Modulation of simultaneously collected hemodynamic and electrophysiological functional connectivity by ketamine and midazolam

The validity of fMRI functional connectivity as a drug biomarker was tested by comparing seven preprocessing pipelines and by simultaneously measuring EEG and fMRI in a placebo-controlled, three-way crossover study with ketamine and midazolam. Independent components analysis (ICA)-denoising produced stronger reductions in connectivity after ketamine and weaker increases after midazolam than pipelines using physiological noise modelling or averaged signals from cerebrospinal fluid or white matter. This indicates that pipeline decisions should match a drug's unique noise structure; when unknown, extensive ICA denoising may sacrifice some signal but increase confidence in remaining results. No significant relationship was found between changes in electrophysiological and hemodynamic correlation structures, cautioning against cross-modal comparisons of pharmacologically-modulated functional connectivity.

Study at a glance

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.