Quantifying cognitive effort's impact on suppression of epilepsy-associated after discharges

Epilepsy affects over 50 million people worldwide, with approximately 30% of patients experiencing seizures that are resistant to medication, significantly impacting their quality of life. In this study, we analyze a unique dataset of intracranial electroencephalography (iEEG) recordings from patients undergoing functional brain mapping prior to epilepsy surgery. During this procedure, electrodes are implanted to identify critical brain regions, and brief pulse electrical stimulation is applied. Often, abnormal brain activity, known as epilepsy-associated after discharges (EAADs), are triggered by stimulation. During these events, patients are engaged in cognitive tasks to exert mental effort, such as solving arithmetic and spelling problems, as a potential method to suppress EAADs. We present evidence that exerting mental effort to perform cognitive tasks can suppress EAADs. Using detrended fluctuation analysis (DFA), multifractal DFA (MFDFA), and fractional-order dynamical network models (FODN), we characterize the temporal and spatial dynamics of iEEG data during these events to identify conditions and classify the trials under which cognitive effort is most effective to suppress EAADs. Our logistic regression model achieves an average accuracy of 77% using leave-one-out cross-validation. Our findings pave the way for a promising, non-invasive therapeutic avenue for managing epileptic activity through targeted cognitive activation. Our work lays the groundwork for novel brain-state modulation strategies for the treatment of epilepsy.