Suicide prevention and ketamine: insights from computational modeling
Open accessAbstract
Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine’s anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and ketamine’s therapeutic action, offering insight into potential biomarkers, treatment targets, and the underlying mechanisms of both. This paper provides an overview of current computational theories of suicidality and ketamine’s mechanism of action, and discusses various computational modeling approaches that attempt to explain ketamine’s anti-suicidal effect. More specifically, the therapeutic potential of ketamine is explored in the context of the mismatch negativity and the predictive coding framework, by considering neurocircuits involved in learning and decision-making, and investigating altered connectivity strengths and receptor densities targeted by ketamine. Theory-driven computational models offer a promising approach to integrate existing knowledge of suicidality and ketamine, and for the extraction of model-derived mechanistic parameters that can be used to identify patient subgroups and personalized treatment approaches. Future computational studies on ketamine’s mechanism of action should optimize task design and modeling approaches to ensure parameter reliability, and external factors such as set and setting, as well as psychedelic-assisted therapy should be evaluated for their additional therapeutic value.
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Pharmacological approaches, particularly rapid-acting agents (i.e., ketamine), have attracted growing attention due to their capacity to produce short-term reductions in depressive symptoms, suicidal ideation, and affective distress.
“Pharmacological approaches, particularly rapid-acting agents (i.e., ketamine), have attracted growing attention due to their capacity to produce short-term reductions in depressive symptoms, suicidal ideation, and affective distress [75,76,77].”
From Targeting Psychological Pain After a Suicide Attempt: Scoping Review and Intervention Protocol (2026) · cites this paper as [77]
The Introduction reports that ketamine relieves depressive symptoms and reduces suicidal ideation within hours, but that its effect after a single infusion typically abates within a week. It also says these rapid effects have prompted further study. The passages found do not establish a short-term reduction in affective distress as a separate outcome. (LLM, conf=0.84)
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Flagged first, then by citations
1 of the 147 references couldn’t be matched to a known paper.
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InfluentialFrom psychache to neuroplasticity: A unified rescue-repair model of Ketamine’s anti-suicidal action
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- Authors
- Charlton, C. E., Karvelis, P., McIntyre, R. S., & Diaconescu, A. O.
- Affiliations
- Centre for Addiction and Mental Health (CA)
- University of Toronto (CA)
- Corresponding author
- Charlton, Colleen E.
- Venue
- Frontiers in Psychiatry
- Publisher
- Frontiers Media SA
- Published
- 2023-06-29
- Volume
- 14
- Pages
- 1214018-1214018
- ISSN
- 1664-0640 (ISSN-L)
- PMC
- PMC10342546
- OpenAlex
- W4382812259
- Cited by
- 7
- References
- 147
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4
- FWCI
- 0.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Krembil Foundation
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Electroconvulsive Therapy Studies
- Keywords
- suicide prevention, ketamine, suicidal thoughts and behaviors, computational psychiatry, mismatch negativity, predictive coding, decision-making, neural circuits, receptor density, biomarkers, personalized treatment, psychedelic therapy, set and setting
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