Quadratic binary programming and dynamical system approach to determine the predictability of epileptic seizures

Epilepsy is one of the most common disorders of the nervous system. The pro gressive entrainment between an epileptogenic focus and normal brain areas results to transitions of the brain from chaotic to less chaotic spatiotemp oral states, the epileptic seizures. The entrainment between two brain site s can be quantified by the T-index from the measures of chaos (e.g., Lyapun ov exponents) of the electrical activity (EEG) of the brain. By applying th e optimization theory, in particular quadratic zero-one programming, we wer e able to select the most entrained brain sites 10 minutes before seizures and subsequently follow their entrainment over 2 hours before seizures. In five patients with 3-24 seizures, we found that over 90% of the seizures ar e predictable by the optimal selection of electrode sites. This procedure, which is applied to epilepsy research for the first time, shows the possibi lity of prediction of epileptic seizures well in advance (19.8 to 42.9 minu tes) of their occurrence.