The "Twin Peaks" method of automated Spike-Wave detection: A two-step, two-criteria Matlab application

There are many automated spike-wave discharge detectors, but the known weaknesses of otherwise good methods and the varying working conditions of different research groups (mainly the access to hardware and software) invite further exploration into alternative approaches.

The algorithm combines two criteria, one in the time-domain and one in the frequency-domain, exploiting morphological asymmetry and the presence of harmonics, respectively. The time-domain criterion is additionally adjusted by normal modelling between the first and second iterations.

We report specificity, sensitivity and accuracy values for 20 recordings from 17 mature, male WAG/Rij rats. In addition, performance was preliminary tested with different hormones, pharmacological injections and species (mice) in a smaller sample. Accuracy and specificity were consistently above 91 %. The number of automatically detected spike-wave discharges was strongly correlated with the numbers derived from visual inspection. Sensitivity varied more strongly than specificity, but high values were observed in both rats and mice.

The algorithm avoids low-voltage movement artifacts, displays a lower false positive rate than many predecessors and appears to work across species, i.e. while designed initially with data from the WAG/Rij rat, the algorithm can pick up seizure activity in the mouse of considerably lower inter-spike frequency. Weaknesses of the proposed method include a lower sensitivity than several predecessors.

The algorithm excels in being a selective and flexible (based on e.g. its performance across rats and mice) spike-wave discharge detector. Future work could attempt to increase the sensitivity of this approach.