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Updated: May 15, 2026

Reducing State Anxiety Using Working Memory Maintenance
Published on: July 19, 2017
Anti-anxiety drugs reduce conflict-specific "theta"--a possible human anxiety-specific biomarker
Neil McNaughton1, Charles Swart, Phoebe Neo
1Department of Psychology and Department of Psychological Medicine, University of Otago, POB56, Dunedin 9054, New Zealand. nmcn@psy.otago.ac.nz
Background:
Syndromes of fear/anxiety are currently ill-defined, with no accepted human biomarkers for anxiety-specific processes. A unique common neural action of different classes of anxiolytic drugs may provide such a biomarker. In rodents, a reduction in low frequency (4-12 Hz; "theta") brain rhythmicity is produced by all anxiolytics (even those lacking panicolytic or antidepressant action) and not by any non-anxiolytics. This rhythmicity is a key property of the Behavioural Inhibition System (BIS) postulated to be one neural substrate of anxiety. We sought homologous anxiolytic-sensitive changes in human surface EEG rhythmicity.
Method:
Thirty-four healthy volunteers in parallel groups were administered double blind single doses of triazolam 0.25mg, buspirone 10mg or placebo 1 hour prior to completing the stop-signal task. Right frontal conflict-specific EEG power (previously shown to correlate with trait anxiety and neuroticism in this task) was extracted as a contrast between trials with balanced approach-avoidance (stop-go) conflict and the average of trials with net approach and net avoidance.
Results:
Compared with placebo, both triazolam and buspirone decreased right-frontal, 9-10 Hz, conflict-specific-power.
Limitations:
Only one dose of each of only two classes of anxiolytic and no non-anxiolytics were tested, so additional tests are needed to determine generality.
Conclusions:
There is a distinct rhythmic system in humans that is sensitive to both classical/GABAergic and novel/serotonergic anxiolytics. This conflict-specific rhythmicity should provide a biomarker, with a strong pre-clinical neuropsychology, for a novel approach to classifying anxiety disorders.
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