Journal of neuroscience methods · 2024
The "Twin Peaks" method of automated Spike-Wave detection: A two-step, two-criteria Matlab application.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Iotchev Ivaylo Borislavov, Perevozniuk Dmitrii Andreevitch, Lazarenko Ivan, Perescis Martin F J, Sitnikova Evgenia, van Luijtelaar Gilles
Аннотация
BACKGROUND: 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.
NEW METHOD: 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.
RESULTS: 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.
COMPARISON WITH EXISTING METHODS: 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.
CONCLUSION: 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.
NEW METHOD: 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.
RESULTS: 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.
COMPARISON WITH EXISTING METHODS: 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.
CONCLUSION: 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.