Modulation of simultaneously collected hemodynamic and electrophysiological functional connectivity by ketamine and midazolam. Issue 6 (6th December 2019)

• Record Type: Journal Article
• Authors: Forsyth, Anna; McMillan, Rebecca; Campbell, Doug; Malpas, Gemma; Maxwell, Elizabeth; Sleigh, Jamie; Dukart, Juergen; Hipp, Jörg; Muthukumaraswamy, Suresh D.
• Is Part Of: Human brain mapping. Volume 41:Issue 6(2020)
• Page Start: 1472
• Page End: 1494
• Publication Date: 2019-12-06
• Subjects: electroencephalography -- functional connectivity -- functional magnetic resonance imaging -- ketamine -- midazolam -- simultaneous EEG/FMRI; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.24889
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: The pharmacological modulation of functional connectivity in the brain may underlie therapeutic efficacy for several neurological and psychiatric disorders. Functional magnetic resonance imaging (fMRI) provides a noninvasive method of assessing this modulation, however, the indirect nature of the blood‐oxygen level dependent signal restricts the discrimination of neural from physiological contributions. Here we followed two approaches to assess the validity of fMRI functional connectivity in developing drug biomarkers, using simultaneous electroencephalography (EEG)/fMRI in a placebo‐controlled, three‐way crossover design with ketamine and midazolam. First, we compared seven different preprocessing pipelines to determine their impact on the connectivity of common resting‐state networks. Independent components analysis (ICA)‐denoising resulted in stronger reductions in connectivity after ketamine, and weaker increases after midazolam, than pipelines employing physiological noise modelling or averaged signals from cerebrospinal fluid or white matter. This suggests that pipeline decisions should reflect a drug's unique noise structure, and if this is unknown then accepting possible signal loss when choosing extensive ICA denoising pipelines could engender more confidence in the remaining results. We then compared the temporal correlation structure of fMRI to that derived from two connectivity metrics of EEG, which provides a direct measure of neural activity. While electrophysiological estimates based on the power envelope were more closely aligned to BOLD signal connectivity than those based on phase consistency, no significant relationship between the change in electrophysiological and hemodynamic correlation structures was found, implying caution should be used when making cross‐modal comparisons of pharmacologically‐modulated functional connectivity.