Physiology in Perspective: Complexity and Emergence of Function.

In his 1986 book The Blind Watchmaker: Why the Evidence Reveals a Universe Without Design, Richard Dawkins stated that “Biology is the study of the complex things in the Universe. Physics is the study of the simple ones. ” Dawkins discussed complexity in the context of competing genes forming the basis of evolution—the “selfish gene theory”; however, complexity is the underpinning of physiology and illustrates the need to go beyond a reductionist approach. As living beings, we are more than just the sum of our parts (molecules, proteins, cells). Molecular reductionism only provides a description, not mechanisms, underlying function. Physiology as a discipline explores the emergence of function from biological complexity in which the functional properties of molecules and cells emerge only when these parts interact in a wider whole. In discussing the selfish gene theory and biological complexity, Denis Noble makes an important distinction between the components of biology, e.g., genes, ion channels, and the processes that emerge from their interactions, e.g., the rhythm of the heartbeat. Nowhere is this emergence of function from component parts more evident than in the nervous system. In this issue of Physiology, six review articles explore emergent function in the nervous system. Humans spend on average one-third of their lives asleep, but why? Evidence indicates that one the most important complex emergent functions of sleep is the consolidation of memories, which facilitates an efficient interaction with one’s environment. In their review (5), Marshall et al. explore the complex neural basis of memory consolidation during sleep, involving local cellular as well as network processes underlying neuroplasticity. They emphasize that cross talk between cortical areas and different brain structures are reflected by brain activity rhythms in particular slow synchronized oscillations, thalamo-cortical spindles, and hippocampal sharp-wave ripples that occur during sleep. It is this temporally coordinated communication that is putatively associated with memory consolidation. Knowledge on the interactions underlying these brain rhythms is therefore a necessary prerequisite for investigating whether their modification by external stimuli can affect memory function. Conversely, investigations targeting the systematic modification of memory function by external stimuli can provide a deeper understanding of the physiological processes involved in brain plasticity. Memory formation is a complex process involving not only neuronal but also non-neuronal cellular activity, chemical messengers, and neuromodulatory systems, which interact in a homeostatic or activity-dependent fashion. A greater understanding of memory function in sleep may help develop more individualized diagnostic assessment and therapeutic strategies for sleep-associated cognitive impairments. Many of the most pressing problems in biomedicine could be solved if we understood how cells cooperate to build and repair complex three-dimensional structures. Birth defects, traumatic injury, degenerative disease, and aging could be addressed if we understood how to employ complex cellular communication to build whatever new organs were needed. For these biomedical applications, and for understanding the evolution of complex bodies, it is essential to probe the physiological controls of patterning during both development and regeneration. In their review (3), Fields and colleagues explore a new hypothesis for the functional evolutionary origin of nervous systems and the relationship between neural function and non-neural controls of growth and form. They propose a novel view of the function of the nervous system in encoding developmental patterns, in addition to its function in controlling behavior, and hypothesize that this function is ancestral. They critically examine emerging evidence that neural activity tells target cells where and when to proliferate. An improved understanding of how cell networks in the brain and in the body interact to encode complex patterning information to form and move complex bodies should improve daily life by driving advances in regenerative medicine and neuroscience. All movements are mediated through the activation of motoneurons, and thus understanding the complex input-output properties of motoneurons is essential for generating a comprehensive model of motor control. In their review (1), Binder and colleagues start with the observation that the direct synaptic contacts received by motoneurons cannot provide sufficient depolarizing drive to enable optimal motoneuron firing rates. To solve this problem, motoneurons supplement the direct synaptic currents they receive with an intrinsic depolarizing drive produced by persistent inward currents (PICs) mediated by voltage-gated Na and Ca channels. The amplitudes of PICs are controlled by neuromodulatory inputs from the brain stem, especially via axons that release either serotonin or norepinephrine. Consequently, the brain stem can modulate motoneuron excitability (adjust gain) over a threeto fivefold range, largely via control of PIC amplitudes. The authors propose that this gain control mechanism permits the CNS to employ a low motoneuron input-output gain for executing precisely controlled movements and a higher gain in generating more forceful outputs. Whereas these PICs “solve” the motoneuron activation problem, the authors point out that they engender a number of nonlinearities in motoneuron behavior, including firing rate saturation and hysteresis in recruitment and de-recruitment. They speculate that this nonlinearity constitutes a tradeoff for the advantages provided by PIC amplification and urge further investigation of motoneuron behaviors in a wider range of motor tasks. Normal activation of muscle is mediated by motoneuron action potentials that are generated to evoke appropriate levels of muscle force and contraction. When there is a problem with motoneuron activation, an external electrical field can be applied to peripheral motor axons to generate muscle contraction. For example, electrical field PHYSIOLOGY IN PERSPECTIVE Gary C. Sieck, Editor-in-Chief Mayo Clinic, Rochester, Minnesota PHYSIOLOGY 35: 2–3, 2020.