Journal Article

Functional Clusters, Hubs, and Communities in the Cortical Microconnectome

Masanori Shimono and John M. Beggs

in Cerebral Cortex

Volume 25, issue 10, pages 3743-3757
Published in print October 2015 | ISSN: 1047-3211
Published online October 2014 | e-ISSN: 1460-2199 | DOI:

More Like This

Show all results sharing these subjects:

  • Neurology
  • Clinical Neuroscience
  • Neuroscience


Show Summary Details


Although relationships between networks of different scales have been observed in macroscopic brain studies, relationships between structures of different scales in networks of neurons are unknown. To address this, we recorded from up to 500 neurons simultaneously from slice cultures of rodent somatosensory cortex. We then measured directed effective networks with transfer entropy, previously validated in simulated cortical networks. These effective networks enabled us to evaluate distinctive nonrandom structures of connectivity at 2 different scales. We have 4 main findings. First, at the scale of 3–6 neurons (clusters), we found that high numbers of connections occurred significantly more often than expected by chance. Second, the distribution of the number of connections per neuron (degree distribution) had a long tail, indicating that the network contained distinctively high-degree neurons, or hubs. Third, at the scale of tens to hundreds of neurons, we typically found 2–3 significantly large communities. Finally, we demonstrated that communities were relatively more robust than clusters against shuffling of connections. We conclude the microconnectome of the cortex has specific organization at different scales, as revealed by differences in robustness. We suggest that this information will help us to understand how the microconnectome is robust against damage.

Keywords: cluster; community; hub; microconnectome; networks

Journal Article.  11203 words.  Illustrated.

Subjects: Neurology ; Clinical Neuroscience ; Neuroscience

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.