Multi-compartmental Modeling Shows Correlated Conductance Parameters in Leech Heart Motor Neurons Contribute to Motor Pattern Formation Open Access

Lamb, Damon Geoffrey (2013)

Permanent URL: https://etd.library.emory.edu/concern/etds/pv63g084w?locale=en
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Abstract

Neurons can have widely differing intrinsic membrane properties, in particular the density of specific ionic conductances, but how these contribute to intrinsic neural properties and characteristic neuronal activity or pattern formation is not well understood. To explore the relationships between conductances, and in particular how they influence the activity of motor neurons in the well characterized leech heartbeat system, we developed a new multi-compartmental Hodgkin-Huxley style leech heart motor neuron model. To do so, we evolved a population of model instances, which differed in the density of specific conductances, capable of achieving specific output activity targets given an associated input pattern. We then examined the sensitivity of measures of output activity to conductances and how the model instances responded to hyperpolarizing current injections. We found that the strengths of many conductances, including those with differing dynamics, had strong partial correlations and that these relationships appeared to be linked by their influence on heart motor neuron activity. Conductances that had positive correlations opposed one another and had the opposite effects on activity metrics when perturbed whereas conductances that had negative correlations could compensate for one another and had similar effects on activity metrics.

Table of Contents

Chapter 1: General introduction. 1

Chapter 2: Model construction and framework. 13

Input/output dataset. 13 Evolution and simulation framework. 19 Updated synapse model26 Calcium sensitive potassium channel model30

Chapter 3: Correlated Conductance Parameters in Leech Heart Motor Neurons Contribute to Motor Pattern Formation. 33

Abstract. 33 Introduction. 34 Methods. 43 Results. 74 Discussion. 102

Chapter 4: General discussion. 120

Chapter 5: References. 128

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