title: Ionic mechanisms in the generation of subthreshold oscillations and action potential clustering in entorhinal layer II stellate neurons.
abstract: A multicompartmental biophysical model of entorhinal cortex layer II stellate cells was developed to analyze the ionic basis of physiological properties, such as subthreshold membrane potential oscillations, action potential clustering, and the medium afterhyperpolarization. In particular, the simulation illustrates the interaction of the persistent sodium current (I(Nap)) and the hyperpolarization activated inward current (Ih) in the generation of subthreshold membrane potential oscillations. The potential role of Ih in contributing to the medium hyperpolarization (mAHP) and rebound spiking was studied. The role of Ih and the slow calcium-activated potassium current Ikappa(AHP) in action potential clustering was also studied. Representations of Ih and I(Nap) were developed with parameters based on voltage-clamp data from whole-cell patch and single channel recordings of stellate cells (Dickson et al., J Neurophysiol 83:2562-2579, 2000; Magistretti and Alonso, J Gen Physiol 114:491-509, 1999; Magistretti et al., J Physiol 521:629-636, 1999a; J Neurosci 19:7334-7341, 1999b). These currents interacted to generate robust subthreshold membrane potentials with amplitude and frequency corresponding to data observed in the whole cell patch recordings. The model was also able to account for effects of pharmacological manipulations, including blockade of Ih with ZD7288, partial blockade with cesium, and the influence of barium on oscillations. In a model with a wider range of currents, the transition from oscillations to single spiking, to spike clustering, and finally tonic firing could be replicated. In agreement with experiment, blockade of calcium channels in the model strongly reduced clustering. In the voltage interval during which no data are available, the model predicts that the slow component of Ih does not follow the fast component down to very short time constants. The model also predicts that the fast component of Ih is responsible for the involvement in the generation of subthreshold oscillations, and the slow component dominates in the generation of spike clusters.
authors.affiliation: Department of Numerical Analysis and Computer Science, Royal Institute of Technology, Stockholm, Sweden. erikf@nada.kth.se
authors.forename: Erik
authors.initials: E
authors.lastname: Fransén
authors.forename: Angel A
authors.initials: AA
authors.lastname: Alonso
authors.forename: Clayton T
authors.initials: CT
authors.lastname: Dickson
authors.forename: Jacopo
authors.initials: J
authors.lastname: Magistretti
authors.forename: Michael E
authors.initials: ME
authors.lastname: Hasselmo
mesh_terms: D000200:Action Potentials / Q000187:drug effects / Q000502:physiology*; D000818:Animals; D001464:Barium / Q000494:pharmacology; D001683:Biological Clocks / Q000187:drug effects / Q000502:physiology*; D002121:Calcium Channel Blockers / Q000494:pharmacology; D015220:Calcium Channels / Q000187:drug effects / Q000502:physiology; D002586:Cesium / Q000494:pharmacology; D003198:Computer Simulation / Q000706:statistics & numerical data; D018728:Entorhinal Cortex / Q000166:cytology / Q000502:physiology*; D006801:Humans; D007473:Ion Channels / Q000187:drug effects / Q000502:physiology*; D008959:Models, Neurological; D009474:Neurons / Q000187:drug effects / Q000502:physiology*; D018408:Patch-Clamp Techniques; D015221:Potassium Channels / Q000187:drug effects / Q000502:physiology; D011743:Pyrimidines / Q000494:pharmacology; D015222:Sodium Channels / Q000187:drug effects / Q000502:physiology
chemical_list: D002121:Calcium Channel Blockers; D015220:Calcium Channels; D007473:Ion Channels; D015221:Potassium Channels; D011743:Pyrimidines; D015222:Sodium Channels; C082246:ICI D2788; D002586:Cesium; D001464:Barium