Nearly 60 years ago, Jerome L. Singer launched a groundbreaking research program into daydreaming (Singer, 1955, 1975, 2009) that presaged and laid the foundation for virtually every major strand of mind wandering research active today (Antrobus, 1999; Klinger, 1999, 2009). Here we review Singer’s enormous contribution to the field, which includes insights, methodologies, and tools still in use today, and trace his enduring legacy as revealed in the recent proliferation of mind wandering studies. We then turn to the central theme in Singer’s work, the adaptive nature of positive constructive daydreaming, which was a revolutionary idea when Singer began his work in the 1950s and remains underreported today. Last, we propose a new approach to answering the enduring question: Why does mind wandering persist and occupy so much of our time, as much as 50% of our waking time according to some estimates, if it is as costly as most studies suggest?

Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. In particular, the sensitivity of cerebral blood flow to activity changes in specific neurotransmitter systems remains unclear. We address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action. We use a novel framework aimed at disentangling the observed effects to contribution from underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings suggest that cerebral blood flow is a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans.

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Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. Here we address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action in a novel framework aimed at disentangling the observed effects to underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying activity and/or neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings validate cerebral blood flow as a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans, with widespread implications for translational medicine and drug discovery alike. Significance statementWhilst magnetic resonance imaging of cerebral blood flow is commonly applied for studying human brain disease and therapeutic interventions it remains obscure if and how such measures reflect specific underlying neurophysiological activity or disease pathology in specific neurotransmitter systems. Here we examine the effects of seven drugs with differential dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action on cerebral blood flow. We demonstrate that cerebral blood flow closely reflects specific activity changes from various underlying neurotransmitter systems. These findings and the proposed framework have widespread implications for deploying metabolic magnetic resonance imaging measures for a more informative evaluation of disease pathology and different therapeutic interventions.

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The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations.

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-oxygenlevel 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.

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