P129 Of mice and men: Dendritic architecture differentiates human from mice neuronal networks
Lida Kanari∗1, Ying Shi1,5, Alexis Arnaudon1, Natalı Barros-Zulaica1, Ruth Benavides-Piccione2, Jay S. Coggan1, Javier DeFelipe2, Kathryn Hess3, Huib D. Mansvelder4, Eline J. Mertens4, Julie Meystre5, Rodrigo de Campos Perin5, Maurizio Pezzoli5, Roy T. Daniel6, Ron Stoop7, Idan Segev8, Henry Markram1and Christiaan P.J. de Kock4
1Blue Brain Project, Ecole Polytechnique Federale de Lausanne (EPFL), Geneva, Switzerland.
2Laboratorio Cajal de Circuitos Corticales, Universidad Politecnica de Madrid and Instituto Cajal (CSIC), Madrid, Spain
3Laboratory for Topology and Neuroscience, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
4Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
5Laboratory of Neural Microcircuitry, ´Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
6Department of Clinical Neurosciences, Neurosurgery Unit, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
7Center for Psychiatric Neurosciences, Department of Psychiatry, Lausanne University Hospital Center, Lausanne, Switzerland
8Department of Neurobiology and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
* Email: lida.kanari@gmail.com
Introduction
The organizational principles that distinguish the human brain from other species have been a long-standing enigma in neuroscience. Numerous studies have investigated the correlations between intelligence and neuronal density [1], cortical thickness [2], gyrification [3], and dendritic architecture [4]. However, despite extensive endeavors to unravel its mysteries, numerous aspects of our unique characteristics remain elusive. Along several other factors that contribute in human intelligence, in this study [5] we demonstrate that the shapes of dendrites are an important indicator of network complexity that cannot be disregarded in our quest to identify what makes us human.
Results
Using experimental pyramidal cell reconstructions [6], we built representative mouse and human cortical networks (Fig. 1). We integrate experimental data, taking into account the lower cell density in human cortex layers 2 and 3 [7, 8] and the greater interneuron percentages in the human cortex [9]. Human pyramidal cells form highly complex networks (Fig. 1C), demonstrated by the increased number and simplex dimension compared to mice. Simple dendritic scaling cannot explain species-specific connectivity differences. Topological comparison of dendritic structure reveals much higher perisomatic (basal and oblique) branching density in human pyramidal cells (Fig1. D), impacting network complexity.
Methods
The Topological Morphology Descriptor [10] represents the neuronal morphology as a persistence barcode, using topological data analysis to characterize the shapes of neurons. Scaling transformations were analyzed to compare mouse and human neurons, with optimization via gradient descent. The connectivity was computed using computational modeling of the cortical layers 2 and 3 [11], and approximates the set of potential connections in mouse and human cortex. Memory capacity was analyzed based on dendritic processing models [12].
Discussion
Despite lower neuronal density, human pyramidal cells establish higher-order interactions via their distinct dendritic topology, forming complex networks. This enhanced connectivity is supported by interneurons, which maintain excitation-inhibition balance. The increased dendritic complexity of human pyramidal cells correlates with increased memory capacity, suggesting its role in computational efficiency. Rather than increasing neuron count, human brains prioritize single-neuron complexity to optimize network function. Our findings highlight dendritic morphology as a key determinant of network performance, shaping cognition and future research directions.
Figure 1. Fig1: Multiscale comparison of mouse and human brains, from brain regions to single neurons (A). Greater network complexity (C) emerges in human networks despite the lower neuron density (B), correlating with the higher dendritic complexity of human pyramidal cells. Our findings suggest that dendritic complexity (D) is more substantial for network complexity than neuron density.
Acknowledgements
BBP, EPFL, by ETH Board by SFIT. H.D.M. and C.d.K. by grant awards U01MH114812, UM1MH130981-01 from NIMH, grant no. 945539 (HBP SGA3) Horizon 2020 Framework, NWO 024.004.012, ENW-M2, OCENW.M20.285. R.S. by SNSF (IZLSZ3\_148803, IZLIZ3\_200297, IZLCZ0_206045, 31003A_138526) and Synapsis Foundation (2020-PI02). J.D.F. and R.B.P. by PID2021-127924NB-I00(MCIN/AEI/10.13039/501100011033).
References
[1]https://doi.org/10.3389/neuro.09.031.2009
[2]https://doi.org/10.1016/j.intell.2013.07.010
[3]http://dx.doi.org/10.1016/j.cub.2016.03.021
[4]https://doi.org/10.1016/j.tics.2022.08.012
[5]https://doi.org/10.1101/2023.09.11.557170
[6]https://doi.org/10.1093/cercor/bhv188
[7]https://doi.org/10.1023/A:1024130211265
[8]https://doi.org/10.1023/a:1024134312173
[9]https://doi.org/10.1126/science.abo0924
[10]https://doi.org/10.1007/s12021-017-9341-1
[11]https://doi.org/10.1016/j.cell.2015.09.029
[12]https://doi.org/10.1016/S0896-6273(01)00252-5
