Spell-IT-Out
…4. **Syllabification**: a three-dot countdown (`pre_syllabification_dot`, 0.6 s…
- Participants
- 25
- Channels
- 61 (10-10)
- Citations
- 1
- Size
- 70.9 GB
- Version
- v1.0.0
- Updated
- Nov 2, 2026
…4. **Syllabification**: a three-dot countdown (`pre_syllabification_dot`, 0.6 s…
A magnetoencephalography (MEG) dataset from a frequency-tagging study of syntactic structure and lexical properties in language processing. The recordings are organized in BIDS format and are intended for investigating neural tracking of linguistic structure.
EEG dataset recorded during rapid serial visual presentation (RSVP) of sentences with flanking words, in which the critical center word was shown between grey flanker words. Sentences contained subject-verb agreement violations, semantic violations, double violations, word-order violations, or no violation (controls). The dataset supports research on sentence processing and parafoveal word processing during reading.
Raw MEG dataset with T1-weighted anatomical scans and behavioural logfiles from an audiovisual speech memory experiment. Participants completed repeated blocks of encoding (audiovisual synchrony detection on speech movies), a distractor task, and cued retrieval of the auditory speech associated with a speaker's face. The data support analyses of neocortical and hippocampal theta oscillations in audiovisual integration and memory replay.
SMN4Lang is a synchronized multimodal neuroimaging dataset for studying brain language processing. It contains fMRI and MEG recordings from the same 12 participants listening to about 6 hours of naturalistic Mandarin Chinese stories. It also includes structural T1/T2, diffusion MRI, resting-state fMRI, and linguistic annotations of the stimuli such as word frequencies, part-of-speech tags, syntactic trees, time-aligned characters and words, and word embeddings.
This dataset contains EEG recordings from deaf readers who read sentences containing semantic and syntactic violations, used to assess sensitivity to semantic and syntactic information during reading. Event-related potentials were recorded while participants viewed 180 sentences presented word by word, including subject-verb agreement, semantic, double, and word-order violations alongside correct control sentences.
EEG dataset investigating visuo-spatial working memory (VSWM) for sequences during a computerized spatial span task in younger and older healthy adults. The study examines whether theta and gamma oscillatory dynamics reflect item-level sequence encoding and recall, and how these processes change in healthy cognitive aging. Results indicate that later gamma power during encoding and theta-gamma phase amplitude coupling during recall track serial position, and may be preserved with aging.
High-density (256-channel) electrocorticography (ECoG) recorded at the University of California, San Francisco, from epilepsy patients reading aloud consonant-vowel syllables. The dataset includes 31 recording blocks from four subject codes, with hand-marked annotations of syllable onset, consonant-vowel transition and offset, plus rest baselines and anatomical electrode labels. It supports study of the functional organization of human ventral sensorimotor cortex during speech articulation and is organized as iEEG-BIDS with the original NWB files.
This dataset contains EEG recordings from phoneme discrimination tasks combined with transcranial magnetic stimulation (TMS) of the motor cortex. It merges two studies: a 2019 study of consonant-vowel and vowel-consonant pairs in 8 participants, and a 2021 study in 16 participants that added single phonemes, real words and pseudowords. It is intended to support research on speech decoding and the role of articulation and coarticulation in speech perception.
Magnetoencephalography (MEG) recordings from participants listening to 16-item binary sound sequences of varying complexity, used to test a language-of-thought account of compression in human working memory. Sequences were defined by minimal description length (transition probabilities, chunking, or nested structures), and occasional deviant sounds probed participants' knowledge of each sequence. The data accompany a study reporting that MEG and fMRI responses scale with sequence complexity.