An Optimized Structure-Function Design Principle Underlies Efficient Signaling Dynamics in Neurons

Francesca Puppo, Vivek George, Gabriel A. Silva
2018 Scientific Reports  
Dynamic signaling on branching axons is critical for rapid and efficient communication between neurons in the brain. Efficient signaling in axon arbors depends on a trade-off between the time it takes action potentials to reach synaptic terminals (temporal cost) and the amount of cellular material associated with the wiring path length of the neuron's morphology (material cost). However, where the balance between structural and dynamical considerations for achieving signaling efficiency is, and
more » ... the design principle that neurons optimize to preserve this balance, is still elusive. In this work, we introduce a novel analysis that compares morphology and signaling dynamics in axonal networks to address this open problem. We show that in Basket cell neurons the design principle being optimized is the ratio between the refractory period of the membrane, and action potential latencies between the initial segment and the synaptic terminals. Our results suggest that the convoluted paths taken by axons reflect a design compensation by the neuron to slow down signaling latencies in order to optimize this ratio. Deviations in this ratio may result in a breakdown of signaling efficiency in the cell. These results pave the way to new approaches for investigating more complex neurophysiological phenomena that involve considerations of neuronal structure-function relationships. The mechanisms underlying the successful integration and rapid transmission of information in the brain rely on interactions between structural and dynamical properties that begin at the level of the single neuron. The complexity of these interactions are reflected in the wide variability of axon arbor morphologies and dynamical states neurons can take on. A still unsolved fundamental question is what is the relationship between the morphological design principles of individual branching axons and their role in optimizing action potential signaling in the neuron? Neuronal morphologies are the outcome of complex developmental processes including axon growth, stabilization of synaptic connections and axon pruning 1-3 . These processes are dependent on a multitude of local molecular and cellular mechanisms and conditions 4-6 . Despite the stochastic nature of morphological development, as well as other biological, physical, and molecular constraints, evolutionarily neurons have achieved a degree of common computational efficiency. A growing list of experimental and computational results, including those we present in this paper, suggest that these developmental processes in neurons satisfy a set of specific optimization principles 7-10 . Until recently, the prevailing dominant hypotheses has been that neurons are morphologically designed to optimize for the least amount of cellular material necessary. The logic was that the less amount of material that was used, the greater the conservation of energy and cellular resources. In particular, a number of studies have argued that wiring minimization principles that maximize the conservation of material underlie the morphological design of neurons and even the broader anatomical organization responsible for functional maps in the neocortex 7,10-13 , such as the intracortical wiring underlying functional maps in mammalian visual cortex 10,14 . However, more recent work has shown that neurons are not minimized for wiring length but instead are designed somewhere in between the two extremes of minimizing wiring costs versus maximizing action potential conduction velocities. They use more material than minimal construction costs would allow in order to increase conduction velocities that decrease temporal costs, but at the same time they do not signal as fast at they could if the wiring design was optimized strictly for speed, thereby offsetting the material cost 9,15 . Budd et al. have recently
doi:10.1038/s41598-018-28527-2 pmid:29992977 pmcid:PMC6041316 fatcat:omhf3lnvjrbkdcrqnsvpb7hmeu