Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others failed to find significant synchronization levels in such tasks. We attempt to understand both lines of evidence within a coherent theoretical framework. We conceptualize synchronization as an independent control parameter to study how the postsynaptic neuron transmits the average firing activity of a presynaptic population, in the presence of synchronization. We apply the Berger-Levy theory of energy efficient information transmission to interpret simulations of a Hodgkin-Huxley-type postsynaptic neuron model, where we varied the firing rate and synchronization level in the presynaptic population independently. We find that for a fixed presynaptic firing rate the simulated postsynaptic interspike interval distribution depends on the synchronization level and is well-described by a generalized extreme value distribution. For synchronization levels of 15% to 50%, we find that the optimal distribution of presynaptic firing rate, maximizing the mutual information per unit cost, is maximized at ~30% synchronization level. These results suggest that the statistics and energy efficiency of neuronal communication channels, through which the input rate is communicated, can be dynamically adapted by the synchronization level.Comment: 47 pages, 14 figures, 2 Table

Channel Modelling of Blood Capillary-based Molecular Communication

Molecular communication (MC) is a new and promising interdisciplinary bio-inspired communication paradigm, which uses molecules as information carriers. Differing from traditional communication, MC is proposed as a feasible solution for nanoscale communication with the help of biological scenarios to overcome the communication limitations. Meanwhile, it is inspired by intracellular and intercellular communication, which involves exchange of information through the transmission, propagation, and reception of molecules. Blood capillaries, extensively distributed in the human body and mutually connected with tissues, are potentially applied to MC, which is the major motivation of this thesis. The focus of this PhD thesis is on the channel modelling of blood capillaries or blood vessels. The objectives of the research are to provide solutions to the modelling of blood capillary-based MC from a communication engineering and information theory perspective. The relationship of the biological scenario in blood capillaries to a communication system is studied. After demonstrating the mapping from biological phenomenon to emission, propagation and reception processes, system models are established. There are three models of blood capillaries behind different biological scenarios. Firstly, the thesis establishes a basic model of vesicle release, vesicle diffusion through blood capillary and ligand reception processes within the endocrine phenomenon. Moreover, differing from previous research in macroscopic Fick's diffusion, this work involves microscopic Langevin diffusion to describe the propagation process with a frequency domain method being proposed to calculate the information-theoretical performance channel capacity. Secondly, a much more realistic blood capillary model with blood flow drift which matches a laminar flow regime is presented, where a generalised Langevin equation is used to model the drift force exerted by blood flow. Finally, the thesis establishes a single input and multiple output MC model with hierarchical levels of Y-shaped bifurcation of blood capillaries, then BER, SNR, and channel capacity performance are analysed