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Peer-reviewedCC BYNature Communications

Universal rhythmic architecture uncovers two modes of neural dynamics

  • Golan Karvat1
  • Maité Crespo‐García2
  • Gal Vishne3,4
  • Michael C. Anderson2
  • Ayelet Nina Landau5,6,7
7 affiliations
  1. 1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK. [email protected]
  2. 2MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
  3. 3Data Science Institute, Columbia University, New York, 10027, NY, USA
  4. 4Edmond and Lily Safra Center for brain sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
  5. 5Department of Cognitive and Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
  6. 6Department of Experimental Psychology, University College London (UCL), London, WC1H 0AP, UK
  7. 7Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
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Abstract

Understanding the organizing principles of brain activity can advance neurotechnology and medical diagnosis. Traditionally, neural activity is viewed as consisting oscillations in distinct frequency bands. However, emerging evidence suggests these oscillations often manifest as transient bursts rather than sustained rhythms. We examine the hypothesis that rhythmicity (sustained vs bursty) adds a further dimension to brain organization. Using a rhythmicity measure, we segment neurophysiological spectra from 859 participants across datasets, species, recording techniques, ages 18-88, sexes, brain regions, and cognitive states in health and disease. Our results reveal a universal rhythmicity-resolved spectral architecture with two categories: high-rhythmicity bands exhibiting sustained oscillations and new low-rhythmicity bands dominated by brief bursts. This architecture reflects two modes of operation: sustained bands suitable for maintaining ongoing activity, and transient bands which can signal responses to change. The rhythmicity-resolved architecture provides a unifying framework that bridges human and non-human findings, enables individualized spectral definitions, and offers a principled basis for understanding brain activity.

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Cite

BibTeXRIS
BibTeX
@article{karvat2026universal,
  title = {{Universal rhythmic architecture uncovers two modes of neural dynamics}},
  author = {Golan Karvat and Maité Crespo‐García and Gal Vishne and Michael C. Anderson and Ayelet Nina Landau},
  journal = {Nature Communications},
  year = {2026},
  month = may,
  doi = {10.1038/s41467-026-73553-8},
  url = {https://doi.org/10.1038/s41467-026-73553-8},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Universal rhythmic architecture uncovers two modes of neural dynamics
AU  - Golan Karvat
AU  - Maité Crespo‐García
AU  - Gal Vishne
AU  - Michael C. Anderson
AU  - Ayelet Nina Landau
PY  - 2026
DA  - 2026/05/30
JO  - Nature Communications
DO  - 10.1038/s41467-026-73553-8
UR  - https://doi.org/10.1038/s41467-026-73553-8
AB  - Understanding the organizing principles of brain activity can advance neurotechnology and medical diagnosis. Traditionally, neural activity is viewed as consisting oscillations in distinct frequency bands. However, emerging evidence suggests these oscillations often manifest as transient bursts rather than sustained rhythms. We examine the hypothesis that rhythmicity (sustained vs bursty) adds a further dimension to brain organization. Using a rhythmicity measure, we segment neurophysiological spectra from 859 participants across datasets, species, recording techniques, ages 18-88, sexes, brain regions, and cognitive states in health and disease. Our results reveal a universal rhythmicity-resolved spectral architecture with two categories: high-rhythmicity bands exhibiting sustained oscillations and new low-rhythmicity bands dominated by brief bursts. This architecture reflects two modes of operation: sustained bands suitable for maintaining ongoing activity, and transient bands which can signal responses to change. The rhythmicity-resolved architecture provides a unifying framework that bridges human and non-human findings, enables individualized spectral definitions, and offers a principled basis for understanding brain activity.
SN  - 2041-1723
ER  -