Schizophrenia is increasingly recognized as a disorder of distributed neural dynamics, but the molecular and genetic contributions are poorly understood. Recent work highlights a role for altered N-methyl-D-aspartate (NMDA) receptor signaling and related impairments in the excitation-inhibitory balance and synchrony of large-scale neural networks. Here, we combined a pharmacological intervention with novel techniques from dynamic network neuroscience applied to functional magnetic resonance imaging (fMRI) to identify alterations in the dynamic reconfiguration of brain networks related to schizophrenia genetic risk and NMDA receptor hypofunction. We quantified "network flexibility," a measure of the dynamic reconfiguration of the community structure of time-variant brain networks during working memory performance. Comparing 28 patients with schizophrenia, 37 unaffected first-degree relatives, and 139 healthy controls, we detected significant differences in network flexibility [F(2,196) = 6.541, P = 0.002] in a pattern consistent with the assumed genetic risk load of the groups (highest for patients, intermediate for relatives, and lowest for controls). In an observer-blinded, placebo-controlled, randomized, cross-over pharmacological challenge study in 37 healthy controls, we further detected a significant increase in network flexibility as a result of NMDA receptor antagonism with 120 mg dextromethorphan [F(1,34) = 5.291, P = 0.028]. Our results identify a potential dynamic network intermediate phenotype related to the genetic liability for schizophrenia that manifests as altered reconfiguration of brain networks during working memory. The phenotype appears to be influenced by NMDA receptor antagonism, consistent with a critical role for glutamate in the temporal coordination of neural networks and the pathophysiology of schizophrenia. S chizophrenia is a highly heritable mental disorder for which aberrant interactions between brain regions or "dysconnectivity" have been proposed as a core neural mechanism (1). Functional magnetic resonance imaging (fMRI) studies demonstrate alterations in specific neural subcircuits in schizophrenia (2, 3) that are under genetic control (4), although recent data from network neuroscience point to more widespread disturbances in the dynamics of large-scale brain networks (5, 6). Uhlhaas (5), Uhlhaas and Singer (6), and Phillips and Silverstein (7) have proposed a plausible pathophysiological mechanism for these phenomena: They argue that alterations in the cellular excitation-inhibitory balance may lead to disturbances in the neural synchrony of large-scale cell ensembles and give rise to the dysconnectivity phenomena at the level of neural ensembles.The neural excitation-inhibitory balance is highly dependent on glutamatergic N-methyl-D-aspartate (NMDA) receptor function (8), and alterations in NMDA receptor signaling have been associated with schizophrenia risk (9), disorder-related cognitive abnormalities (10, 11), and deficits in the temporal coordination of large-scale bra...

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.fMRI | hyperscanning | joint attention H uman social interactions have likely shaped brain evolution and are critical for development, health, and society. Defining their neural underpinnings is a key goal of social neuroscience. Interacting dyads, the simplest and fundamental form of human interaction, have been examined with behavioral setups that used real movement interactions during communication in real time as a proxy (1-4), providing mathematical models representing human interaction, goal sharing, mutual engagement, and coordination. To identify the neural systems supporting these behaviors, neuroimaging would be the tool of choice, but studying dyadic interactions with this method is both experimentally and analytically challenging. Consequently, the neural processes underlying human social interactions remain incompletely understood.Experimentally, studying dyads with neuroimaging technology that allows only one participant per scanner provides challenges that have been addressed in the literature in one of two ways. First, the audiovisual experiences of human social contact have been simulated using stimuli such as photographs, recorded videos, or computerized avatars in the absence of human interaction (5-7), or, recently, immersive audiovisual linkups have been used with one of the two participants being scanned (8, 9). Secondly, pioneering neuroimaging experiments have coupled two scanner sites over the Internet, a setup called hyperscanning, enabling subjects to observe higher-level behavioral responses such as choices made to accept or reject an offer in real time while in the scanners (10, 11). In the current study, we aimed to combine the advantages of these experimental approaches by enabling two humans to see (and possibly hear) each other in a hyperscanning framework, enabling an immersive social interaction while both participant's brains are imaged. To do so, we implemented a setup with delay-free data transmission and precisely synchronized data acquisitio...

Neural plasticity is crucial for understanding the experience-dependent reorganization of brain regulatory circuits and the pathophysiology of schizophrenia. An important circuit-level feature derived from functional magnetic resonance imaging (fMRI) is prefrontalhippocampal seeded connectivity during working memory, the best established intermediate connectivity phenotype of schizophrenia risk to date. The phenotype is a promising marker for the effects of plasticity-enhancing interventions, such as high-frequency repetitive transcranial magnetic stimulation (rTMS), and can be studied in healthy volunteers in the absence of illness-related confounds, but the relationship to brain plasticity is unexplored. We recruited 39 healthy volunteers to investigate the effects of 5 Hz rTMS on prefrontalhippocampal coupling during working memory and rest. In a randomized and sham-controlled experiment, neuronavigation-guided rTMS was applied to the right dorsolateral prefrontal cortex (DLPFC), and fMRI and functional connectivity analyses [seeded connectivity and psychophysiological interaction (PPI)] were used as readouts. Moreover, the test-retest reliability of working-memory related connectivity markers was evaluated. rTMS provoked a significant decrease in seeded functional connectivity of the right DLPFC and left hippocampus during working memory that proved to be relatively time-invariant and robust. PPI analyses provided evidence for a nominal effect of rTMS and poor test-retest reliability. No effects on n-back-related activation and DLPFC-hippocampus resting-state connectivity were observed. These data provide the first in vivo evidence for the effects of plasticity induction on human prefrontalhippocampal network dynamics, offer insights into the biological mechanisms of a well established intermediate phenotype linked to schizophrenia, and underscores the importance of the choice of outcome measures in test-retest designs.