TY - JOUR
T1 - Electroencephalographic Connectivity
T2 - A Fundamental Guide and Checklist for Optimal Study Design and Evaluation
AU - Miljevic, Aleksandra
AU - Bailey, Neil W.
AU - Vila-Rodriguez, Fidel
AU - Herring, Sally E.
AU - Fitzgerald, Paul B.
N1 - Funding Information:
This study is supported by a National Health and Medical Research Council Investigator Fellowship (Grant No. 1193596 [to PBF]) and partly supported by a Research Capacity Building Grant funded by the Epworth Medical Foundation (to AM).
Funding Information:
PBF has received equipment for research from MagVenture A/S, Medtronic Ltd, Neuronetics, and Brainsway Ltd and funding for research from Neuronetics. PBF is a founder of TMS Clinics Australia and Resonance Therapeutics. FVR receives research support from CIHR, Brain Canada, Michael Smith Foundation for Health Research, Vancouver Coastal Health Research Institute, and in-kind equipment support for an investigator-initiated trial from MagVenture. FVR has received honoraria for participation in advisory board for Janssen. All other authors report no biomedical financial interests or potential conflicts of interest.
Funding Information:
This study is supported by a National Health and Medical Research Council Investigator Fellowship (Grant No. 1193596 [to PBF]) and partly supported by a Research Capacity Building Grant funded by the Epworth Medical Foundation (to AM). All who meet authorship criteria are listed as authors, and all certify that they have participated sufficiently in the work to take public responsibility for the content. AM contributed to conceptualization, design, writing?preparation, creation, writing?editing, and revision; NWB contributed to conceptualization, design, writing?editing, and revision; and SEH, FVR, and PBF contributed to writing?editing and revision. A previous version of this article was published as a preprint on arXiv: http://arxiv.org/abs/2108.13611. PBF has received equipment for research from MagVenture A/S, Medtronic Ltd, Neuronetics, and Brainsway Ltd and funding for research from Neuronetics. PBF is a founder of TMS Clinics Australia and Resonance Therapeutics. FVR receives research support from CIHR, Brain Canada, Michael Smith Foundation for Health Research, Vancouver Coastal Health Research Institute, and in-kind equipment support for an investigator-initiated trial from MagVenture. FVR has received honoraria for participation in advisory board for Janssen. All other authors report no biomedical financial interests or potential conflicts of interest.
Publisher Copyright:
© 2021
PY - 2022/6
Y1 - 2022/6
N2 - Brain connectivity can be estimated through many analyses applied to electroencephalography (EEG) data. However, substantial heterogeneity in the implementation of connectivity methods exists. Heterogeneity in conceptualization of connectivity measures, data collection, or data preprocessing may be associated with variability in robustness of measurement. While it is difficult to compare the results of studies using different EEG connectivity measures, standardization of processing and reporting may facilitate the task. We discuss how factors such as referencing, epoch length and number, controls for volume conduction, artifact removal, and statistical control of multiple comparisons influence the EEG connectivity estimate for connectivity measures, and what can be done to control for potential confounds associated with these factors. Based on the results reported in previous literature, this article presents recommendations and a novel checklist developed for quality assessment of EEG connectivity studies. This checklist and its recommendations are made in an effort to draw attention to factors that may influence connectivity estimates and factors that need to be improved in future research. Standardization of procedures and reporting in EEG connectivity may lead to EEG connectivity studies being made more synthesizable and comparable despite variations in the methodology underlying connectivity estimates.
AB - Brain connectivity can be estimated through many analyses applied to electroencephalography (EEG) data. However, substantial heterogeneity in the implementation of connectivity methods exists. Heterogeneity in conceptualization of connectivity measures, data collection, or data preprocessing may be associated with variability in robustness of measurement. While it is difficult to compare the results of studies using different EEG connectivity measures, standardization of processing and reporting may facilitate the task. We discuss how factors such as referencing, epoch length and number, controls for volume conduction, artifact removal, and statistical control of multiple comparisons influence the EEG connectivity estimate for connectivity measures, and what can be done to control for potential confounds associated with these factors. Based on the results reported in previous literature, this article presents recommendations and a novel checklist developed for quality assessment of EEG connectivity studies. This checklist and its recommendations are made in an effort to draw attention to factors that may influence connectivity estimates and factors that need to be improved in future research. Standardization of procedures and reporting in EEG connectivity may lead to EEG connectivity studies being made more synthesizable and comparable despite variations in the methodology underlying connectivity estimates.
KW - Brain
KW - Connectivity
KW - Connectivity metrics
KW - EEG
KW - EEG analysis
KW - EEG connectivity
KW - EEG processing
KW - Electroencephalography
KW - Methodology
UR - http://www.scopus.com/inward/record.url?scp=85121294052&partnerID=8YFLogxK
U2 - 10.1016/j.bpsc.2021.10.017
DO - 10.1016/j.bpsc.2021.10.017
M3 - Review Article
C2 - 34740847
AN - SCOPUS:85121294052
SN - 2451-9022
VL - 7
SP - 546
EP - 554
JO - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
JF - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
IS - 6
ER -