Showing 10 of 755 datasets · page 7 of 76
This dataset contains intracranial EEG recordings from 110 individuals who performed a visual-naming task, with electrode coordinates provided in MNI-305 space. It was collected to support analyses of effective connectivity underlying speech and language processing, as reported by Kochi et al. (2025). Each recording is annotated with event codes marking stimulus and response onsets.
This dataset contains intracranial EEG recordings from 121 individuals who performed an auditory-naming task, with electrode coordinates provided in MNI-305 space. The data support analyses of whole-brain, millisecond-scale effective connectivity underlying speech processing, as reported by Kochi et al. (2025).
This dataset comprises EEG recordings from 41 participants collected to investigate the effects of rhythmic visual stimulation on experimental pain perception. The study was conducted at Université Laval in Quebec, Canada, and examines whether rhythmic visual stimulation modulates pain-related neural responses. The dataset includes raw EEG data and associated metadata from a controlled experimental protocol designed to test pain perception under different visual stimulation conditions. This is a derived dataset based on OpenNeuro ds006897.v1.0.0.
A longitudinal wireless subdural electrocorticography (ECoG) dataset from two fully implanted macaque monkeys (Macaca fuscata), organized in BIDS-iEEG format. The dataset comprises multiple recording sessions acquired weekly using an inductively powered wireless implant during rest and task-based conditions (pressing, reaching, listening, and sensorimotor tasks). This resource enables reproducible research in primate neurophysiology and brain-computer interface development. The dataset was independently curated and reorganized from in-house raw recordings (.bin files) using a custom BIDS converter. The original in-house raw recordings that served as the source for this BIDS-organized dataset are not publicly released. While a related version exists on OpenNeuro (ds006890), this dataset represents an independently maintained BIDS reorganization of the original in-house recordings.
This dataset contains 64-channel EEG recordings and behavioral ratings from 148 healthy adults performing an Emotion Processing and Regulation task using static emotional images. The study examines discrepancies between self-reported and neurophysiological socio-affective responses in relation to loneliness, using a factorial design manipulating stimulus content (social/non-social) and regulation instructions (watch-neutral, watch-negative, reappraise-negative). Participants rated arousal and valence after viewing each stimulus, enabling analysis of the relationship between subjective and physiological emotional responses.
This dataset comprises EEG and behavioral recordings from a study examining the effects of transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex on emotion processing and regulation in lonely individuals. 120 participants completed two sessions (sham and active stimulation) involving an emotion regulation task with static social and non-social images, rated on arousal and valence. The dataset includes raw EEG, behavioral ratings, and derived ERP data, along with questionnaires assessing side effects and blinding effectiveness.
This dataset contains continuous EEG, ECG, and EDA recordings from 63 participants who viewed and rated Streetview images of urban environments across nine subjective scales (e.g., valence, safety, beauty). The study aims to investigate how urban environmental features influence subjective appraisal and neural responses such as stimulus-locked ERPs. Data were collected in 2024 at the BeMoBIL lab, TU Berlin.
This dataset comprises raw 64-channel EEG, ECG, PPG, and behavioral data collected from 30 healthy young adults during resting-state and verbal working memory tasks. Participants completed a digit-span serial recall task under four stimulus presentation modes (simultaneous, fast, fast+delay, and slow sequential), enabling investigation of neural and physiological correlates of encoding, maintenance, and retrieval. The dataset supports research on working memory load classification and the relationship between oscillatory brain activity, autonomic signals, and behavioral performance.
This dataset comprises EEG and hand kinematics data recorded during an intention-action conflict paradigm, in which participants performed hand movements while cognitive intention and executed action were experimentally manipulated. The data are intended to support research into the neural and behavioral correlates of intention-action conflict. Data were organized into BIDS format for public sharing and analysis.
This dataset comprises 32-channel EEG recordings collected during a sham neurofeedback experiment conducted in a virtual reality environment. Participants underwent four conditions—positive feedback, negative feedback, control, and resting-state (eyes open/closed)—designed to examine how feedback valence influences alpha-band activity during an attentional task. The data were originally recorded in NeuroScan .cnt format and converted to BIDS using MNE-BIDS.