THE EFFECTS OF GAP JUNCTIONS AND INHIBITION ON SYNCHRONIZATION OF BIOPHYSICALLY DETAILED NEURAL NETWORK MODELS OF BUSHY CELLS OF VENTRAL COCHLEAR NUCLEUS

Abstract

The cochlear nucleus is the first stage in the central auditory nervous system (CANS) that receives information from auditory nerve fibers (ANFs). Sound identification and localization cues are extracted here and propagated to the upper levels of the CANS. One of the main cell types of the ventral cochlear nucleus is the bushy cells which can be divided into two subtypes as globular and spherical bushy cells (GBCs and SBCs). Bushy cells receive excitation from ANFs and inhibition from D-stellate and tuberculoventral cells via chemical synapses. Additionally, bushy cells are connected via electrical synapses known as gap junctions and form clusters. One of the main features of bushy cells is enhancing the synchronization behavior seen in ANFs. Although coincidence detection can be the underlying mechanism for the GBCs to show this behavior, SBCs’ synchrony enhancement mechanism is still unclear. In this thesis, biophysically detailed neural network models of SBCs and GBCs are built to investigate the effect of gap junctions on the excitability and the synchronization behavior of GBCs and SBCs. Current injection simulations show that gap junctions substantially affect the excitability of the bushy cell models and allow the spread of excitation within and between the cell clusters. Simulations made with more realistic synaptic inputs indicate that inhibition and gap junctions strongly affect the synchronization of the model SBCs and GBCs. Although the effects of the inhibition on synchronization is non-monotonic, the effects of gap junctions on the synchronization found to be clearer. A grid search is done to investigate the effects of the inhibition, gap junctions, and strength of excitation on the synchronization of bushy cell models and a set of parameters is hand-picked to fit the model results to the recorded physiological data.