English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A recent publication provides the network graph for a neocorticalmicrocircuit comprising 8 million connections between 31,000 neurons (H.Markram, et al., Reconstruction and simulation of neocortical microcircuitry,Cell, 163 (2015) no. 2, 456-492). Since traditional graph-theoretical methodsmay not be sufficient to understand the immense complexity of such a biologicalnetwork, we explored whether methods from algebraic topology could provide anew perspective on its structural and functional organization. Structuraltopological analysis revealed that directed graphs representing connectivityamong neurons in the microcircuit deviated significantly from differentvarieties of randomized graph. In particular, the directed graphs contained inthe order of $10^7$ simplices {\DH} groups of neurons with all-to-all directedconnectivity. Some of these simplices contained up to 8 neurons, making themthe most extreme neuronal clustering motif ever reported. Functionaltopological analysis of simulated neuronal activity in the microcircuitrevealed novel spatio-temporal metrics that provide an effective classificationof functional responses to qualitatively different stimuli. This studyrepresents the first algebraic topological analysis of structural connectomicsand connectomics-based spatio-temporal activity in a biologically realisticneural microcircuit. The methods used in the study show promise for moregeneral applications in network science.

Topological analysis of the connectome of digital reconstructions of neural microcircuits