Communication in neuronal networks

Abstract

Brains perform with remarkable efficiency, are capable of prodigious computation, and are marvels of communication. We are beginning to understand some of the geometric, biophysical, and energy constraints that have governed the evolution of cortical networks. To operate efficiently within these constraints, nature has optimized the structure and function of cortical networks with design principles similar to those used in electronic networks. The brain also exploits the adaptability of biological systems to reconfigure in response to changing needs.

Fig. 1

Cortical white and gray matter volumes of 59 mammalian species are related by a power law that spans five to six orders of magnitude. The line is the least squares fit, with a slope around 1.23 ± 0.01 (mean ± SD) and correlation of 0.998. The number of white matter fibers is proportional to the gray matter volume; their average length is the cubic root of that volume. If the fiber cross section is constant, then the white matter volume should scale approximately as the 4/3 power of the gray matter volume. An additional factor arises from the cortical thickness, which scales as the 0.10 power of the gray matter volume. [Adapted from (11)]

Fig. 2

Power consumption limits neural signaling rate in the gray matter of rat cerebral cortex. Baseline consumption is set by the energy required to maintain the resting potentials of neurons and associated supportive tissue (r.p.) and to satisfy their vegetative needs (nonsignaling). Signaling consumption rises linearly with the average signaling rate (the rate at which neurons transmit action potentials). The measured rates of power consumption in rat gray matter vary across cortical areas and limit average signaling rates to 3 to 5.5 Hz. Values are from (19), converted from rates of hydrolysis of adenosine triphosphate (ATP) to W/kg using a free energy of hydrolysis for a molecule of ATP under cellular conditions of 10⁻¹⁹ J.