Temporal dynamics of the pharmacological MRI response to subanaesthetic ketamine in healthy volunteers: A simultaneous EEG/fMRI study.

ABSTRACT

BACKGROUND: Pharmacological magnetic resonance imaging has been used to investigate the neural effects of subanaesthetic ketamine in healthy volunteers. However, the effect of ketamine has been modelled with a single time course and without consideration of physiological noise. AIMS: This study aimed to investigate ketamine-induced alterations in resting neural activity using conventional pharmacological magnetic resonance imaging analysis techniques with physiological noise correction, and a novel analysis utilising simultaneously recorded electroencephalography data. METHODS: Simultaneous electroencephalography/functional magnetic resonance imaging and physiological data were collected from 30 healthy male participants before and during a subanaesthetic intravenous ketamine infusion. RESULTS: Consistent with previous literature, we show widespread cortical blood-oxygen-level dependent signal increases and decreased blood-oxygen-level dependent signals in the subgenual anterior cingulate cortex following ketamine. However, the latter effect was attenuated by the inclusion of motion regressors and physiological correction in the model. In a novel analysis, we modelled the pharmacological magnetic resonance imaging response with the power time series of seven electroencephalography frequency bands. This showed evidence for distinct temporal time courses of neural responses to ketamine. No electroencephalography power time series correlated with decreased blood-oxygen-level dependent signal in the subgenual anterior cingulate cortex. CONCLUSIONS: We suggest the decrease in blood-oxygen-level dependent signals in the subgenual anterior cingulate cortex typically seen in the literature is the result of physiological noise, in particular cardiac pulsatility. Furthermore, modelling the pharmacological magnetic resonance imaging response with a single temporal model does not completely capture the full spectrum of neuronal dynamics. The use of electroencephalography regressors to model the response can increase confidence that the pharmacological magnetic resonance imaging is directly related to underlying neural activity.