Networks of the Brain [ハードカバー]

The label "networks" in the title of this impressive book may fail to fully capture the incredible richness of intricate (multi-scale) brain structure depicted here. Perhaps an added adjective like "genuine" might serve to contrast this work with the many "toy" neural networks illustrated in other publications. To get some idea of the complexity of the genuine brain networks discussed here, picture your living room fully packed top to bottom with centimeter scale worms representing (scaled up) axons linking 100 billion cell bodies. Your worm visitors occupy multiple intricate paths; many are short and form local worm societies (modules), but some cross the entire room and allow remote worm modules to interact non-locally.

Sporns asks what network science might tell us about the brain. He begins with a non mathematical overview of graph theory, "graphs" being mathematicians' abstract label for "networks." Sporns considers both structural (fixed wiring) and functional (dynamic) interactions between brain network nodes and modules. "Modules" are defined here as communities of nodes with large numbers of internal interconnections that may, in some cases, be viewed as "super nodes" or nodes defined at larger scales. To adopt the metaphor of human social networks, neurons are analogous to persons and the modules at various scales are analogous to neighborhoods, cities, and nations.

Like social systems, brain networks exhibit a striking (nested) hierarchical modularity, essentially small networks within larger networks within still larger networks, much like nested Russian dolls. This multi-scale structure may account for much of the brain's complex behavior. I quote the famous neuroscientist Vernon Mountcastle with Sporns' provocative suggestion added in brackets, "the dynamic interaction between brain subsystems [organized in modular hierarchies] lies at the very essence of brain function." Sporns emphasizes this point by pointing out that descriptions of the brain at large scales should not be regarded as poorly resolved approximations of an underlying microscopic order; rather different scales offer parallel and complementary views of brain organization. Failure to appreciate this critical issue and focus only on a single favored level of organization may be labeled "scale chauvinism" (my words).

One important idea emerging from graph theory is that of "small world" networks, illustrated in social networks by strangers (perhaps living on opposite sides of the world) linked by a few acquaintances. The high density of short-range brain connections coupled with a small admixture of long-range connections favors small world behavior. Small worlds also promote high complexity; they appear to be quite abundant in brain structural networks, across systems, scales, and species. Network disruptions, perhaps due to lesions of network hubs, are believed to be associated with mental disturbances or other diseases.

A later chapter focuses on the neural complexity issue addressed in several earlier chapters. While there is no agreed upon rigorous measure of neural (or any other system) "complexity," many complex systems have certain common features, including the hierarchical modularity evident in brain tissue. Sporns argues that system complexity is high when order and disorder coexist. For example, the molecules in a gas exhibit (random) disorder, whereas the molecules in a crystal are ordered, but neither system qualifies as a complex system. Rather, organizational mixtures of order and disorder are hallmarks of complexity. Another common feature of complex systems is that segregation and integration of structure and dynamic activity coexist. Different parts of the brain do different things; yet they work together to produce a uniform behavior and consciousnes, a condition greatly facilitated by small world networks.

This book should have broad appeal among many neuroscientists working in disparate areas of brain science. The writing is clear with many useful figures (including beautiful color plates) and directed examples absent even a single equation. The latter feature will evidently broaden the book's appeal, although some may wish for some mathematical support in an Appendix. In any case, one can confidently predict that Sporns' book will become an essential reference on many neuroscientists' bookshelves well into the future.

The material in this book overlaps several other books aimed at broad audiences. Earlier in his career, Sporns worked closely with Gerald Edelman and Giulio Tononi; their book A Universe Of Consciousness How Matter Becomes Imagination (1995) provides and nice introduction to Sporns' conceptual framework in "Networks of the Brain." My new book (2010) emphasizes the critical importance of nested hierarchy in brain tissue, and also speculates in the wider world of intra and extra cranial information and its possible fundamental role in the production of consciousness.

This book is an excellent coverage of brain networks, covering structural, functional, and effective connectivity and their respective dynamics. I am a neurobiologist but this book is presented in such a way that it builds up to complex subjects with topics and language that non-neuroscientists (for instance computer scientists and mathematicians) can understand. There are no equations in the book and yet the mathematical concepts are explained clearly so that they can be easily understood.

I'm not a neuroscientist but have read a fair amount on the subject. This book was great, it builds up an understanding of networks in general and their application to brain science. It summarizes a lot of the latest science and makes claims that are largely in line with other authors I've read (e.g. Tononi, Gerald Edelman, Joaquin Fuster). In other words, from the perspective of someone on the sidelines, Sporns backs up the central claims with a whole lot of evidence. I'm very glad I read it and I plan on re-reading it soon to make sure it sinks in. Whatever little networks make up my brain got a good workout