Using Computational Models to Assess the Functional Consequences of BDNF-Induced Excitatory and Inhibitory Synapse Formation

The action potential is fundamental to the transfer of information between neurons. The generation of an action potential is influenced by the spatial distribution of dendrites and synapses around the neuronal soma where the action potential is initiated. Brain-derived neurotrophic factor (BDNF) is a secreted molecule that influences synapse density and action potential generation. In this thesis, I test the hypothesis that elevated BDNF signaling increases the rate of action potential generation by promoting a spatial distribution of synapses that is more efficient at generating action potentials. I begin by developing an algorithmic approach for constraining computational models of action potential generation with actual distributions of excitatory and inhibitory synapses obtained with confocal microscopy of individual neurons. Next, I apply this algorithm to primary cortical neurons that have been stimulated with a single acute dose of BDNF. I determine that BDNF alters the spatial distribution of excitatory and inhibitory synapses and that the resulting distribution is more adept at converting barrages of synaptic activity into action potentials. Finally, I investigate the molecular mechanisms that mediate BDNF-induced excitatory synapse formation. I determine that the established BDNF target gene Arc is required for BDNF-induced excitatory synapse and dendrite formation. Further, I determine that LRRMT1 is a BDNF target gene that displays an additive interaction with BDNF during the process of excitatory synapse formation. Collectively, these data highlight previously undocumented mechanisms by which BDNF may shape cortical circuitry