Multiscale Bioelectric Fields: Implications for Neural Dynamics and Sensing

Abstract

Bioelectric fields are produced in many tissues including muscle, heart and brain. These electric fields arise from the transmembrane ionic currents that underlie action potentials. Electric fish use such fields to sense in the dark. A specialized electric organ generates large currents, the electric organ discharge (EOD), resulting in an electric field around the fish body. This self-generated field is perturbed by external heterogeneities and these perturbations modulate the activity of receptor cells on their skin, forming the basis of the electric sense. The EOD is oscillatory with an individual-specific frequency that is extremely stable. Despite this stability, fish modulate their EOD frequency on short time-scales during social interactions. When electric fish with similar frequencies interact, their EODs interfere with one another and compromise sensing. To mitigate this, fish diverge their frequencies through the jamming avoidance response. These fish also communicate via a transient desynchronization of neurons in the brain network that controls EOD timing, the pacemaker network (PN). Subsequent resynchronization occurs in tens of milliseconds, too fast to be explained by the network properties of the PN.

In the first part of this thesis, we consider the hypothesis that the EOD entrains the PN through electric field effects and increases resynchronization rate. We first develop a computational tool (ELFENN) to explore how neurons are affected by electric fields. We also develop a model of pacemaker cells in the PN and validate it against experimental data. We then combine these developments to show that feedback entrainment between the EOD and PN mediates resynchronization time.

In the second part, we focus on the electric field perturbations that occur during sensing. We first show that the spatial structure of the field is important for effective frequency separation during the jamming avoidance response. We then develop novel computational models of electric fish that are freely deformable (pyFEM2S); we can thus simulate natural poses and study how fish shape their electric field and the resultant sensory corollaries.

Finally, we consider how insight from studying bioelectric fields for sensing and control can be applied to more general aspects of electric field effects and brain function.