NEMAR Dataset nm000105: discrete_gestures - Discrete hand gesture detection from EMG
…findings that may have clinical relevance. The purpose of this is to…
The Penn Electrophysiology of Encoding and Retrieval Study (PEERS) characterizes behavioral and electrophysiological correlates of memory encoding and retrieval in highly practiced individuals. Across five PEERS experiments, more than 300 subjects contributed over 7,000 ninety-minute memory testing sessions with EEG. This dataset includes three free recall experiments: ltpFR (PEERS1-3), ltpFR2 (PEERS4), and VFFR (PEERS5).
…MATLAB structures (one-hot encoded vectors converted to class indices). For the…
The Finer-grained Affective Computing EEG Dataset (FACED) contains 32-channel scalp EEG from 123 healthy participants who watched 28 emotion-eliciting video clips targeting nine emotion categories (four negative, four positive, and neutral). Participants gave self-reported ratings on 12 dimensions, including discrete emotions, valence, arousal, liking, and familiarity. The dataset supports cross-subject affective computing and the development of EEG-based emotion recognition algorithms. This version is converted to BIDS with events annotated by video and emotion labels.
…promoting insights into the behavioral relevance of resting state brain activity. The…
ROAMM (Reading Observed At Mindless Moments) is a multimodal dataset of simultaneous EEG and eye-tracking recordings from 44 participants during naturalistic reading, with span-level mind-wandering annotations collected through a retrospective self-report paradigm. It serves as a benchmark for mind-wandering detection and EEG-to-text decoding, and supports research on how attention lapses degrade language decoding from brain activity. Synchronized machine-learning-ready data, reading stimuli and page-level comprehension scores are included.
…a whole-head Elekta Neuromag Vector View 306 MEG system (Neuromag Elekta…
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.
…feature matrix, and the label vector is the recalled status of the…