Schedule of Events | Search Abstracts | Symposia | Invited Symposia | Poster Sessions | Data Blitz Sessions

Poster E37

Cognitive electrophysiology and big data: advancing science through open-source, standardized data

Poster Session E - Monday, April 15, 2024, 2:30 – 4:30 pm EDT, Sheraton Hall ABC

Haydn Herrema1 (, Joseph Rudoler1, Michael Kahana1; 1University of Pennsylvania

In human cognitive electrophysiology, many studies contain low numbers of subjects, largely due to the financial and logistical difficulties involved in collecting EEG. Intracranial recordings of the brain are particularly uncommon, given the small subset of the population requiring invasive neural implants for medical treatment. Nonetheless, there exists an increasing recognition that large sample sizes are critical for obtaining reliable experimental results. Over the past decade, in collaboration with multiple institutions, the Computational Memory Lab at the University of Pennsylvania has compiled the largest intracranial and scalp EEG datasets in the world, yielding well over 50 peer-reviewed publications. Currently, we are working to standardize these data to comply with the Brain Imaging Data Structure (BIDS) specifications, for upload to the open-source neuroscience data sharing platform OpenNeuro. To date, we have published more than 500 hours of intracranial EEG data, from over 250 unique participants and over 750 experimental sessions. We have further released over 9500 hours of scalp EEG data, from 398 unique participants and 6781 experimental sessions. We recorded these data and the corresponding behavioral events while participants completed a variety of memory experiments. These were often variants of the canonical free recall task, with modulations that included semantically categorized word lists, a time delay of days between encoding and retrieval, and a spatial navigation component. In publicizing the release of these rich datasets, we hope to empower researchers to make novel discoveries that will advance the field of cognitive neuroscience.

Topic Area: LONG-TERM MEMORY: Episodic


CNS Account Login


April 13–16  |  2024