Costa F, Krayenbühl N, Ramantani G, Boran E, König K, Sarnthein J

Dataset of BCI2000-compatible intraoperative ECoG with neuromorphic encoding Online

2024.

Dimakopoulos V, Mégevand P, Stieglitz L, Imbach L, Sarnthein J

Dataset of intracranial EEG, scalp EEG and beamforming sources from human epilepsy patients performing a verbal working memory task Online

2023.

Dimakopoulos V, Neidert MC, Sarnthein J

Intraoperative recordings of medianus stimulation with low and high impedance ECoG Online

2023.

Dimakopoulos V, Selmin G, Regli L, Sarnthein J

Intraoperative SEP with stimulation rates 2.7-28.7 Hz Online

2023.

Boran E, Hilfiker P, Stieglitz L, Sarnthein J, Klaver P

Dataset of human medial temporal lobe neurons during a visual working memory task Online

2022, visited: 31.03.2022.

Cserpan D, Boran E, Rosch R, Lo Biundo SP, Ramantani G, Sarnthein J

Dataset of EEG recordings of pediatric patients with epilepsy based on the 10-20 system Online

2021.

Fedele T, Boran E, Chirkov V, Hilfiker P, Grunwald T, Stieglitz L, Jokeit H, Sarnthein J

Dataset of spiking and LFP activity invasively recorded in the human amygdala during aversive dynamic stimuli Journal Article

In: Scientific Data, vol. 8, no. 1, pp. 9, 2021.

Boran E, Fedele T, Steiner A, Hilfiker P, Stieglitz L, Grunwald T, Sarnthein J

Dataset of human medial temporal lobe neurons, scalp and intracranial EEG during a verbal working memory task Journal Article

In: Scientific Data, vol. 7, no. 1, pp. 30, 2020.

Boran E, Sarnthein J, Krayenbühl N, Ramantani G, Fedele T

Dataset of pre- and postsurgical EEG recorded from epilepsy patients and HFO markings Online

2019.

Boran E, Ramantani G, Krayenbuhl N, Schreiber M, Konig K, Fedele T, Sarnthein J

Dataset of intraoperative pre- and post-resection ECoG recorded from epilepsy patients and fast ripple (FR) markings Online

2019.

Fedele T, Burnos S, Boran E, Krayenbühl N, Hilfiker P, Grunwald T, Sarnthein J

interictal iEEG during slow-wave sleep with HFO markings Online

2017.

Automated HFO detection

Our automated HFO detector is available in github.
https://github.com/ZurichNCH/Automatic-High-Frequency-Oscillation-Detector

Recently this HFO detector was implemented in Python (by Adam Li) and supports BIDS datasets.
https://github.com/mne-tools/mne-hfo

We are also detecting HFO using a Spiking Neural Network. The detector is now available in github.
https://github.com/kburel/SNN_HFO_iEEG
https://zenodo.org/record/4701467

Automated HFO detection in scalp EEG

Verbal working memory task

In each trial, subjects are instructed to memorize a set of four, six, or eight letters presented for 2 s (encoding). The number of letters is thus specific for the memory load. After a delay (maintenance) period of 3 s, a probe letter prompts the subjects to retrieve their memory (retrieval) and to indicate by button press (“IN” or “OUT”) whether or not the probe letter was a member of the letter set held in memory

http://www.neurobs.com/ex_files/expt_view?id=266

Visual working memory task

In each trial, subjects are instructed to memorize an array of 1, 2, 4 or 6 colored squares (memory array) simultaneously presented for 0.8 s (encoding). The number of squares is thus specific for the memory load. After a delay (maintenance) period of 0.9 s, a probe array of the same size prompts the subjects to indicate by button press (“Same” or “Different”) whether the array was identical to the memory array (test). This cognitively demanding task involves internal processing in the absence of external stimuli during maintenance.

https://www.neurobs.com/ex_files/expt_view?id=285

Fearful faces task

The videos are all silent and consist of dynamic fearful faces and dynamic neutral landscapes, presented in an alternating order, in a block design. The paradigm includes eight blocks of 75 short video clips (2–3 s) of fearful faces and nine blocks of 72 short video clips (2–3 s) of neutral landscapes. Each block lasts 24 s in total, and contains short video clips without any intermission between consecutive videos. Video clips of fearful faces are extracted from thriller and horror movies and contain faces of actors showing fear, without being violent or aggressive. Video clips of neutral landscapes are chosen as a control condition, and are matched to the duration of the fearful faces videos (2–3 s). They include domestic landscapes which are posited to have a low emotional content and visual properties comparable to the emotional videos. All videos are only included once.

https://www.neurobs.com/ex_files/expt_view?id=283