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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

When brain signals are recorded in an electroencephalogram or some similarlarge-scale record of brain activity, oscillatory patterns are typicallyobserved that are thought to reflect the aggregate electrical activity of theunderlying neuronal ensemble. Although it now seems that such patternsparticipate in feedback loops both temporally with the neurons' spikes andspatially with other brain regions, the mechanisms that might explain theexistence of such loops have remained essentially unknown. Here we present atheoretical study of these issues on a cortical model we introduced earlier[Nathan A, Barbosa VC (2010) Network algorithmics and the emergence of thecortical synaptic-weight distribution. Phys Rev E 81: 021916]. We start withthe definition of two synchronization measures that aim to capture thesynchronization possibilities offered by the model regarding both the overallspiking activity of the neurons and the spiking activity that causes theimmediate firing of the postsynaptic neurons. We present computational resultson our cortical model, on a model that is random in the Erd\H{o}s-R\'enyisense, and on a structurally deterministic model. We have found that thealgorithmic component underlying our cortical model ultimately provides,through the two synchronization measures, a strong quantitative basis for theemergence of both types of synchronization in all cases. This, in turn, mayexplain the rise both of temporal feedback loops in the neurons' combinedelectrical activity and of spatial feedback loops as brain regions that arespatially separated engage in rhythmic behavior.

Network algorithmics and the emergence of synchronization in cortical models