
  • Mark C. Eldaief4
  • Randy L. Buckner5,4,1,2
5 affiliations
  1. 1Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
  2. 2Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 0238, USA
  3. 3Centre for Sleep & Cognition & Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
  4. 4Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
  5. 5Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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Abstract

The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.

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Cite

BibTeXRIS
BibTeX
@article{du2026withinindividual,
  title = {{Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function}},
  author = {Jingnan Du and Lauren M. DiNicola and Peter A. Angeli and Noam Saadon‐Grosman and Wendy Sun and Stéphanie Kaiser and Joanna Ladopoulou and Aihuiping Xue and B.T. Thomas Yeo and Mark C. Eldaief and Randy L. Buckner},
  year = {2026},
  month = jun,
  doi = {10.21428/8e6ba8ef.7dba6cc4},
  url = {https://doi.org/10.21428/8e6ba8ef.7dba6cc4},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function
AU  - Jingnan Du
AU  - Lauren M. DiNicola
AU  - Peter A. Angeli
AU  - Noam Saadon‐Grosman
AU  - Wendy Sun
AU  - Stéphanie Kaiser
AU  - Joanna Ladopoulou
AU  - Aihuiping Xue
AU  - B.T. Thomas Yeo
AU  - Mark C. Eldaief
AU  - Randy L. Buckner
PY  - 2026
DA  - 2026/06/15
DO  - 10.21428/8e6ba8ef.7dba6cc4
UR  - https://doi.org/10.21428/8e6ba8ef.7dba6cc4
AB  - The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.
ER  -