Department of Psychology, Stanford University, Building 420, Jordan Hall, 94305 Stanford, CA, USA.
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
J Affect Disord. 2019 Feb 15;245:545-552. doi: 10.1016/j.jad.2018.11.009. Epub 2018 Nov 3.
Suicidal ideation (SI) is an important predictor of suicide attempt, yet SI is difficult to predict. Given that SI begins in adolescence when brain networks are maturing, it is important to understand associations between network functioning and changes in severity of SI.
Thirty-three depressed adolescents were administered the Columbia-Suicide Severity Rating Scale to assess SI and completed resting-state fMRI at baseline (T1) and 6 months later (T2). We computed coherence in the executive control (ECN), default mode (DMN), salience (SN), and non-relevant noise networks and then examined the association between changes in brain network coherence and changes in SI severity from T1 to T2.
A greater reduction in severity of SI was associated with a stronger increase in SN coherence from T1 to T2. There were no associations between the other networks and SI.
We cannot generalize our findings to more psychiatrically diverse samples. More time-points are necessary to understand the trajectory of SI and SN coherence change.
Our finding that reductions in SI are associated with increases in SN coherence extends previous cross-sectional results documenting a negative association between SI severity and SN coherence. The SN is involved in coordinating activation of ECN and DMN in response to salient information. Given this regulatory role of the SN, the association between SN coherence and SI suggests that adolescents with reduced SN coherence might more easily engage in harmful thoughts. Thus, the SN may be particularly relevant as a target for treatment applications in depressed adolescents.
自杀意念（SI）是自杀企图的重要预测指标，但 SI 很难预测。鉴于 SI 始于大脑网络发育的青少年时期，了解网络功能与 SI 严重程度变化之间的关联非常重要。
33 名抑郁青少年接受了哥伦比亚自杀严重程度评定量表（Columbia-Suicide Severity Rating Scale）评估 SI，并在基线（T1）和 6 个月后（T2）完成了静息态 fMRI 扫描。我们计算了执行控制（ECN）、默认模式（DMN）、突显（SN）和非相关噪声网络的相干性，然后考察了从 T1 到 T2 期间脑网络相干性变化与 SI 严重程度变化之间的关联。
SI 严重程度的降低与从 T1 到 T2 期间 SN 相干性的增强呈正相关。其他网络与 SI 之间无关联。
我们的研究结果不能推广到更多精神疾病多样化的样本中。需要更多的时间点来了解 SI 和 SN 相干性变化的轨迹。
我们发现 SI 的减少与 SN 相干性的增加有关，这扩展了之前的横断面研究结果，即 SI 严重程度与 SN 相干性之间存在负相关。SN 参与协调对显著信息的 ECN 和 DMN 的激活。鉴于 SN 的这种调节作用，SN 相干性与 SI 之间的关联表明，SN 相干性降低的青少年可能更容易产生有害思维。因此，SN 可能是抑郁青少年治疗应用中特别相关的靶点。
