Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients
Abstract
Suicidal thoughts and behaviors (STB) are among the leading causes of death worldwide. Although previous research has consistently documented elevated risk-taking in individuals with STB and identified mood disturbances as central features of suicidality, the precise cognitive and affective computational mechanisms underlying this increased risky behavior remain poorly understood. Here, 83 adolescent inpatients with affective disorders-including 58 patients with STB (S+) and 25 without STB (S-)-and 118 age- and sex-matched healthy controls (HC) completed a decision-making task involving choices between certain and gamble options, alongside momentary mood ratings. Behavioral analyses showed that S+ exhibited greater risk-taking than both S- and HC. Computational modeling of choice behavior using a prospect-theory framework augmented with value-insensitive approach-avoidance parameters indicated that this increase in risky behavior was specifically driven by an elevated approach parameter in S+. In addition, mood-model analyses revealed reduced sensitivity to certain rewards in S+ relative to S- and HC. Importantly, these computational signatures predicted suicidal symptom severity and showed generalizability in an independent general-population sample (n = 747). In S+, lower mood sensitivity to certain rewards was associated with greater gambling, providing a computational affective account of increased risk-taking in STB. These findings remained robust after adjusting for…
Read the paper
Related studies
- The neurocircuitry of addiction: an overview
- Gender Differences in Human Brain: A Review
- Stratified medicine for mental disorders
- The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex
- Annual Research Review: DNA methylation as a mediator in the association between risk exposure and child and adolescent psychopathology
- Schizophrenia: The new etiological synthesis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.