Human MEG recordings during sequential conflict task
[ recordings from 13 healthy subjects performing a visual matrix speller task using a calibrationless brain-computer interface approach. The study introduces learning from label proportions (LLP), an unsupervised classification method that exploits known target/non-target stimulus ratios to enable online BCI operation without prior calibration. Subjects performed copy-spelling tasks using a 6×7 character grid across three sessions, achieving 84.5% character accuracy without labeled training data.
[ and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.
[ recordings from a visual search task conducted across three undergraduate institutions. Data were collected from participants in 2017-2018 and represent a component of the ERP CORE resource for standardized human electrophysiological research. The dataset includes demographic information and is designed to facilitate investigation of the N2pc component, a neural marker of attentional selection during visual search.
…from altered perceptual decision-making processes in lonely individuals? An exploration with…
This dataset comprises EEG recordings from 20 subjects performing a sustained attention task involving mental concentration on a target stimulus. Participants received automated verbal instructions guiding them through cycles of relaxation, preparation, and 15-second concentration periods, with the entire experiment conducted with eyes closed. The dataset includes 20 repetitions of the attention task per participant and is annotated using HED (Hierarchical Event Descriptors) version 8.0.0.
…These results have potential implications for optimizing the current cognitive training on…
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