Models that contain the Implementer : Terman, David [terman at]

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    Models   Description
1.  A model for recurrent spreading depolarizations (Conte et al. 2017)
A detailed biophysical model for a neuron/astrocyte network is developed in order to explore mechanisms responsible for cortical spreading depolarizations. This includes a model for the Na+-glutamate transporter, which allows for a detailed description of reverse glutamate uptake. In particular, we consider the specific roles of elevated extracellular glutamate and K+ in the initiation, propagation and recurrence of spreading depolarizations.
2.  Activity patterns in a subthalamopallidal network of the basal ganglia model (Terman et al 2002)
"Based on recent experimental data, we have developed a conductance-based computational network model of the subthalamic nucleus and the external segment of the globus pallidus in the indirect pathway of the basal ganglia. Computer simulations and analysis of this model illuminate the roles of the coupling architecture of the network, and associated synaptic conductances, in modulating the activity patterns displayed by this network. Depending on the relationships of these coupling parameters, the network can support three general classes of sustained firing patterns: clustering, propagating waves, and repetitive spiking that may show little regularity or correlation. ...". Terman's XPP code and a partial implementation by Taylor Malone in NEURON and python are included.
3.  Signal fidelity in the rostral nucleus of the solitary tract (Boxwell et al 2018)
"Neurons in the rostral nucleus of the solitary tract (rNST) convey taste information to both local circuits and pathways destined for forebrain structures. This nucleus is more than a simple relay, however, because rNST neurons differ in response rates and tuning curves relative to primary afferent fibers. To systematically study the impact of convergence and inhibition on firing frequency and breadth of tuning (BOT) in rNST, we constructed a mathematical model of its two major cell types: projection neurons and inhibitory neurons. First, we fit a conductance-based neuronal model to data derived from whole cell patch-clamp recordings of inhibitory and noninhibitory neurons in a mouse expressing Venus under the control of the VGAT promoter. We then used in vivo chorda tympani (CT) taste responses as afferent input to modeled neurons and assessed how the degree and type of convergence influenced model cell output frequency and BOT for comparison with in vivo gustatory responses from the rNST. Finally, we assessed how presynaptic and postsynaptic inhibition impacted model cell output. ..."

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