{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T15:03:20Z","timestamp":1775833400974,"version":"3.50.1"},"reference-count":41,"publisher":"World Scientific Pub Co Pte Lt","issue":"07","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2018,9]]},"abstract":"<jats:p> Pathological High-Frequency Oscillations (HFOs) have been recently proposed as potential biomarker of the seizure onset zone (SOZ) and have shown superior accuracy to interictal epileptiform discharges in delineating its anatomical boundaries. Characterization of HFOs is still in its infancy and this is reflected in the heterogeneity of analysis and reporting methods across studies and in clinical practice. The clinical approach to HFOs identification and quantification usually still relies on visual inspection of EEG data. In this study, we developed a pipeline for the detection and analysis of HFOs. This includes preliminary selection of the most informative channels exploiting statistical properties of the pre-ictal and ictal intracranial EEG (iEEG) time series based on spectral kurtosis, followed by wavelet-based characterization of the time\u2013frequency properties of the signal. We performed a preliminary validation analyzing EEG data in the ripple frequency band (80\u2013250 Hz) from six patients with drug-resistant epilepsy who underwent pre-surgical evaluation with stereo-EEG (SEEG) followed by surgical resection of pathologic brain areas, who had at least two-year positive post-surgical outcome. In this series, kurtosis-driven selection and wavelet-based detection of HFOs had average sensitivity of 81.94% and average specificity of 96.03% in identifying the HFO area which overlapped with the SOZ as defined by clinical presurgical workup. Furthermore, the kurtosis-based channel selection resulted in an average reduction in computational time of 66.60%. <\/jats:p>","DOI":"10.1142\/s0129065718500016","type":"journal-article","created":{"date-parts":[[2018,1,15]],"date-time":"2018-01-15T04:43:07Z","timestamp":1515991387000},"page":"1850001","source":"Crossref","is-referenced-by-count":31,"title":["Kurtosis-Based Detection of Intracranial High-Frequency Oscillations for the Identification of the Seizure Onset Zone"],"prefix":"10.1142","volume":"28","author":[{"given":"Lucia Rita","family":"Quitadamo","sequence":"first","affiliation":[{"name":"School of Life and Health Sciences, Aston Brain Centre, Aston University, Birmingham, B4 7ET, UK"}]},{"given":"Roberto","family":"Mai","sequence":"additional","affiliation":[{"name":"Centro per la Chirurgia dell\u2019Epilessia \u201cClaudio Munari\u201d, Ospedale Ca\u2019 Granda-Niguarda, 20162 Milan, Italy"}]},{"given":"Francesca","family":"Gozzo","sequence":"additional","affiliation":[{"name":"Centro per la Chirurgia dell\u2019Epilessia \u201cClaudio Munari\u201d, Ospedale Ca\u2019 Granda-Niguarda, 20162 Milan, Italy"}]},{"given":"Veronica","family":"Pelliccia","sequence":"additional","affiliation":[{"name":"Centro per la Chirurgia dell\u2019Epilessia \u201cClaudio Munari\u201d, Ospedale Ca\u2019 Granda-Niguarda, 20162 Milan, Italy"}]},{"given":"Francesco","family":"Cardinale","sequence":"additional","affiliation":[{"name":"Centro per la Chirurgia dell\u2019Epilessia \u201cClaudio Munari\u201d, Ospedale Ca\u2019 Granda-Niguarda, 20162 Milan, Italy"}]},{"given":"Stefano","family":"Seri","sequence":"additional","affiliation":[{"name":"School of Life and Health Sciences, Aston Brain Centre, Aston University, Birmingham, B4 7ET, UK"},{"name":"Department of Clinical Neurophysiology, The Birmingham Children\u2019s Hospital NHS, F. 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