TY - JOUR
T1 - Advances in human intracranial electroencephalography research, guidelines and good practices
AU - Mercier, Manuel R
AU - Dubarry, Anne-Sophie
AU - Tadel, François
AU - Avanzini, Pietro
AU - Axmacher, Nikolai
AU - Cellier, Dillan
AU - Vecchio, Maria Del
AU - Hamilton, Liberty S
AU - Hermes, Dora
AU - Kahana, Michael J
AU - Knight, Robert T
AU - Llorens, Anais
AU - Megevand, Pierre
AU - Melloni, Lucia
AU - Miller, Kai J
AU - Piai, Vitória
AU - Puce, Aina
AU - Ramsey, Nick F
AU - Schwiedrzik, Caspar M
AU - Smith, Sydney E
AU - Stolk, Arjen
AU - Swann, Nicole C
AU - Vansteensel, Mariska J
AU - Voytek, Bradley
AU - Wang, Liang
AU - Lachaux, Jean-Philippe
AU - Oostenveld, Robert
N1 - Funding Information:
RM is supported by EU-REA H2020 MSCA - IF 798853.
Funding Information:
RTK is supported by NIH/NINDS 2 R01 NS021135, NIH/NINDS 1U19NS107609-01.
Funding Information:
PM is supported by Swiss National Science Foundation grants 167836 and 194507.
Funding Information:
CMS is supported by the Emmy Noether Program of the German Research Foundation (SCHW1683/2-1).
Funding Information:
LM is supported by the Max Planck Society.
Funding Information:
We dedicate this review paper to the patients that make this research possible, thanks to their participation they move clinical and fundamental neuroscience forward. We thank the organizers and attendees of the online LiveMEEG 2020 conference for providing a welcoming platform to present and discuss some of the ideas that formed the basis for this manuscript. We thank Mariana P. Branco for help with Fig. 4. Last, we acknowledge the three anonymous reviewers for thoroughly reading the manuscript and for their insightful comments. RM is supported by EU-REA H2020 MSCA - IF 798853. FT is supported by NIH/NIBIB R01EB026299. DH is supported by NIMH/NIH R01MH122258. RTK is supported by NIH/NINDS 2 R01 NS021135, NIH/NINDS 1U19NS107609-01. NFR and MJV are supported by NIH/NIDCD U01 DC016686 and NWO 17619. PM is supported by Swiss National Science Foundation grants 167836 and 194507. LM is supported by the Max Planck Society. AP is supported by NIH/NIBIB R01EB030896. CMS is supported by the Emmy Noether Program of the German Research Foundation (SCHW1683/2-1).
Publisher Copyright:
© 2022
PY - 2022/10/15
Y1 - 2022/10/15
N2 - Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.
AB - Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.
KW - ECoG
KW - Electrocorticogram
KW - Good research practice
KW - Intracranial recording in humans
KW - Stereotactic electroencephalography
KW - sEEG
UR - http://www.scopus.com/inward/record.url?scp=85134690132&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2022.119438
DO - 10.1016/j.neuroimage.2022.119438
M3 - Article
C2 - 35792291
SN - 1053-8119
VL - 260
JO - NeuroImage
JF - NeuroImage
M1 - 119438
ER -