title: Network-specific mechanisms may explain the paradoxical effects of carbamazepine and phenytoin.
abstract: OBJECTIVE
  A common notion of the mechanism by which the antiepileptic drugs (AEDs) carbamazepine and phenytoin act is that they block sodium channels by binding preferentially to the inactivated state, thereby allowing normal neuronal firing while blocking ictal activity. However, these drugs have unpredictable efficacy and, in some cases, may exacerbate seizures. Previous studies have suggested that reducing sodium channel availability in the dentate gyrus (DG) paradoxically increases excitability. We used a biophysically detailed computer model of the DG to test the hypothesis that AEDs increase excitability by disproportionately reducing negative feedback mechanisms.
  
  
  METHODS
  We built a Markov model of sodium channel gating that reproduces responses to voltage clamp experiments in the presence of carbamazepine and phenytoin. We incorporated this validated Markov model into a biophysically realistic computer model of DG neurons and networks. Simulated drug concentrations were similar to those measured in cerebral spinal fluid in medicated patients. Single neuron models were stimulated with current injections, and networks were stimulated with perforant path synaptic input. In the network model, environmental effects were studied by introducing mossy fiber sprouting.
  
  
  RESULTS
  As expected, drugs reduced sodium channel availability, which in turn reduced action potential amplitude. This had only a small effect on action potential (AP) firing rate during brief (100 msec) current injections. Paradoxically, long current injections (2,500 msec) increased AP firing rates. This was caused by reduced calcium entry and consequently reduced activation of calcium activated potassium channels. It is important to note that the main determinant of drug effect was resting membrane potential (RMP) and not action potential firing rate. Binding of phenytoin and carbamazepine is slow and, thus drug effects are largely determined by the long term state of the RMP. This paradoxical AP firing increase was dependent on the unusually large calcium-activated potassium conductances expressed by DG granule cells. This predicts that drug efficacy in a given network will depend on the precise makeup of conductances in the network. RMP is expected to vary with the level of activity in the network. We simulated the effects of drugs on single shot stimulus responses in networks with mossy fiber sprouting and varied the RMP in all neurons as a model for network activity. For an RMP of -50 mV, representing an active network, drugs had no effect, or in some cases, increased excitability. Drugs had an increasingly larger inhibitory effect on network responses as RMP decreased. An important prediction is that drugs will be unable to block ictal activity invading an active network.
  
  
  CONCLUSIONS
  Our key findings are that drug effects depend on both intrinsic properties of the network and its behavioral state. This may explain the paradoxical and unpredictable effects of some AEDs on seizure control in some patients.
authors.affiliation: Florey Neuroscience Institutes, Parkville, Victoria, Australia. evan@evan-thomas.net
authors.forename: Evan A
authors.initials: EA
authors.lastname: Thomas
authors.forename: Steven
authors.initials: S
authors.lastname: Petrou
mesh_terms: D000200:Action Potentials / Q000187:drug effects; D000818:Animals; D000927:Anticonvulsants / Q000494:pharmacology*; D002220:Carbamazepine / Q000494:pharmacology*; D003198:Computer Simulation; D018891:Dentate Gyrus / Q000166:cytology; D008390:Markov Chains; D008954:Models, Biological; D009415:Nerve Net / Q000187:drug effects*; D009474:Neurons / Q000187:drug effects*; D010672:Phenytoin / Q000494:pharmacology*; D015222:Sodium Channels / Q000187:drug effects / Q000502:physiology; D013997:Time Factors
chemical_list: D000927:Anticonvulsants; D015222:Sodium Channels; D002220:Carbamazepine; D010672:Phenytoin
keywords: Carbamazepine; Computer simulations; Dentate gyrus; Epilepsy; Markov model; Mossy fiber sprouting; Phenytoin; Recurrent networks; Seizures; Sodium channels