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

The architecture of iso-orientation domains in the primary visual cortex ofplacental carnivores and primates apparently follows species invariantquantitative laws. Dynamical optimization models assuming that neuronscoordinate their stimulus preferences throughout cortical circuits linkingmillions of cells specifically predict these invariants. This might indicatethat V1's intrinsic connectome and its functional architecture adhere to asingle optimization principle with high precision and robustness. To validatethis hypothesis, it is critical to closely examine the quantitative predictionsof alternative candidate theories. Random feedforward wiring within theretino-cortical pathway represents a conceptually appealing alternative todynamical circuit optimization because random dimension-expanding projectionsare believed to generically exhibit computationally favorable properties forstimulus representations.  Here, we ask whether the quantitative invariants of V1 architecture can beexplained as a generic emergent property of random wiring. We generalize andexamine the stochastic wiring model proposed by Ringach and coworkers, in whichiso-orientation domains in the visual cortex arise through random feedforwardconnections between semi-regular mosaics of retinal ganglion cells (RGCs) andvisual cortical neurons. We derive closed-form expressions for corticalreceptive fields and domain layouts predicted by the model for perfectlyhexagonal RGC mosaics [...] We conclude that V1 layout invariants are specificquantitative signatures of visual cortical optimization, which cannot beexplained by generic random feedforward-wiring models.  *See pdf for the full abstract.*

Random wiring, ganglion cell mosaics, and the functional architecture of the visual cortex