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

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Trial registration: ClinicalTrials.gov NCT00047853.

Keywords: Anxiety; Dynamic causal modeling; GABA; Hypervigilance; Magnetoencephalography; Mismatch negativity.

Conflict of interest statement

Financial Disclosures

The authors report no biomedical financial interests or potential conflicts of interest.

Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

Figures

Figure 1. Threat of unpredictable shocks elevates anxiety and increases evoked responses to auditory stimulus deviance

A. Retrospective anxiety reports for each context after receiving placebo and 1mg alprazolam on a 0–10 scale. B. Group-averaged difference waves (deviant minus standard tones) exhibiting the magnetic mismatch negativity (MMNm) response by Treatment and Context. Axial gradiometer traces are color coded by hemisphere (green = left, dark blue = right, light blue = midline). C. Six a priori regions of interest (ROIs) to which event-related beamformer source analyses were constrained. Coordinates (MNI space) for each spherical ROI depicted on the standard MRI are as follows: left IFG (yellow) = −46, 20, 8 mm; right IFG = 46, 20, 8 mm; left A1 (red) = −42, −22, 7 mm; right A1 = 46, −14, 8; left STG (orange) = −61, −32, 8 mm; right STG = 59, −25, 8 mm. D. Left primary auditory cortex (A1) and left superior temporal gyrus (STG) ROIs showing significant Treatment by Context interactions (p < .05, corrected). Bar graph shows group-averaged evoked power estimates (log10-transformed deviant/standard power ratio or ‘MMN power’) integrated over 100–250 ms post-stimulus onset. Error bars are s.e.m. pla=placebo, alp=alprazolam, TH=THREAT, SA=SAFE.

Figure 2. Stimulus deviance network shows biased feedforward processing under threat-induced anxiety

A. Family-level random-effects Bayesian analyses revealed that after placebo treatment best fitting models were those that allowed modulation of intrinsic A1 (i) and feedforward (f) connectivity but not feedback (b) connectivity. B. After alprazolam treatment, best fitting models allowed modulation of intrinsic A1 and balanced feedforward/feedback connectivity. C. The lack of feedback modulation in the placebo condition was replicated in an independent dataset (9) using a 5-node architecture. A1 = primary auditory cortex, IFG = inferior frontal gyrus, STG = superior temporal gyrus.

Figure 3. Reduced fronto-temporal feedback coupling under threat of shock is reversed by anxiolytic treatment

Feedback connectivity parameters obtained by Bayesian model averaging are graphed by treatment, context and stimulus for the right fronto-temporal connection (circled). Coupling gains for each participant (circles) and group means (bars) are displayed. dv = deviant tone, st = standard tone, *p=.006

Figure 4. Increased intrinsic A1 coupling to deviant tones under threat is normalized after alprazolam treatment

Coupling gains (ln-transformed) are averaged across left and right A1 (circled) given that there was no interaction involving the Hemisphere factor. *p=.04.