…Bayesian optimization, individual experimental parameters, brain-computer interfaces, learning from small data…
MEG recordings from participants performing a localizer task and a risky decision-making task, used to study how heuristics in risky choice relate to preferential neural representation of information. The dataset includes raw MEG with photodiode-derived event timing, event information tables, and preprocessed epoched data for the localizer and choice phases.
EEG-BIDS dataset of cue-locked EEG recordings and event annotations from 43 neurotypical adults performing a random-dot kinematogram motion discrimination task. The task dissociates low-level priors (implicitly learned tone-motion contingencies) from high-level priors (a cover story about tinted glasses) against a neutral baseline. The data support analyses of hierarchical priors with signal detection theory, drift-diffusion modeling, and occipital oscillatory and aperiodic EEG activity, alongside psychosis-proneness and psychological flexibility questionnaires.
…Bayesian optimization, individual experimental parameters, brain-computer interfaces, learning from small data…
EEG recordings from 122 college-age participants performing a probabilistic selection task, with participants scoring reliably high or low on the Beck Depression Inventory. Data were collected around 2008-2010 in the John J.B. Allen lab at the University of Arizona to study reward and punishment processing in depression. Analysis code to reproduce the associated publication is included.
…The original study investigated a fully automated trial selection method for optimization…
…invasive closed-loop stimulus timing optimization". This experiment constitutes the non-invasive…
EEG dataset of multiband auditory brainstem responses (ABRs) derived from continuous 'peaky' speech, collected to identify optimal stimulus parameters. Experiment 1 compares zero-phase and chirp-phase speech profiles in normal-hearing adults, and Experiment 2 compares narrators with different fundamental frequencies (natural versus shifted to 100 Hz). Data include raw BrainVision EEG recordings, event files, and HDF5 stimulus and regressor files for deconvolution.
[ recordings from participants with major depressive disorder and non-depressed controls performing a probabilistic selection reinforcement learning task. The dataset was collected to examine the Reward Positivity and related ventromedial frontal cortex activity during feedback processing. It includes 90 participants, 52 with MDD and 38 controls, all screened using the SCID interview. T1 anatomical and resting-state data are planned to be added in a later release. Associated publication: Pirrung, C.J.H., Singh, G., Hogeveen, J., Quinn, D. & Cavanagh, J.F. (2025), Hypoactivation of ventromedial frontal cortex in major depressive disorder: an MEG study of the Reward Positivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging.