Use of compartmental models to predict physiological properties of hippocampal inhibitory neurons

Inhibitory neurons, or interneurons, which make up only 10-15% of the neuronal population in the hippocampus are thought to control and sculpt field rhythms through their contact with hundreds of excitatory cells, or pyramidal neurons. Interneurons are heterogeneous in terms of their morphologies, biophysical properties, and their presynaptic or postsynaptic targets. These heterogeneities are thought to have functional significance. We hypothesize that biophysical parameters of neurons can be determined by a variety of simulations using morphologically realistic multi-compartment neuron models. Virtual experiments, which would be difficult or impossible to perform in real experiments, can be used to place constraints on such parameters as the ion channel content of distal dendrites or the location of electrical synapses between neurons. The basket cell models were used in two-cell networks to explore how location and strength of electrical coupling affects network spiking patterns. Proximal gap junctions resulted in pure synchrony patterns for all gap junctional strengths and all intrinsic frequencies explored. Middle and distal dendritic gap junctional locations produced a variety of network patterns including pure synchrony, phase-locked and anti-phase. Both interneuron types have been shown experimentally to contribute to the theta/gamma field rhythms that have been measured in vivo during exploration and learning. Speculations on the possible role of the parameters explored here are discussed within the context of the theta/gamma field rhythms and the hippocampal circuitry. Kinetic model parameters were determined for the muscarinic potassium current, IM, by using multi-compartment models of O-LM interneurons with various IM somato-dendritic distributions. The simulations predicted conductance densities for each distribution to match experiments. Using a reverse engineering approach, the steady-state activation curves of IM were predicted in simulations to match whole cell recordings from experiments. Using sinusoidal current inputs, the O-LM interneuron models displayed a resonance at theta frequencies which could be expanded with block of IM, particularly for suprathreshold sinusoidal inputs. The aim of this dissertation was to use compartmental models to predict physiological parameters of hippocampal inhibitory neurons. The oriens-lacunosum/moleculare (O-LM) and basket cell interneurons were the focus of this work due to the availability of biophysical data for these interneuron subtypes.

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