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Peer-reviewedCC BY-NC-NDProceedings of the National Academy of Sciences

Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons

  • Ido Aizenbud1
  • Daniela Yoeli1
  • David Beniaguev1
  • Christiaan P. J. de Kock2
  • Michael London3,1
  • Idan Segev3,1
  1. 1The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem
  2. 2Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, Vrije Universiteit Amsterdam
  3. 3Department of Neurobiology, The Hebrew University of Jerusalem
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Abstract

Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct properties of human cortical neurons help explain the superior cognitive capabilities of humans? Understanding this relationship requires a measure to quantify how neuronal properties contribute to the functional complexity of single neurons; yet, such a standardized measure is currently missing. Here, we propose the Functional Complexity Index (FCI), a general, deep-learning-based framework for assessing the input-output complexity of neurons. By comparing the FCI of cortical pyramidal neurons across layers in rats and humans, we identified key morpho-electrical factors that underlie neuronal functional complexity. Human cortical pyramidal neurons are significantly more functionally complex than their rat counterparts, primarily due to differences in dendritic membrane area and branching patterns, as well as in the density and nonlinearity of NMDA-mediated synaptic receptors. These findings reveal the structural and biophysical basis for the enhanced functional properties of human cortical neurons, providing a key step toward understanding the underpinnings of our enhanced cognitive capabilities.

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Cite

BibTeXRIS
BibTeX
@article{aizenbud2026dendritic,
  title = {{Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons}},
  author = {Ido Aizenbud and Daniela Yoeli and David Beniaguev and Christiaan P. J. de Kock and Michael London and Idan Segev},
  journal = {Proceedings of the National Academy of Sciences},
  year = {2026},
  month = jul,
  doi = {10.1073/pnas.2533168123},
  url = {https://doi.org/10.1073/pnas.2533168123},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons
AU  - Ido Aizenbud
AU  - Daniela Yoeli
AU  - David Beniaguev
AU  - Christiaan P. J. de Kock
AU  - Michael London
AU  - Idan Segev
PY  - 2026
DA  - 2026/07/07
JO  - Proceedings of the National Academy of Sciences
DO  - 10.1073/pnas.2533168123
UR  - https://doi.org/10.1073/pnas.2533168123
AB  - Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct properties of human cortical neurons help explain the superior cognitive capabilities of humans? Understanding this relationship requires a measure to quantify how neuronal properties contribute to the functional complexity of single neurons; yet, such a standardized measure is currently missing. Here, we propose the Functional Complexity Index (FCI), a general, deep-learning-based framework for assessing the input-output complexity of neurons. By comparing the FCI of cortical pyramidal neurons across layers in rats and humans, we identified key morpho-electrical factors that underlie neuronal functional complexity. Human cortical pyramidal neurons are significantly more functionally complex than their rat counterparts, primarily due to differences in dendritic membrane area and branching patterns, as well as in the density and nonlinearity of NMDA-mediated synaptic receptors. These findings reveal the structural and biophysical basis for the enhanced functional properties of human cortical neurons, providing a key step toward understanding the underpinnings of our enhanced cognitive capabilities.
SN  - 0027-8424
SN  - 1091-6490
ER  -