Physical Constraints in Intracellular Signaling: The Cost of Sending a Bit

Many biological processes require timely communication between molecular components. Cells employ diverse physical channels to this end, transmitting information through diffusion, electrical depolarization, and mechanical waves among other strategies. Here we bound the energetic cost of transmitting information through these physical channels, in k_{B}T/bit, as a function of the size of the sender and receiver, their spatial separation, and the communication latency. These calculations provide an estimate for the energy costs associated with information processing arising from the physical constraints of the cellular environment, which we find to be many orders of magnitude larger than unity in natural units. From these calculations, we construct a phase diagram indicating where each strategy is most efficient. Our results suggest that intracellular information transfer may constitute a substantial energetic cost. This provides a new tool for understanding tradeoffs in cellular network function.

Modelling neuron fiber interaction and coupling in non-myelinated bundled fiber

Understanding the local dynamics of a neural network relies heavily on local field potential and cell-field interaction. But it is still unclear how local the local potential is and what kinds of consequences the trans-membrane current flow and produced electric field have on the local neural fiber. Mimicking signal transmission in neighboring nerve fiber, a simulation model is built to analyze local behavior due to trans-membrane current, cell-field interactions, and their repercussions on the bundled fiber system. Simulation studies reveal that depending on the coupling parameters, activity in one fiber can depolarize or hyper-polarize adjacent fibers. The suggested cell-field interaction model was tested using an orientation-selective coupled retinal ganglion cell network, which was compared to its uncoupled counterpart. The proposed work has been used to model and simulate local signal dynamics in a bundled fiber system of an orientation-selective RGC network due to cell-field interaction, as well as to gain insight into the possible significance of dendritic fiber coupling in orientation selectivity bandwidth adjustment.

Generalized cable theory for neurons in complex and heterogeneous media

Cable theory has been developed over the last decade, usually assuming that the extracellular space around membranes is a perfect resistor. However, extracellular media may display more complex electrical properties due to various phenomena, such as polarization, ionic diffusion, or capacitive effects, but their impact on cable properties is not known. In this paper, we generalize cable theory for membranes embedded in arbitrarily complex extracellular media. We outline the generalized cable equations, then consider specific cases. The simplest case is a resistive medium, in which case the equations recover the traditional cable equations. We show that for more complex media, for example, in the presence of ionic diffusion, the impact on cable properties such as voltage attenuation can be significant. We illustrate this numerically, always by comparing the generalized cable to the traditional cable. We conclude that the nature of intracellular and extracellular media may have a strong influence on cable filtering as well as on the passive integrative properties of neurons.