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Published February 16, 2024 | Published
Journal Article Open

Multimodal single-neuron, intracranial EEG, and fMRI brain responses during movie watching in human patients

Abstract

We present a multimodal dataset of intracranial recordings, fMRI, and eye tracking in 20 participants during movie watching. Recordings consist of single neurons, local field potential, and intracranial EEG activity acquired from depth electrodes targeting the amygdala, hippocampus, and medial frontal cortex implanted for monitoring of epileptic seizures. Participants watched an 8-min long excerpt from the video “Bang! You’re Dead” and performed a recognition memory test for movie content. 3 T fMRI activity was recorded prior to surgery in 11 of these participants while performing the same task. This NWB- and BIDS-formatted dataset includes spike times, field potential activity, behavior, eye tracking, electrode locations, demographics, and functional and structural MRI scans. For technical validation, we provide signal quality metrics, assess eye tracking quality, behavior, the tuning of cells and high-frequency broadband power field potentials to familiarity and event boundaries, and show brain-wide inter-subject correlations for fMRI. This dataset will facilitate the investigation of brain activity during movie watching, recognition memory, and the neural basis of the fMRI-BOLD signal.

Copyright and License

© Te Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acknowledgement

We would like to express our deepest gratitude to the patients who volunteered to participate in this study. We thank the clinical team at Cedars-Sinai Medical Center for patient management, Michael Kyzar for advice on NWB usage, and Nand Chandravadia, and April Carlson for assistance with data processing. We thank Rhodri Cusack for sharing the edited version of the Hitchcock movie with us. This study was supported by the NIMH Caltech Conte Center (P50MH094258 to R.A. and U.R.), the BRAIN initiative through the National Institute of Neurological Disorders and Stroke (U01NS117839 to U.R.), the Simons Collaboration on the Global Brain (542941 to R.A. and U.R.), and the National Science Foundation (BCS-2219800).

Contributions

J.D. and U.R. conceived the original study and designed the experiment. J.D., U.R. and J.M.T. performed experiments. U.K., J.D., K.J.M.L., J.M.T. and D.A.K. organized the data. U.K. analyzed the data. A.N.M. performed surgery and supervised clinical care. J.M.C. and C.M.R. enrolled patients, provided clinical care, and supervised MRI scanning. U.R. and R.A. provided supervision and acquired funding. U.K., K.J.M.L., J.M.T., R.A. and U.R. wrote the manuscript. All the authors reviewed and approved the manuscript for submission.

Code Availability

All code is available in the GitHub repository (https://github.com/rutishauserlab/bmovie-release-NWB-BIDS). The python code includes scripts to read and plot the data from the NWB files and perform the analyses presented in this data descriptor. The code relies heavily on open-source Python packages such as numpy61, scipy62, pynwb18, mne-python63, nilearn48, and pycortex64. The movie annotation files are also provided in the GitHub repository under ‘assets/annotations’ folder. The scripts related to the estimation of tSNR and ISC were adapted from the code provided in the GitHub repository associated with the budapest-fmri-data study49,50 (see: https://github.com/mvdoc/budapest-fmri-data).

Conflict of Interest

The authors declare no competing interests.

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Additional details

Created:
February 21, 2024
Modified:
February 21, 2024