Evolution of the Brain, Cognition, and Emotion in Vertebrates by Shigeru Watanabe Michel A Hofman & Toru Shimizu

Author:Shigeru Watanabe, Michel A Hofman & Toru Shimizu
Language: eng
Format: epub
Publisher: Springer Japan, Tokyo

7.5 Neural Network Wiring

Although the details of the interpretation of the columnar organization of the neocortex are still controversial (for critical reviews, see Da Costa and Martin 2010; Rockland 2010; Preuss 2001; DeFelipe 2015), it is evident that the potential for brain evolution results not from the unorganized aggregation of neurons but from cooperative association by the self-similar compartmentalization and hierarchical organization of neural circuits and the invention of fractal folding, which reduces the interconnective axonal distances. The human cerebral cortex, for example, contains about 20 billion neurons, which are interconnected via a massive yet highly organized network of axonal and dendritic wiring. This wiring enables both near and distant neurons to coordinate their responses to external stimulation. Understanding the organizing principles of cortical wiring, therefore, represents a central goal toward explaining human cognition and perception (see for example, Preuss 2011; Budd and Kisvárday 2013; De Reus et al. 2014; Wang and Liu 2014).

In the mammalian cerebral cortex, reciprocal connections between excitatory and inhibitory neurons are distributed across multiple layers, encompassing modular, dynamical, and recurrent functional networks during information processing. These dynamical brain networks are often organized in neuronal assemblies interacting through rhythmic phase relationships. Accordingly, these oscillatory interactions are observed across multiple brain scale levels, and they are associated with several sensory, motor, and cognitive processes. Recently Bosman and Aboitiz (2015) argued that there are functional constraints in the evolution of brain circuits and that these constraints may be the result of advantages that oscillatory activity contributes to brain network processes, such as information transmission and code reliability.

Network studies, using diffusion tensor imaging (DTI), have demonstrated that not only the neurons in the cerebral cortex are structurally and functionally highly organized but that it also holds for the wiring of the entire brain (Van den Heuvel and Sporns 2011; Wedeen et al. 2012; Van den Heuvel et al. 2016). The interconnecting white matter axonal pathways are not a mass of tangled wires, as thought for a long time, but they form a rectilinear three-dimensional grid continuous with the three principal axes of development. The topology of the brain’s long-range communication network looks like a 3-D chessboard with a number of highly connected neocortical and subcortical hub regions. The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools (for a review, see Sporns and Betzel 2016). It turns out that modularity is a key characteristic of brain networks across species and scales. Indeed, the modular organization of the primate neocortex may confer increased robustness and more flexible learning, help to conserve wiring cost, and promote functional specialization and complex brain dynamics (Gómez-Robles et al. 2014).

The competing requirements for high connectivity and short conduction delay may lead naturally to the observed architecture of the human neocortex. Obviously, the brain functionally benefits from high synaptic connectivity and short conduction delays.

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