Brain: The Neuronal Network Revolution

Abstract

This chapter deals with a central concept in causality in psychology and related disciplines---that of networks, and especially as the concept is applied to the brain. On the one hand, it deals with the Connectome, in general, as applied to brain networks and, on the other hand, it describes intrinsic or core brain networks. The concept of the Connectome is part of the burgeoning field of connectomics, which also involves pathoconnectomics. Brain connectivities might be structural, functional, or effective. Connections are established by connection matrices, which include graphs, nodes, edges, hubs, cores, and paths. The connectivities might evidence rich clubs or small worlds. The measures include ones of centrality and betweenness. The field has determined up to 14 brain networks, but three generally are considered primary---the salience network, the central executive network, and the default mode network. Another one referred to in the chapter is the frontoparietal network. A major theory cutting across networks involves a Bayesian model of the brain acting to reduce its free energy or surprise by minimizing prediction errors and otherwise functioning thermodynamically (Friston, 2010). This work is important enough to have been emphasized in the title of the book, when I refer to freeing the brain. Other concepts in this model include the ones of local and global dynamics, inference machines, meta-stability/quasi-stability, and hidden causes and econiches. The chapter refers to other causality-related terms, such as causal flow. One article discusses network organization in terms of ``cacti.'' The work on networks incorporates the perspective on NLDST, and the chapter is replete with terminology from this model and related ones. For example, it refers to ``criticality,'' which is the region in state space of a system that facilitates state change, including to ``chaotic'' regimes. Also, the chapter refers to state space ``viscosity,'' a concept not traditionally encountered in NLDST. The chapter examines systems at the micro level, that is, neuronal networks and even the networked nature of concept cells and of astrocytes. Finally, wherever one looks in research and conceptualization about the brain, one finds evidence supporting the present model of activation--inhibition coordination as being a common metric within each of and across brain and behavior, and in this chapter I point out areas where this concept applies. As for the application of network models to more behavioral phenomena, the chapter describes a network causal system model that treats items or symptoms of mental disorder. It is contrasted to the latent variable/construct model. Causality inheres in linkages across symptoms themselves rather than to underlying constructs relating them or central constructs that they address.