Nicholas FitzRoy-Dale's personal journal. I also write a programming blog and a tumble log. Contact me at or subscribe to my RSS feed.

Jun 26, 2018
Paper: Sporns: The non-random brain: efficiency, economy, and complex dynamics: February 2011

(New direction for this blog.)

“Modules (carefully defined) are important in biological brains for efficiency reasons”.

Older models of learning demonstrated the effects on random networks, but real brain networks are small-world networks (of some varying degree), with highly-interconnected hubs, for various reasons including metabolic cost of long-range connectivity (‘wiring cost’). It is therefore unrealistic to demonstrate learning on random networks.

“Random” has multiple definitions — random networks take one aspect of graph generation (such as number of nodes and average number of edges) and hold it constant while varying another aspect (e.g. the from and to nodes of the edges)

“Module” is overloaded. Modules definitely aren’t repeated neural circuits — there is a lot of variability in the actual wiring. Instead modules may be “characteristic patterns of ‘average connectivity’ that can inform dynamic models of local or large-scale cortical dynamics”.

Highly-connected hubs are association regions?