Social interactions have a major impact on well-being. While many individuals actively seek social situations, others avoid them, at great cost to their private and professional life. The neural mechanisms underlying individual differences in social approach or avoidance tendencies are poorly understood. Here we estimated people's subjective value of engaging in a social situation. In each trial, more or less socially anxious participants chose between an interaction with a human partner providing social feedback and a monetary amount. With increasing social anxiety, the subjective value of social engagement decreased; amygdala BOLD response during decision-making and when experiencing social feedback increased; ventral striatum BOLD response to positive social feedback decreased; and connectivity between these regions during decision-making increased. Amygdala response was negatively related to the subjective value of social engagement. These findings suggest a relation between trait social anxiety / social avoidance and activity in a subcortical network during social decision-making.
Data are freely available on Dryad, doi:10.5061/dryad.jq44b1r
Data from: A human subcortical network underlying social avoidance revealed by an econometric taskDryad Digital Repository, doi:10.5061/dryad.jq44b1r.
The authors declare that there was no funding for this work.
Human subjects: All subjects gave written informed consent and the ethics committee of the Medical Faculty of the University of Bonn, Germany approved all studies (Approval number: 098/18).
- Christian Büchel, University Medical Center Hamburg-Eppendorf, Germany
© 2019, Schultz et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Fusing brain organoids with blood vessel organoids leads to the incorporation of non-neural endothelial cells and microglia into the brain organoids.
The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to elevated emergency response. However, neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRHPVN neurons often fire with rhythmic brief bursts (RB), which, somewhat counterintuitively, constrains firing rate due to long (~2 s) inter-burst intervals. Stressful stimuli rapidly switch RB to continuous single spiking (SS), permitting a large increase in firing rate. A spiking network model shows that recurrent inhibition can control this activity-state switch, and more broadly the gain of spiking responses to excitatory inputs. In biological CRHPVN neurons ex vivo, the injection of whole-cell currents derived from our computational model recreates the in vivo-like switch between RB and SS, providing a direct evidence that physiologically relevant network inputs enable state-dependent computation in single neurons. Together, we present a novel mechanism for state-dependent activity dynamics in CRHPVN neurons.