Functional trade-offs in white matter axonal scaling

Area of Science:

• Neuroscience
• Comparative Biology
• Mammalian Physiology

Background:

• Mammalian brain metabolism scales with size, with larger brains exhibiting lower metabolic rates.
• The functional implications of metabolic scaling on neural communication, particularly axon properties, remain unclear.

Purpose of the Study:

• To investigate how white matter composition, specifically axon characteristics, changes with mammalian brain size.
• To understand the functional consequences of these changes on neural conduction speed and metabolic efficiency.

Main Methods:

• Comparative analysis of white matter composition across a range of mammalian species, from small shrews to large whales.
• Examination of axon size, conduction velocity, and energy consumption.
• Modeling of metabolic scaling and conduction time based on axon size distributions.

Main Results:

• White matter composition shifts from unmyelinated to myelinated axons as brain size increases.
• Larger brains utilize larger, faster-conducting, and more energy-efficient myelinated axons.
• Fastest axons achieve neocortical conduction times of 1-5 ms and eye-to-brain times under 1 ms.
• Axon size distributions explain metabolic rate scaling and suggest a maximum neural firing rate of 7 ± 2 Hz.

Conclusions:

• Mammalian white matter composition represents a metabolic trade-off, optimizing for reduced conduction time and metabolic cost at the expense of increased volume in larger brains.
• Axon size and myelination are key factors in neural communication efficiency and metabolic scaling across mammals.
• Heterogeneous white matter composition in large brains facilitates rapid information processing within metabolic constraints.