Showing 10 of 581 datasets · page 26 of 59
This dataset contains intracranial EEG (iEEG) recordings from 8 patients undergoing single pulse electrical stimulation, collected to characterize electrical stimulation-driven network interactions within the human limbic system. The data support investigations into connectivity and evoked responses in the human brain and were formatted according to the BIDS standard.
TNO (Task-Negative Oscillations) is an EEG dataset containing resting-state and task-based electroencephalography recordings. The dataset includes EEG data collected during cognitive tasks and resting-state conditions, organized in BIDS format with data files in EEGLAB format (.set/.fdt files) and accompanying metadata in BIDS-compatible formats (JSON, TSV). This dataset is designed to investigate neural oscillations and their relationship to task engagement and cognitive processing. The dataset comprises recordings from multiple subjects performing standardized cognitive tasks and resting-state sessions, with complete event annotations and electrode location information.
This dataset comprises multimodal physiological and behavioral recordings (EEG, EOG, ECG, EDA, and gaze tracking) collected during a semi-automated driving task designed to study trust in automation (TiA). Participants performed lane maintenance, following distance, and collision avoidance tasks under varying levels of autonomous driving assistance, with the aim of developing quantitative metrics that predict and track changes in operator trust. The research supports the development of psychophysiology-based indicators for real-time trust monitoring in human-autonomy interaction, relevant to military vehicle survivability and human factors research.
This dataset comprises intraoperative intracranial EEG recordings from 10 patients undergoing brain tumor resection in the perirolandic region. Median nerve somatosensory evoked potentials (SEP) were recorded simultaneously using two 4-contact ECoG electrode strips with different impedance characteristics (low impedance: 3.4 kΩ and high impedance: 6.9 kΩ) to investigate the efficacy of low-impedance electrodes for detecting high-frequency oscillations in clinical neurophysiology.
This dataset comprises continuous EEG recordings from 48 infants (5-10 months old) during passive viewing of relaxing videos, collected to establish reliability metrics for microstate analysis in infant populations. The study demonstrates microstate analysis methodology applied to infant EEG data and provides a tutorial resource for researchers interested in this analytical approach. Data were acquired using a 128-channel geodesic sensor net at 1000 Hz sampling rate.
This dataset contains EEG recordings collected to investigate whether hypervigilance to social threats can be dissociated from altered perceptual decision-making in individuals experiencing loneliness. Event-related potentials and Drift Diffusion Modelling were used to examine the neural and cognitive mechanisms underlying social threat processing and decision-making in this population.
This dataset comprises high-density, dual-layer EEG, neck EMG, IMU acceleration, ground reaction force, and structural MRI-derived head model data from 32 young adult participants walking over uneven terrain and at varying speeds. Each participant completed two three-minute trials per condition along with a seated rest trial. The dataset is designed to support research on the neural and biomechanical correlates of walking balance and gait adaptation on irregular surfaces.
This dataset comprises intracranial EEG recordings collected using the CorTec BrainInterchange implantable device and the BCI2000 software platform, developed as part of an ecosystem of technology and protocols for adaptive neuromodulation research in humans. The data support research into closed-loop neuromodulation approaches and adaptive brain-computer interface systems. Recordings were obtained under IACUC-approved protocols in collaboration with Mayo Clinic and academic partners.
This dataset comprises EEG/ERP recordings collected from a sample of healthy adults performing multiple cognitive tasks, including an extended multi-source interference task (MSIT+), a 3-stimuli oddball task, a control simple reaction task (SRT), and a resting-state protocol. It is intended to support research on cognitive control, attention, and resting-state brain dynamics using electrophysiological methods.
This dataset contains EEG recordings from 37 healthy adult subjects who completed a novel visual contextual trajectory paradigm (CTP) designed to probe predictive processing of attribute-specific violations. Stimuli involved a bound object whose brightness, size, or orientation could deviate from an established trajectory, with control trials containing no violation. The dataset supports investigation of attribute-specific prediction error responses in the visual system.