100 results for "verbal memory" · page 5 of 10 · ranked by relevance
…influence the accessibility of working memory content". Analytic scripts for this project…
…influence the accessibility of working memory content". Analytic scripts for this project…
…See the Computational Memory Lab's [wiki page](https://memory.psych.upenn…
This dataset comprises preprocessed EEG recordings from 8 healthy subjects performing imagined speech tasks involving three vowel phonemes (a, i, u). Participants received auditory and visual cues to imagine speaking each vowel, with 64-channel EEG data acquired at 256 Hz. The dataset includes 2,400 base trials (8 subjects × 300 trials per subject) with 3 overlapping 2-second epochs extracted per trial, yielding 7,200 total epochs, analyzed using Riemannian manifold-based feature extraction and relevance vector machine classification for brain-computer interface applications. This is a MOABB (Mother of All BCI Benchmarks) benchmark collection dataset converted to BIDS format.
…As in the memory phase, at the onset of a trial, the…
This dataset combines high-density electroencephalography (128-channel HD-EEG) and mouse-tracking to examine dynamic decision-making processes in the human brain. Collected from 31 adults (ages 18-33), it includes resting-state and task-related EEG data acquired during food preference choices and semantic judgment tasks. The resource provides both raw and preprocessed EEG data with synchronized behavioral measures, enabling investigation of neural correlates underlying binary choice decisions.
…Each memory item was preceded by a central color cue (red, green…
This dataset comprises preprocessed EEG recordings from 6 healthy participants performing imagined speech discrimination tasks between short and long words ('cooperate' vs 'in'). Data were acquired at 256 Hz using 64 EEG channels with standard preprocessing including bandpass filtering (8-70 Hz), notch filtering (60 Hz), and artifact removal. The dataset contains 1,200 trials analyzed using Riemannian manifold and relevance vector machine approaches for brain-computer interface applications, achieving mean classification accuracy of 73.3±8.9%.
…nemar.on004942) Visuo-spatial working memory (VSWM) for sequences is thought to…
Visual Working Memory. Mostly unpublished! Beh data published here: 10.3758/s13415…