The Unpredictive Brain Under Threat: A Neurocomputational Account of Anxious Hypervigilance

Anxious hypervigilance is marked by sensitized sensory-perceptual processes and attentional biases to potential danger cues in the environment. How this is realized at the neurocomputational level is unknown but could clarify the brain mechanisms disrupted in psychiatric conditions such as posttraumatic stress disorder. Predictive coding, instantiated by dynamic causal models, provides a promising framework to ground these state-related changes in the dynamic interactions of reciprocally connected brain areas.

Anxiety states were elicited in healthy participants (n = 19) by exposure to the threat of unpredictable, aversive shocks while undergoing magnetoencephalography. An auditory oddball sequence was presented to measure cortical responses related to deviance detection, and dynamic causal models quantified deviance-related changes in effective connectivity. Participants were also administered alprazolam (double-blinded, placebo-controlled crossover) to determine whether the cortical effects of threat-induced anxiety are reversed by acute anxiolytic treatment.

Deviant tones elicited increased auditory cortical responses under threat. Bayesian analyses revealed that hypervigilant responding was best explained by increased postsynaptic gain in primary auditory cortex activity as well as modulation of feedforward, but not feedback, coupling within a temporofrontal cortical network. Increasing inhibitory gamma-aminobutyric acidergic action with alprazolam reduced anxiety and restored feedback modulation within the network.

Threat-induced anxiety produced unbalanced feedforward signaling in response to deviations in predicable sensory input. Amplifying ascending sensory prediction error signals may optimize stimulus detection in the face of impending threats. At the same time, diminished descending sensory prediction signals impede perceptual learning and may, therefore, underpin some of the deleterious effects of anxiety on higher-order cognition.