…Task included in Matlab programming language. Data collected circa 2015 in Cognitive…
This derivative dataset redistributes, unchanged, 20 per-patient feature tables computed from the Freiburg intracranial EEG database for epilepsy analysis. Each row is a 2-s sliding window (1-s step) with 1080 univariate and bivariate features, extracted from six electrodes (three in the epileptic focus, three outside it) across six frequency bands. Windows are labelled as pre-ictal, ictal, post-ictal or inter-ictal, so the tables can be used to train machine-learning models for seizure detection. No raw recordings are included.
…Large-scale replication study reveals a limit on probabilistic prediction in language…
This dataset contains raw EEG recordings, in BrainVision format and organized according to BIDS, from participants silently reading word-by-word naturalistic narratives. It accompanies a study of auditory representations of words evoked during silent visual reading. Derivatives include preprocessed word-level EEG epochs, story and run metadata, expected/unexpected epoch labels, and corresponding feature embeddings.
…Task included in Matlab programming language. Data collected circa 2012-2013 in…
…Task included in Matlab programming language, with instructions for eyes open & eyes…
…hospital's ethics committee. ## Processing No signal processing. The ictal EDF files…
Intracranial EEG and behavioral event data from a paired associates learning task in which participants studied pairs of visually presented words, solved arithmetic distractor problems, and then performed cued recall. Data were collected from clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania. Recordings include monopolar and bipolar iEEG with subject-specific electrode montages, MNI/Talairach coordinates, and brain region annotations.
…Task included in Matlab programming language. Data collected 2016-2018 in the…
MEG-SCANS provides raw and MaxFiltered magnetoencephalography recordings from 24 German-speaking participants who listened to about one hour of auditory stimuli. The stimuli were two audiobooks, 120 Oldenburg Matrix Sentence Test (OLSA) sentences at varying intelligibility levels, and short up-chirps for signal quality assessment. The dataset also includes empty-room recordings, structural MRI, audiograms, speech reception threshold results, and audio stimulus material. It is organized in BIDS and intended as a benchmark for encoding and decoding analyses of brain responses to speech.