Back

Uncovering the Basis of Human ConnectomeComplexity: The Role of Neuronal Morphology

Barros Zulaica, N.; Egas Santander, D.; Kanari, L.; Shi, Y.; Perin, R.; Pezzoli, M.; Benavides-Piccione, R.; DeFelipe, J.; de Kock, C. P.; Segev, I.; Markram, H.; Reimann, M.

2026-02-13 neuroscience
10.64898/2026.02.12.705493 bioRxiv
Show abstract

Comparative studies have established differences between the electrophysiology and anatomy of human and rodent cortical circuits. A consistent finding is that human neuronal morphologies display more elaborate neurite shapes than those of rodents, a feature that cannot be accounted for merely by their larger size according to recent findings. Here, we study the impact of these neurite shapes on the structure of synaptic connectivity in their local microcircuitry. Our approach is based on the idea that axonal and dendritic geometries constrain the locations of afferent and efferent synaptic contacts (potential connectivity). Although the mechanisms by which potential connectivity translates into actual synaptic connectivity are manifold and complex, the potential connectivity is nevertheless highly informative for the final structure of a biological connectome. We found that connectomes predicted from human reconstructed morphologies have higher complexity according to several measures that have been demonstrated to be functionally relevant. Going beyond a simple comparison, we demonstrate mechanistically how the shapes of neuron morphologies give rise to non-random and clustered structures observed in experimentally measured connectomes, and how the specific shapes of human neurons strengthen the process. Finally, we conceptually examine how synapse formation processes may interact with potential connectivity, showing that a process compatible with Hebbian plasticity leads to the highest complexity and best match experimentally observed patterns.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
eLife
5422 papers in training set
Top 2%
17.1%
2
PLOS Computational Biology
1633 papers in training set
Top 4%
8.9%
3
Cell Reports
1338 papers in training set
Top 5%
7.0%
4
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 9%
7.0%
5
Current Biology
596 papers in training set
Top 3%
6.6%
6
iScience
1063 papers in training set
Top 2%
6.2%
50% of probability mass above
7
Frontiers in Computational Neuroscience
53 papers in training set
Top 0.4%
6.2%
8
eneuro
389 papers in training set
Top 2%
3.9%
9
Scientific Reports
3102 papers in training set
Top 43%
2.8%
10
The Journal of Neuroscience
928 papers in training set
Top 4%
2.5%
11
Neuroscience
88 papers in training set
Top 0.8%
2.0%
12
PRX Life
34 papers in training set
Top 0.5%
1.4%
13
Frontiers in Systems Neuroscience
19 papers in training set
Top 0.2%
1.4%
14
Neuron
282 papers in training set
Top 6%
1.4%
15
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 5%
1.3%
16
Journal of Comparative Neurology
66 papers in training set
Top 0.5%
1.2%
17
Cerebral Cortex
357 papers in training set
Top 1%
1.1%
18
Progress in Neurobiology
41 papers in training set
Top 1%
0.9%
19
Frontiers in Neuroscience
223 papers in training set
Top 6%
0.9%
20
Nature Communications
4913 papers in training set
Top 62%
0.8%
21
Physical Review Research
46 papers in training set
Top 0.8%
0.8%
22
Network Neuroscience
116 papers in training set
Top 1%
0.8%
23
Science Advances
1098 papers in training set
Top 31%
0.7%
24
Biophysical Journal
545 papers in training set
Top 5%
0.7%
25
Communications Biology
886 papers in training set
Top 25%
0.7%
26
Frontiers in Neural Circuits
36 papers in training set
Top 0.8%
0.7%
27
Developmental Cell
168 papers in training set
Top 12%
0.7%
28
The Journal of Physiology
134 papers in training set
Top 2%
0.6%
29
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 11%
0.6%