Shadli, Shabah M

Ando, Lynne C

McIntosh, Julia

Lodhia, Veema

Russell, Bruce R

Kirk, Ian J

Glue, Paul

McNaughton, Neil

2021

<p><b>Psychiatric diagnoses currently rely on a patient's presenting symptoms or signs, lacking muchneeded theory-based biomarkers. Our neuropsychological theory of anxiety, recently supported by human imaging, is founded on a longstanding, reliable, rodent 'theta' brain rhythm model of human clinical anxiolytic drug action. We have now developed a human scalp EEG homolog—goal-confictspecifc rhythmicity (GCSR), i.e., EEG rhythmicity specifc to a balanced confict between goals (e.g., approach-avoidance). Critically, GCSR is consistently reduced by diferent classes of anxiolytic drug and correlates with clinically-relevant trait anxiety scores (STAI-T). Here we show elevated GCSR in student volunteers divided, after testing, on their STAI-T scores into low, medium, and high (typical of clinical anxiety) groups. We then tested anxiety disorder patients (meeting diagnostic criteria) and similar controls recruited separately from the community. The patient group had higher average GCSR than their controls—with a mixture of high and low GCSR that varied with, but cut across, conventional disorder diagnosis. Consequently, GCSR scores should provide the frst theoretically based biomarker that could help diagnose, and so redefne, a psychiatric disorder.</b></p>

Scientific Reports, v.11

2045-2322

https://hdl.handle.net/1959.11/58607

Nature Publishing Group

Attribution 4.0 International

Right frontal anxiolytic-sensitive EEG ‘theta’ rhythm in the stop-signal task is a theory-based anxiety disorder biomarker

Journal Article

Publication