Abstract
The functional organization of the mammalian brain can be considered to form a layered control architecture, but how this complex system has emerged through evolution and is constructed during development remains a puzzle. Here we consider brain organization through the framework of constraint closure, viewed as a general characteristic of living systems, that they are composed of multiple sub-systems that constrain each other at different timescales. We do so by developing a new formalism for constraint closure, inspired by a previous model showing how within-lifetime dynamics can constrain between-lifetime dynamics, and we demonstrate how this interaction can be generalized to multi-layered systems. Through this model, we consider brain organization in the context of two major examples of constraint closure—physiological regulation and visual orienting. Our analysis draws attention to the capacity of layered brain architectures to scaffold themselves across multiple timescales, including the ability of cortical processes to constrain the evolution of sub-cortical processes, and of the latter to constrain the space in which cortical systems self-organize and refine themselves.This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.
Highlights
Beginning with the nineteenth century philosopher, Herbert Spencer [1], and the neurologist, John Hughlings Jackson [2,3], there is an extensive literature that views the nervous system as a layered architecture
Both homeostasis and allostasis emphasize the maintenance of equilibria, and while this has sometimes been expressed through the engineering idea of ‘set points’, the search for brain mechanisms that explicitly defend specific values or ranges of key physiological variables has yielded little evidence [29,32], leading to the alternative idea of ‘balance points’ as values that are implicitly maintained through the interacting dynamics of multiple regulatory processes [29,33]
As we will see operationalizing the concept of constraint closure through a computational model reveals how the dynamics of faster processes can serve to scaffold the dynamics of slower processes, permitting systems of mutually interacting slow and fast processes to discover useful states that may otherwise be impossible for a system to discover
Summary
Beginning with the nineteenth century philosopher, Herbert Spencer [1], and the neurologist, John Hughlings Jackson [2,3], there is an extensive literature that views the nervous system as a layered architecture (for reviews, see [4,5,6,7,8,9,10]). The concept of allostasis, originated by Sterling [30,31], extends this notion of adaptive regulation by recognizing that the internal balance may shift with circumstances, for example, throughout the day, or with the organism’s bodily or environmental context Both homeostasis and allostasis emphasize the maintenance of equilibria, and while this has sometimes been expressed through the engineering idea of ‘set points’, the search for brain mechanisms that explicitly defend specific values or ranges of key physiological variables has yielded little evidence [29,32], leading to the alternative idea of ‘balance points’ as values that are implicitly maintained through the interacting dynamics of multiple regulatory processes [29,33]. We will explore this idea in more detail and with respect to its implications for understanding the evolution of the brain as a layered control architecture
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