Hypofunctioning of the N-methyl-D-aspartate receptor (NMDA-R) has been prominently implicated in the pathophysiology of schizophrenia (ScZ). The current study tested the effects of ketamine, a dissociative anesthetic and NMDA-R antagonist, on resting-state activity recorded with magnetoencephalography (MEG) in healthy volunteers. In a single-blind cross-over design, each participant (n = 12) received, on 2 different sessions, a subanesthetic dose of S-ketamine (0.006 mg/Kg) and saline injection. MEG-data were analyzed at sensor- and source-level in the beta (13-30 Hz) and gamma (30-90 Hz) frequency ranges. In addition, connectivity analysis at source-level was performed using transfer entropy (TE). Ketamine increased gamma-power while beta-band activity was decreased. Specifically, elevated 30-90 Hz activity was pronounced in subcortical (thalamus and hippocampus) and cortical (frontal and temporal cortex) regions, whilst reductions in beta-band power were localized to the precuneus, cerebellum, anterior cingulate, temporal and visual cortex. TE analysis demonstrated increased information transfer in a thalamo-cortical network after ketamine administration. The findings are consistent with the pronounced dysregulation of high-frequency oscillations following the inhibition of NMDA-R in animal models of ScZ as well as with evidence from electroencephalogram-data in ScZ-patients and increased functional connectivity during early illness stages. Moreover, our data highlight the potential contribution of thalamo-cortical connectivity patterns towards ketamine-induced neuronal dysregulation, which may be relevant for the understanding of ScZ as a disorder of disinhibition of neural circuits.

Autism spectrum disorder (ASD) is a common developmental disorder characterized by communication difficulties and impaired social interaction. Recent results suggest altered brain dynamics as a potential cause of symptoms in ASD. Here, we aim to describe potential information-processing consequences of these alterations by measuring active information storage (AIS)—a key quantity in the theory of distributed computation in biological networks. AIS is defined as the mutual information between the past state of a process and its next measurement. It measures the amount of stored information that is used for computation of the next time step of a process. AIS is high for rich but predictable dynamics. We recorded magnetoencephalography (MEG) signals in 10 ASD patients and 14 matched control subjects in a visual task. After a beamformer source analysis, 12 task-relevant sources were obtained. For these sources, stationary baseline activity was analyzed using AIS. Our results showed a decrease of AIS values in the hippocampus of ASD patients in comparison with controls, meaning that brain signals in ASD were either less predictable, reduced in their dynamic richness or both. Our study suggests the usefulness of AIS to detect an abnormal type of dynamics in ASD. The observed changes in AIS are compatible with Bayesian theories of reduced use or precision of priors in ASD.

Motor inhibitory control implemented as response inhibition is an essential cognitive function required to dynamically adapt to rapidly changing environments. Despite of over a decade of research on the neural mechanisms of response inhibition, it remains unclear, how exactly response inhibition is initiated and implemented. Using a multimodal MEG/fMRI approach in 59 subjects our results reliably reveal that response inhibition is initiated by the right inferior frontal gyrus (rIFG) as a form of attention-independent top-down control that involves the modulation of beta-band activity. Furthermore, stopping performance was predicted by beta-band power and beta-band connectivity was directed from rIFG to pre-supplementary motor area (pre-SMA), indicating rIFG's dominance over pre-SMA. Thus, these results strongly support the hypothesis that rIFG initiates stopping, implemented by beta-band oscillations with potential to open up new ways of spatially localized oscillation-based interventions.

Unexpected and thus surprising events are omnipresent and oftentimes require adaptive behavior such as unexpected inhibition or unexpected action. The current theory of unexpected events suggests that such unexpected events just like global stopping recruit a fronto-basal-ganglia network. A global suppressive effect impacting ongoing motor responses and cognition is specifically attributed to the subthalamic nucleus (STN). Previous studies either used separate tasks or presented unexpected, task-unrelated stimuli during response inhibition tasks to relate the neural signature of unexpected events to that of stopping. Here, we aimed to test these predictions using a within task design with identical stimulus material for both unexpected action and unexpected inhibition using functional magnetic resonance imaging (fMRI) for the first time. To this end, 32 healthy human participants of both sexes performed a cue-informed go/nogo task comprising expected and unexpected action and inhibition trials during fMRI. Using conjunction, contrast, and Bayesian analyses, we demonstrate that unexpected action elicited by an unexpected go signal and unexpected inhibition elicited by an unexpected nogo signal recruited the same fronto-basal-ganglia network which is usually assigned to stopping. Furthermore, the stronger the unexpected action-related activity in the STN region was the more detrimental was the effect on response times. The present results thus complement earlier findings and provide direct evidence for the unified theory of unexpected events while ruling out alternative task and novelty effects.