The Physics of Living Neural Networks

TL;DR

This paper reviews recent advances in understanding living neural networks by measuring physical and informational properties, using experimental models to elucidate structure-function relationships and exploring potential applications in neuronal devices.

Contribution

It introduces new experimental models and measurement techniques that provide quantitative insights into the structure and function of cultured neuronal networks.

Findings

Quantitative analysis of propagation speeds and synaptic transmission.

Insights into information creation and capacity in neural networks.

Experimental models enabling comparison with analytic theories.

Abstract

Improvements in technique in conjunction with an evolution of the theoretical and conceptual approach to neuronal networks provide a new perspective on living neurons in culture. Organization and connectivity are being measured quantitatively along with other physical quantities such as information, and are being related to function. In this review we first discuss some of these advances, which enable elucidation of structural aspects. We then discuss two recent experimental models that yield some conceptual simplicity. A one-dimensional network enables precise quantitative comparison to analytic models, for example of propagation and information transport. A two-dimensional percolating network gives quantitative information on connectivity of cultured neurons. The physical quantities that emerge as essential characteristics of the network in vitro are propagation speeds, synaptic transmission, information creation and capacity. Potential application to neuronal devices is discussed.