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Although globus pallidus (GP) is dominated by a single morphological type of projection neuron, it shows patterns of activity ranging from strongly bursting to more regularly firing in vivo. The activity of different neurons is uncorrelated in normal animals, but in Parkinsonian states, activity switches to synchronous bursting. The degree to which single neuron properties contribute to the diseased activity pattern has not been addressed. Finding relationship between the distribution of its intrinsic properties and dynamic activity of GP neurons is a crucial step in understanding larger-scale phenomena such as network oscillations and inter-nuclei synchronization.
We used multicompartmental modeling to understand distribution of ion channel parameters in GP neurons by fitting models to activity recorded in slice preparation from Sprague-Dawley rats. Electrophysiologic measures of real and model GP neurons were determined automatically from voltage traces. These measures are collected in databases (DBs), allowing quantitative comparisons between model and real neurons. The physiology DB (phDB) was generated from 146 recorded GP neurons. The model DBs contained variations of our model that consisted of 500-600 compartments in three different morphological reconstructions, where each compartment had 9 conductances. Each conductance was scaled using a maximal conductance parameter, and its dynamics were governed by voltage-dependent activation, inactivation and time constant parameters. Earlier, we analyzed a ~100,000-model DB by varying the maximal value of the model's nine conductances (mcDB). In the present study, we compared these results with a model DB obtained by varying nine half-activation voltage parameters of selected conductances (haDB). We used a brute-force approach to systemically scan the parameter space to find physiologically realistic models.
Our analyses revealed that distribution of model measures obtained by both manipulations were similar, and provided good matches to the electrophysiological characteristics in phDB. Although model DB measure distributions were different, they were unimodal and provided a good overlap with distributions in phDB. For instance, the firing rate ranged between 0-60 Hz in all three distributions, while peaking at 23.3 Hz in phDB, 2.17 Hz in haDB and 10 Hz in mcDB. We also found specific cases where each parameter manipulation had an advantage in obtaining realistic behavior. Thus, it is equally possible that GP heterogeneity is caused by a continuous distribution of either ion channel densities or shifts in voltage-dependence of activation and inactivation.

Authors:	*C. GUNAY, J. R. EDGERTON, D. JAEGER; Biol. Dept, Emory Univ., Atlanta, GA
Although globus pallidus (GP) is dominated by a single morphological type of projection neuron, it shows patterns of activity ranging from strongly bursting to more regularly firing in vivo. The activity of different neurons is uncorrelated in normal animals, but in Parkinsonian states, activity switches to synchronous bursting. The degree to which single neuron properties contribute to the diseased activity pattern has not been addressed. Finding relationship between the distribution of its intrinsic properties and dynamic activity of GP neurons is a crucial step in understanding larger-scale phenomena such as network oscillations and inter-nuclei synchronization. We used multicompartmental modeling to understand distribution of ion channel parameters in GP neurons by fitting models to activity recorded in slice preparation from Sprague-Dawley rats. Electrophysiologic measures of real and model GP neurons were determined automatically from voltage traces. These measures are collected in databases (DBs), allowing quantitative comparisons between model and real neurons. The physiology DB (phDB) was generated from 146 recorded GP neurons. The model DBs contained variations of our model that consisted of 500-600 compartments in three different morphological reconstructions, where each compartment had 9 conductances. Each conductance was scaled using a maximal conductance parameter, and its dynamics were governed by voltage-dependent activation, inactivation and time constant parameters. Earlier, we analyzed a ~100,000-model DB by varying the maximal value of the model's nine conductances (mcDB). In the present study, we compared these results with a model DB obtained by varying nine half-activation voltage parameters of selected conductances (haDB). We used a brute-force approach to systemically scan the parameter space to find physiologically realistic models. Our analyses revealed that distribution of model measures obtained by both manipulations were similar, and provided good matches to the electrophysiological characteristics in phDB. Although model DB measure distributions were different, they were unimodal and provided a good overlap with distributions in phDB. For instance, the firing rate ranged between 0-60 Hz in all three distributions, while peaking at 23.3 Hz in phDB, 2.17 Hz in haDB and 10 Hz in mcDB. We also found specific cases where each parameter manipulation had an advantage in obtaining realistic behavior. Thus, it is equally possible that GP heterogeneity is caused by a continuous distribution of either ion channel densities or shifts in voltage-dependence of activation and inactivation.

Support:	NINDS R01-NS039852
	NIMH R01-MH065634