Networking Brains: Modeling Spatial Relationships of the Cerebral Cortex

Abstract

Brain mapping has always been a priority in neurobiology and evolutionary neuroanatomy. In the last century, methodological issues and technical advances have generated a vivid debate on the parcellation and functions of the cortical territories. Brain structure is generally analyzed by considering the network of connections associated with neural pathways. Nonetheless, there is still a major debate on the recognition of the spatial and geometrical components of the cerebral cortex. The maps produced by Korbinian Brodmann in the early twentieth century on the basis of histological patterns represented a pioneering and decisive step in this sense, being a reference until the present day. Network models allow a numerical analysis of the spatial relationships among anatomical elements, supplying a quantitative tool to evaluate their reciprocal geometrical organization. This approach is able to analyze the spatial parameters associated with an anatomical system, characterized by the relationships of its elements. The network analysis of the spatial contiguity of Brodmann’s areas approximately describes the major cerebral lobes. A frontal cluster includes only the prefrontal areas. There is a large parieto-occipital block including also the precentral and paracentral cortex. The cortical areas identified by the model match different areas of craniocerebral relationships, namely, the anterior fossa influenced by the upper face (prefrontal cortex), the middle fossa influenced by cranial base and mandibular integration (temporal cortex), and the vault which is characterized by more linear brain-bone dynamics (parieto-occipital cortex). The maps of Brodmann, after one century of contributions, are now replaced by finer parcellations obtained with new technical approaches based on histology, biochemistry, and metabolism, enhanced by advances in brain imaging and digital biology. Besides issues associated with cognitive processing, structural factors can influence geometrical and mechanical properties of the cerebral morphology. Network theory, applied to alternative parcellation schemes or to specific brain districts, can provide essential information on evolutionary factors channeling or constraining the evolution of the brain spatial organization.