Archival ReportThe Unpredictive Brain Under Threat: A Neurocomputational Account of Anxious Hypervigilance
Section snippets
Subjects
Nineteen healthy participants (7 women, mean age ± SD = 29 ± 7 years) completed two testing MEG sessions and a single magnetic resonance imaging (MRI) session. Target sample size was based on previously published data using the same MEG paradigm (9). All participants received physical and psychiatric exams to ensure their health status and confirm that they were not taking psychoactive medications. They were also screened for metallic implants and other contraindications associated with MRI
Contextual and Pharmacological Manipulation of Anxiety
Participants were exposed to two conditions during MEG scanning, a threat context in which aversive shocks could be delivered unpredictably without immediate warning and a safe context in which no shocks could be delivered. MEG scanning commenced approximately 90 to 120 minutes after participants had been orally administered 1 mg of the benzodiazepine alprazolam or an inactive placebo on two separate occasions (double blinded). As expected, participants reported feeling less anxious during the
Discussion
By exposing participants in a threat-induced anxiety state to simple auditory oddball stimuli, we observed a radical change in network dynamics underlying early perceptual processing. Within a DCM analytic framework, Bayesian model comparisons revealed that deviant stimulus responding under threat of shock could be adequately explained by changes only in intrinsic A1 gain and feedforward signaling within a bilateral temporofrontal cortical network. In other words, models that allowed for
Acknowledgments and Disclosures
This work was supported in part by the Intramural Research Program of the National Institute of Mental Health Grant No. ZIAMH002798 (Protocol 02-M-0321; NCT00047853 to CG), a NARSAD Young Investigator Award from the Brain & Behavior Research Foundation (to BRC), and a University of Queensland Fellowship Grant No. 2016000071 (to MIG).
We thank Lynne Liebermann for assistance with data collection, members of the National Institute of Mental Health Magnetoencephalography Core Facility for quality
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