Detailed reconstructed neuronal morphologies are now widely available, but how do you wire them up in a network?
The shape of the neurons provides a key constraint: synapses only can occur when presynaptic axon terminals are physically close to postsynaptic dendrites.
Today’s guest has used this and other principles to construct large-scale cortical model networks and to study the relationship between the anatomical connectivity and function of such networks.
Links:
- Reimann et al: “An algorithm to predict the connectome of neural microcircuits”, Frontiers in Computational Neuroscience (2015)
- Markram et al: “Reconstruction and Simulation of Neocortical Microcircuitry”, Cell (2015)
- Reimann et al: “A null model of the mouse whole-neocortex micro-connectome, Nature Communications (2019)
- Isbister et al: “Modeling and simulation of neocortical micro- and mesocircuitry (Part II, Physiology and experimentation )”, eLife (2024)
- Ecker et al: “Cortical cell assemblies and their underlying connectivity: An in silico study”, PLoS Computational Biology (2024)
- Reimann et al: “Spatial continuity of neurons explains non-random network architecture”, iScience (2026)
- Homepage of Michael Reimann
The podcast was recorded on August 4th, 2026 and lasts 2 hours and 17 minutes.
To become a Patreon supporter of the podcast, go to patreon.com/TheoreticalNeurosciencePodcast .
In addition to the access via the link above, the audio version of the podcast is also available through major podcast providers such as Apple, Spotify, and Amazon Music/Audible.