Abstract
Why do cortical microcircuits in a variety of brain regions express similar, highly nonrandom, network motifs?
To what extent this structure is innate and how much of it is molded by plasticity and learning processes? To
address these questions, we developed a general network science framework to quantify the contribution of
neurons’ geometry and their embedding in cortical volume to the emergence of three-neuron network motifs.
Applying this framework to a dense in silico reconstructed cortical microcircuits showed that the innate
asymmetric neuron’s geometry underlies the universally recurring motif architecture. It also predicted the spatial
alignment of cells composing the different triplets-motifs. These predictions were directly validated via in vitro
12-patch whole-cell recordings (7,309 triplets) from rat somatosensory cortex. We conclude that the local
geometry of neurons imposes an innate, already structured, global network architecture, which serves as a
skeleton upon which fine-grained structural and functional plasticity processes take place
To what extent this structure is innate and how much of it is molded by plasticity and learning processes? To
address these questions, we developed a general network science framework to quantify the contribution of
neurons’ geometry and their embedding in cortical volume to the emergence of three-neuron network motifs.
Applying this framework to a dense in silico reconstructed cortical microcircuits showed that the innate
asymmetric neuron’s geometry underlies the universally recurring motif architecture. It also predicted the spatial
alignment of cells composing the different triplets-motifs. These predictions were directly validated via in vitro
12-patch whole-cell recordings (7,309 triplets) from rat somatosensory cortex. We conclude that the local
geometry of neurons imposes an innate, already structured, global network architecture, which serves as a
skeleton upon which fine-grained structural and functional plasticity processes take place
Original language | American English |
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Publisher | bioRxiv |
Pages | 1-19 |
Number of pages | 19 |
Volume | 656058 |
DOIs | |
State | Published - 7 May 2020 |