Intracranial EEG (iEEG) dataset titled 'Neural spatial volatility', collected by Kuroda, Asano, Nakasato and colleagues, with ethics approval from the IRBs of Wayne State University and Tohoku University. The dataset is organized in BIDS format and mirrored on NEMAR from its original OpenNeuro deposit (ds006107).
Intracranial EEG (iEEG) recordings from 7 participants undergoing closed-loop, theta-synchronized stimulation of human hippocampal networks. The dataset accompanies a study showing that closed-loop control of theta oscillations enhances hippocampal network connectivity. Recordings are segmented into pre- and post-stimulation evoked potentials, pre- and post-stimulation rest, closed-loop stimulation, and control stimulation periods.
This dataset contains electrocorticography (ECoG) recordings from two human participants viewing visual stimuli, including high-contrast vertical gratings and noise patterns with different spatial frequencies and spectral power distributions. Participants fixated on a central dot that changed color at random times. The data were used to study stimulus dependence of gamma oscillations and the relationship between neuronal synchrony, BOLD response, and the local field potential in human visual cortex.
An intracranial EEG (iEEG) dataset recorded from ten epilepsy patients undergoing invasive monitoring for seizure localization. Participants played five sessions of Speed Match, a visuomotor game on the Lumosity platform, during interictal recording. Continuous iEEG recordings are provided in EDF format with channel information and event markers for finger tapping.
Invasive epidural recordings from the cervical spinal cord of eight patients with neuropathic pain and implanted epidural electrodes, collected to test whether temporal expectation alters initial sensory processing in the human spinal cord. Participants received median nerve stimulation preceded by an auditory cue, with the cue-to-stimulus interval either fixed (1100 ms) or randomly varied (100-2100 ms) in alternating blocks. Participants silently counted rare double-stimulus trials (80 ms ISI).
This dataset contains resting-state stereo-electroencephalography (SEEG) recordings from two patients with epilepsy, acquired with implanted depth electrodes. It is provided in BIDS format as raw intracranial EEG data.
Raw electrophysiological recordings from a color change detection task, a visual working memory paradigm. The dataset is organized in BIDS format and is available through OpenNeuro and NEMAR. The README provides little detail on the participants or the acquisition, so the description is limited to what the dataset name and metadata state.
The "Podcast" electrocorticography (ECoG) dataset captures intracranial neural activity from 9 participants (1,330 grid, depth, and strip electrodes) who listened to a 30-minute naturalistic story containing over 5,000 words. It includes raw recordings, a minimally preprocessed high-gamma version, the auditory stimuli, an aligned word-level transcript, and linguistic features ranging from acoustic properties to large language model embeddings. Tutorials replicating prior findings are provided to support research on natural language comprehension.
This dataset contains behavioral events and intracranial electrophysiology (iEEG) recordings from a categorized free recall task with closed-loop electrical stimulation during encoding. Participants studied lists of semantically categorized words, completed arithmetic distractors, and freely recalled the words. Stimulation was triggered by a classifier trained on each participant's prior encoding data to predict subsequent recall. Data were collected at multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania.
This dataset contains behavioral events and intracranial EEG recordings from a delayed free recall task with closed-loop electrical stimulation delivered during word encoding. A logistic regression classifier trained on participants' prior free recall sessions predicts subsequent recall from encoding-period neural activity, and stimulation is triggered when predicted recall is low. Data were collected at multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania.