Tonic-Clonic Transitions in Computer Simulation

William W. Lytton, Ahmet Omurtag
2007 Journal of clinical neurophysiology  
Network simulations can help identify underlying mechanisms of epileptic activity that are hard to isolate in biologic preparations. To be useful, simulations must be sufficiently realistic to make possible biologic and clinical prediction. This requirement for large networks of sufficiently detailed neurons raises challenges both with regard to computational load and the difficulty of obtaining insights with large numbers of free parameters and the large amounts of generated data. The authors
more » ... ave addressed these problems by simulating computationally manageable networks of moderate size consisting of 1,000 to 3,000 neurons with multiple intrinsic and synaptic properties. Experiments on these simulations demonstrated the presence of epileptiform behavior in the form of repetitive high-intensity population events (clonic behavior) or latch-up with near maximal activity (tonic behavior). Intrinsic neuronal excitability is not always a predictor of network epileptiform activity but may paradoxically produce antiepileptic effects, depending on the settings of other parameters. Several simulations revealed the importance of random coincident inputs to shift a network from a low-activation to a high-activation epileptiform state. Finally, a simulated anticonvulsant acting on excitability tended to preferentially decrease tonic activity. (J Clin Neurophysiol 2007;24: 175-181) From the * †Departments of Physiology, Pharmacology, and *Neurology, SUNY Downstate, Brooklyn, NY. FIGURE 4. Activity in NetB simulation with no inhibition. Field potential for expressors is superimposed on the raster plot. Voltage traces for two expressors are shown at bottom. FIGURE 5. Latch-up occurring late in a simulation with augmentation of expressor ¡ expressor NMDA strength. FIGURE 7. Reduction of bursting in ACD simulation with repeated plateau inputs of increasing duration. Top, control; bottom, ACD effect. FIGURE 6. Feedback inhibition from expressors ¡ inhibitors ¡ expressors more cleanly carves out episodes of activation.
doi:10.1097/wnp.0b013e3180336fc0 pmid:17414973 pmcid:PMC2633473 fatcat:gspv5dw5jfbmpeqq4owvhcjg2i