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Little is known about the density and function of dendritic spines on midbrain dopamine neurons, or the relative contribution of spine and shaft synapses to excitability. Using Ca(2+) imaging, glutamate uncaging, fluorescence recovery after photobleaching and transgenic mice expressing labeled PSD-95, we comparatively analyzed electrical and Ca(2+) signaling in spines and shaft synapses of dopamine neurons. Dendritic spines were present on dopaminergic neurons at low densities in live and fixed tissue. Uncaging-evoked potential amplitudes correlated inversely with spine length but positively with the presence of PSD-95. Spine Ca(2+) signals were less sensitive to hyperpolarization than shaft synapses, suggesting amplification of spine head voltages. Lastly, activating spines during pacemaking, we observed an unexpected enhancement of spine Ca(2+) midway throughout the spike cycle, likely involving recruitment of NMDA receptors and voltage-gated conductances. These results demonstrate functionality of spines in dopamine neurons and reveal a novel modulation of spine Ca(2+) signaling during pacemaking.
Pubmed ID: 27163179
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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