Partial directed coherence analysis of intracranial neural spikes in epilepsy patients
Intracranial electroencephalograms (EEG) provide a direct observation of neural activity by placing an electrode array on the cortical surface near the suspected epileptic foci. The neural spikes appeared during inter-ictal stages are mainly produced by abnormal neural discharges from epileptic foci. The topological mapping of spikes' potentials is commonly used to identify the epileptogenic zone. However, the propagations among multi-channel spikes are also important to identify the epileptic source activity. In addition, the changes of source activities in a series of consecutive spikes reveal the time-varying neural activations during discharge process, which provide alternative information for interpreting epileptic source activity. This paper proposes a spike classification based on the similarity of phase-space features to select candidate spikes from the intracranial EEGs recorded from an 8×8 electrocorticogram grid. Then, the partial directed coherence (PDC), which can provide the flow of source activity, at each spiking time point is computed. The outflow PDCs of all electrodes are therefore displayed on the grid. Our result showed that the derived source activities in the preceding spikes had high concentrated distributions but decreased in latter spikes. This implied the epileptic discharges were initially induced by a small-area cortex neurons and then spread out.