D
Drausin Wulsin
Researcher at University of Pennsylvania
Publications - 18
Citations - 1570
Drausin Wulsin is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Epilepsy & Ictal. The author has an hindex of 11, co-authored 16 publications receiving 1398 citations. Previous affiliations of Drausin Wulsin include University of Washington.
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Journal ArticleDOI
Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo
Jonathan Viventi,Dae-Hyeong Kim,Leif Vigeland,Eric S. Frechette,Justin A. Blanco,Yun-Soung Kim,Andrew E. Avrin,Vineet Tiruvadi,Suk Won Hwang,Ann C. Vanleer,Drausin Wulsin,Kathryn A. Davis,Casey E. Gelber,Larry A. Palmer,Jan Van der Spiegel,Jian Wu,Jianliang Xiao,Yonggang Huang,Diego Contreras,John A. Rogers,Brian Litt +20 more
TL;DR: This system is used to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures, and it is found that seizures may manifest as recurrent spiral waves that propagate in the neocortex.
Journal ArticleDOI
Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement.
TL;DR: It is demonstrated how the unsupervised step of DBN learning produces an autoencoder that can naturally be used in anomaly measurement, and results indicate that DBNs and raw data inputs may be more effective for online automated EEG waveform recognition than other common techniques.
Proceedings ArticleDOI
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
TL;DR: It is shown that Deep Belief Nets, a type of multi-layer generative neural network, can be used effectively for EEG anomaly detection and can facilitate human review of large amounts of clinical EEG as well as mining new EEG features that may be indicators of unusual activity.
Journal ArticleDOI
Temporal changes of neocortical high-frequency oscillations in epilepsy
TL;DR: Temporal analysis of HFO features has potential for designing custom seizure prediction algorithms and for exploring the relationship between HFOs and seizure generation.
Journal ArticleDOI
Mining continuous intracranial EEG in focal canine epilepsy: Relating interictal bursts to seizure onsets
Kathryn A. Davis,Hoameng Ung,Drausin Wulsin,Joost B. Wagenaar,Emily B. Fox,Ned Patterson,Charles H. Vite,Gregory A. Worrell,Brian Litt +8 more
TL;DR: A long‐term iEEG dataset from canines with naturally occurring epilepsy is leveraged to investigate interictal bursts and their electrographic relationship to seizures.