Abstracts

Rationale:
Although plastic adaptation is well known to modulate seizure susceptibility, the role of different types of neuroplasticity in shaping epileptiform activity has received little attention to date. For example, homeostatic plasticity mechanisms ideally function as a set of regulatory mechanisms to maintain neuronal excitability levels within physiologically normal boundaries following different normal and pathological perturbations. If the dynamic of these neuroplasticity responses does not adequately match the time course of the perturbations, they may fail to regulate neural excitability within the physiological ranges and may even become maladaptive in pathological conditions.

Methods:
To investigate the role of different neuroplasticity mechanisms in the emergence of hyperexcitable states, we developed a Hodgkin-Huxley based model with homeostasis and a range of short and long term plasticity rules. We created a three-dimensional parameter space using potentiation and depression parameters and homeostasis set point. To create the parameter space, we varied each of these parameters within their physiological ranges and input a background excitation to the model and calculated changes in the network excitability as the ratio of the average excitatory firing rates before and after the application of excitatory input. A permutation test was conducted on shuffled firing rate data to determine the level of significance for identifying increased excitability. In the parameter space, using unsupervised clustering, we identified parameter ranges that contribute to the emergence of excitable states. To validate the model, we used our existing database of human microelectrode (Utah array) recordings that include interictal discharges from patients with medically intractable focal epilepsy. More specifically, to validate model predictions we used firing rate measure and network motif-classes. Network motif-classes were identified using a novel analysis method based on the triple correlation uniqueness theorem.

Results:
Within specific regions in the parameter space, the model generated spontaneous epileptifom events. Firing rate and bursting events increased when there was neuroplasticity maladaptation (e.g., when parameter settings for the plasticity rules induced stronger potentiation than depression). To validate our modeling work, we compared the firing rate and network motif-classes between model output and samples of interictal discharges from our existing dataset of human microelectrode recordings. Moreover, to simulate a chronic epileptic condition, we increased the set point of the homeostasis rule which regulates the neural intrinsic excitability and resting membrane potential. Our findings showed a gradual increase in the frequency of the interictal and seizure like events correlated with the increase in the set point of the homeostasis rule.

Conclusions:
Our results provide a detailed picture of the two-way interaction between plasticity rules and the generation of epileptic hyperexcitable events. A transition in the parameter space toward more pronounced plasticity maladaptation was identified in association with increased excitability.

Funding: NIH R01 NS084142, NIH R01 NS110669.