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Peer-reviewedCC BYNature Neuroscience

Strong and localized recurrence controls the dimensionality of neural activity across brain areas

  • David Dahmen1,2
  • Stefano Recanatesi3,4,5
  • Xiaoxuan Jia6,7
  • Gabriel Koch Ocker6,8,9
  • Nilufar Lahiji10,11,6
  • Simon Musall10,12,11,6
  • Luke Campagnola6
  • Stephanie C. Seeman6,13,2
  • Tim Jarsky6,5
  • Moritz Helias13,14
  • Eric Shea‐Brown6,15
15 affiliations
  1. 1Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany. [email protected]
  2. 2Institute of Neuroscience and Medicine (INM-6 and INM-0) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany
  3. 3Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel. [email protected]
  4. 4University of Washington Computational Neuroscience Center, Department of Applied Mathematics, and Swartz Center for Theoretical Neuroscience, Seattle, WA, USA. [email protected]
  5. 5University of Washington Center for Computational Neuroscience and Swartz Center for Theoretical Neuroscience, Seattle, WA, USA
  6. 6Allen Institute, Seattle, WA, USA
  7. 7School of Life Sciences and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
  8. 8Department of Mathematics and Statistics, Boston University, Boston, MA, USA
  9. 9Department of Mathematics and Statistics, Boston University, MA, USA
  10. 10Bioelectronics (IBI-3), Jülich Research Centre, Jülich, Germany
  11. 11Systems Neurophysiology, Institute of Zoology, RWTH Aachen University, Aachen, Germany
  12. 12Institute of Experimental Epileptology and Cognition Research, Medical Faculty, University of Bonn, Bonn, Germany
  13. 13Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany
  14. 14Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany
  15. 15University of Washington Computational Neuroscience Center, Department of Applied Mathematics, and Swartz Center for Theoretical Neuroscience, Seattle, WA, USA
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Abstract

The brain contains an astronomical number of neurons, but it is their collective activity that underlies brain function. The number of degrees of freedom that this activity explores (its dimensionality) is therefore a fundamental signature of neural dynamics. However, it is not known what controls dimensionality in the biological brain. Through analysis of high-density Neuropixels recordings, here, we argue that areas across the mouse cortex predominantly operate in a sensitive regime that gives recurrent synaptic networks a strong role in regulating dimensionality. This control is expressed across time, as cortical activity transitions among states with different dimensionalities. Moreover, this control is mediated through highly tractable features of synaptic networks (network motifs). Analyzing a massive synaptic physiology dataset, we find that motifs impacting dimensionality are prevalent in both mouse and human brains. Thus, local circuitry scales up systematically to help control the degrees of freedom that brain networks may explore and exploit.

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Cite

BibTeXRIS
BibTeX
@article{dahmen2026strong,
  title = {{Strong and localized recurrence controls the dimensionality of neural activity across brain areas}},
  author = {David Dahmen and Stefano Recanatesi and Xiaoxuan Jia and Gabriel Koch Ocker and Nilufar Lahiji and Simon Musall and Luke Campagnola and Stephanie C. Seeman and Tim Jarsky and Moritz Helias and Eric Shea‐Brown},
  journal = {Nature Neuroscience},
  year = {2026},
  month = aug,
  doi = {10.1038/s41593-026-02395-w},
  url = {https://doi.org/10.1038/s41593-026-02395-w},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Strong and localized recurrence controls the dimensionality of neural activity across brain areas
AU  - David Dahmen
AU  - Stefano Recanatesi
AU  - Xiaoxuan Jia
AU  - Gabriel Koch Ocker
AU  - Nilufar Lahiji
AU  - Simon Musall
AU  - Luke Campagnola
AU  - Stephanie C. Seeman
AU  - Tim Jarsky
AU  - Moritz Helias
AU  - Eric Shea‐Brown
PY  - 2026
DA  - 2026/08/19
JO  - Nature Neuroscience
DO  - 10.1038/s41593-026-02395-w
UR  - https://doi.org/10.1038/s41593-026-02395-w
AB  - The brain contains an astronomical number of neurons, but it is their collective activity that underlies brain function. The number of degrees of freedom that this activity explores (its dimensionality) is therefore a fundamental signature of neural dynamics. However, it is not known what controls dimensionality in the biological brain. Through analysis of high-density Neuropixels recordings, here, we argue that areas across the mouse cortex predominantly operate in a sensitive regime that gives recurrent synaptic networks a strong role in regulating dimensionality. This control is expressed across time, as cortical activity transitions among states with different dimensionalities. Moreover, this control is mediated through highly tractable features of synaptic networks (network motifs). Analyzing a massive synaptic physiology dataset, we find that motifs impacting dimensionality are prevalent in both mouse and human brains. Thus, local circuitry scales up systematically to help control the degrees of freedom that brain networks may explore and exploit.
SN  - 1097-6256
SN  - 1546-1726
ER  -