CNS*2026 Halifax

Introduction
Synapses are integral to information processing and plasticity in the brain. Their functional properties, such as their strength and plasticity profiles, are determined by their underlying synaptic structure and organization. A recent study by Rollenhagen and colleagues (unpublished data) reconstructed the structure and vesicle organization of cortical layers 1-6 presynaptic boutons in the human temporal lobe neocortex (hTLN) using transmission electron microscopy and quantitative 3D volume reconstructions. The data reveal variations in vesicle numbers, sizes, and positions within each bouton, as well as differences in bouton organization, such as active zone areas, across cortical layers. 


Methods
Using these ultrastructural measurements, we develop biophysically detailed, spatially explicit, stochastic models of hTLN presynaptic boutons across cortical layers, implemented in STEPS (Stochastic Engine for Pathway Simulation, https://steps.sourceforge.net/), and simulate neurotransmitter release to investigate how synaptic transmission is shaped by bouton organization.


Results
We observe that vesicle size diversity within a presynaptic bouton enhances variability in excitatory postsynaptic current amplitudes, and that smaller vesicles exhibit higher fusion propensity due to faster diffusion compared to larger vesicles. Additionally, our modeling framework allows us to reconcile structural measurements and electrophysiological recordings from similar synapses, suggesting layer-specific differences in voltage-dependent calcium channel expression in hTLNboutons.  


Discussion
These findings suggest that nanoscale structural heterogeneity within presynaptic boutons can shape synaptic transmission dynamics and variability. Moreover, our modeling approach provides a quantitative framework linking ultrastructural measurements to functional synaptic outputs.


References
Wils, Stefan, and Erik De Schutter. "STEPS: modeling and simulating complex reaction-diffusion systems with Python." Frontiers in neuroinformatics 3 (2009): 374. 

\nHepburn, Iain, et al. "Vesicle and reaction-diffusion hybrid modeling with STEPS." Communications Biology 7.1 (2024): 573. 
\nGallimore, Andrew R., et al. "Dynamic regulation of vesicle pools in a detailed spatial model of the complete synaptic vesicle cycle." Science Advances 11.22 (2025): eadq6477. 

Acknowledgement
Astrid Rollenhagen and Joachim Lübke, Institute of Neurosciences and Medicine (INM-10), Forschungszentrum Jülich, for sharing unpublished ultrastructural data and helpful discussions; and the Scientific Computing and Data Analysis Section at OIST for access to the Deigo supercomputing cluster. This work was supported by OIST Graduate University.