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Clinical, behavioral, and electrophysiological profiles along a continuum of suicide risk: evidence from an implicit association task

Published online by Cambridge University Press:  24 November 2023

Steven J. Lamontagne ,
Jessica R. Gilbert ,
Paloma K. Zabala ,
Laura R. Waldman ,
Carlos A. Zarate Jr Open the ORCID record for Carlos A. Zarate Jr [Opens in a new window]  and
Elizabeth D. Ballard
Steven J. Lamontagne
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Jessica R. Gilbert
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Paloma K. Zabala
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Laura R. Waldman
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Carlos A. Zarate Jr
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Elizabeth D. Ballard*
Affiliation:
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
*
Corresponding author: Elizabeth D. Ballard; Email: Elizabeth.Ballard@nih.gov
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Abstract

Background

An urgent need exists to identify neural correlates associated with differing levels of suicide risk and develop novel, rapid-acting therapeutics to modulate activity within these neural networks.

Methods

Electrophysiological correlates of suicide were evaluated using magnetoencephalography (MEG) in 75 adults with differing levels of suicide risk. During MEG scanning, participants completed a modified Life-Death Implicit Association Task. MEG data were source-localized in the gamma (30–58 Hz) frequency, a proxy measure of excitation-inhibition balance. Dynamic causal modeling was used to evaluate differences in connectivity estimates between risk groups. A proof-of-concept, open-label, pilot study of five high risk participants examined changes in gamma power after administration of ketamine (0.5 mg/kg), an NMDAR antagonist with rapid anti-suicide ideation effects.

Results

Implicit self-associations with death were stronger in the highest suicide risk group relative to all other groups, which did not differ from each other. Higher gamma power for self-death compared to self-life associations was found in the orbitofrontal cortex for the highest risk group and the insula and posterior cingulate cortex for the lowest risk group. Connectivity estimates between these regions differentiated the highest risk group from the full sample. Implicit associations with death were not affected by ketamine, but enhanced gamma power was found for self-death associations in the left insula post-ketamine compared to baseline.

Conclusions

Differential implicit cognitive processing of life and death appears to be linked to suicide risk, highlighting the need for objective measures of suicidal states. Pharmacotherapies that modulate gamma activity, particularly in the insula, may help mitigate risk.

Clinicaltrials.gov identifier: NCT02543983, NCT00397111.

Keywords

dynamic causal modelinggamma powerimplicit association taskketaminemagnetoencephalographysuicide

Information

Type
Original Article
Information
Psychological Medicine , Volume 54 , Issue 7 , May 2024 , pp. 1431 - 1440
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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