The clinical assessment of suicidal risk would be substantially complemented by a biologically based measure that assesses alterations in the neural representations of concepts related to death and life in people who engage in suicidal ideation. This study used machine-learning algorithms (Gaussian Naive Bayes) to identify such individuals (17 suicidal ideators versus 17 controls) with high (91%) accuracy, based on their altered functional magnetic resonance imaging neural signatures of death-related and life-related concepts. The most discriminating concepts were ‘death’, ‘cruelty’, ‘trouble’, ‘carefree’, ‘good’ and ‘praise’. A similar classification accurately (94%) discriminated nine suicidal ideators who had made a suicide attempt from eight who had not. Moreover, a major facet of the concept alterations was the evoked emotion, whose neural signature served as an alternative basis for accurate (85%) group classification. This study establishes a biological, neurocognitive basis for altered concept representations in participants with suicidal ideation, which enables highly accurate group membership classification.
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
WISQARS Data (CDC, 2016); http://webappa.cdc.gov/sasweb/ncipc/leadcaus10_us.html.
Glenn, C. R. & Nock, M. K. Improving the short-term prediction of suicidal behavior. Am. J. Prev. Med. 47, S176–S180 (2014).
Nock, M. K. et al. Measuring the suicidal mind: implicit cognition predicts suicidal behavior. Psychol. Sci. 21, 511–517 (2010).
Busch, K. A., Fawcett, J. & Jacobs, D. G. Clinical correlates of inpatient suicide. J. Clin. Psychiatry 64, 14–19 (2003).
Mann, J. J. et al. Candidate endophenotypes for genetic studies of suicidal behavior. Biol. Psychiatry 65, 556–563 (2009).
Ribeiro, J. D. et al. Self-injurious thoughts and behaviors as risk factors for future suicide ideation, attempts, and death: a meta-analysis of longitudinal studies. Psychol. Med. 46, 225–236 (2016).
Just, M. A., Cherkassky, V. L., Aryal, S. & Mitchell, T. M. A neurosemantic theory of concrete noun representation based on the underlying brain codes. PLoS ONE 5, e8622 (2010).
Kassam, K. S., Markey, A. R., Cherkassky, V. L., Loewenstein, G. & Just, M. A. Identifying emotions on the basis of neural activation. PLoS ONE 8, e66032 (2013).
Mitchell, T. M. et al. Predicting human brain activity associated with the meanings of nouns. Science 320, 1191–1195 (2008).
Just, M. A., Cherkassky, V. L., Buchweitz, A., Keller, T. A. & Mitchell, T. M. Identifying autism from neural representations of social interactions: neurocognitive markers of autism. PLoS ONE 9, e113879 (2014).
Cha, C. B., Najmi, S., Park, J. M., Finn, C. T. & Nock, M. K. Attentional bias toward suicide-related stimuli predicts suicidal behavior. J. Abnorm. Psychol. 119,616–622 (2010).
Armey, M. F., Crowther, J. H. & Miller, I. W. Changes in ecological momentary assessment reported affect associated with episodes of nonsuicidal self-injury. Behav. Ther. 42, 579–588 (2011).
Bresin, K., Carter, D. L. & Gordon, K. H. The relationship between trait impulsivity, negative affective states, and urge for nonsuicidal self-injury: a daily diary study. Psychiatry Res. 205, 227–231 (2013).
Bryan, C. J., Morrow, C. E., Etienne, N. & Ray-Sannerud, B. Guilt, shame, and suicidal ideation in a military outpatient clinical sample. Depress. Anxiety 30,55–60 (2013).
Bryan, C. J., Ray-Sannerud, B., Morrow, C. E. & Etienne, N. Shame, pride, and suicidal ideation in a military clinical sample. J. Affect. Disord. 147, 212–216 (2013).
Humber, N., Emsley, R., Pratt, D. & Tarrier, N. Anger as a predictor of psychological distress and self-harm ideation in inmates: a structured self-assessment diary study. Psychiatry Res. 210, 166–173 (2013).
Nock, M. K., Prinstein, M. J. & Sterba, S. K. Revealing the form and function of self-injurious thoughts and behaviors: a real-time ecological assessment study among adolescents and young adults. J. Abnorm. Psychol. 118, 816–827 (2009).
Olié, E. et al. Processing of decision-making and social threat in patients with history of suicidal attempt: a neuroimaging replication study. Psychiatry Res. 234,369–377 (2015).
Dukart, J., Schroeter, M. L. & Mueller, K. Age correction in dementia — matching to a healthy brain. PLoS ONE 6, e22193 (2011).
Koikkalainen, J. et al. Improved classification of Alzheimer’s disease data via removal of nuisance variability. PLoS ONE 7, e31112 (2012).
Jacobson, C., Batejan, K., Kleinman, M. & Gould, M. Reasons for attempting suicide among a community sample of adolescents. Suicide Life Threat. Behav. 43,646–662 (2013).
Rogers, M. L., Kelliher-Rabon, J., Hagan, C. R., Hirsch, J. K. & Joiner, T. E. Negative emotions in veterans relate to suicide risk through feelings of perceived burdensomeness and thwarted belongingness. J. Affect. Disord. 208, 15–21 (2017).
Pestian, J., Matykiewicz, P. & Linn-Gust, M. What’s in a note: construction of a suicide note corpus. Biomed. Inform. Insights 5, 1–6 (2012).
Pan, L. A. et al. Differential patterns of activity and functional connectivity in emotion processing neural circuitry to angry and happy faces in adolescents with and without suicide attempt. Psychol. Med. 43, 2129–2142 (2013).
Beck, A. T. & Haigh, E. A. P. Advances in cognitive theory and therapy: the generic cognitive model. Annu. Rev. Clin. Psychol. 10, 1–24 (2014).
Adler, A. et al. A mixed methods approach to identify cognitive warning signs for suicide attempts. Arch. Suicide Res. 20, 528–538 (2016).
Jager-Hyman, S. et al. Cognitive distortions and suicide attempts. Cognit. Ther. Res. 38, 369–374 (2014).
Brown, G. K., Steer, R. A., Henriques, G. R. & Beck, A. T. The internal struggle between the wish to die and the wish to live: a risk factor for suicide. Am. J. Psychiatry 162, 1977–1979 (2005).
Bakhiyi, C. L., Calati, R., Guillaume, S. & Courtet, P. Do reasons for living protect against suicidal thoughts and behaviors? A systematic review of the literature. J. Psychiatr. Res. 77, 92–108 (2016).
Jollant, F. et al. Orbitofrontal cortex response to angry faces in men with histories of suicide attempts. Am. J. Psychiatry 165, 740–748 (2008).
Mann, J. J., Waternaux, C., Haas, G. L. & Malone, K. M. Toward a clinical model of suicidal behavior in psychiatric patients. Am. J. Psychiatry 156, 181–189 (1999).
Brent, D. A. et al. Familial pathways to early-onset suicide attempt: a 5.6 year prospective study. JAMA Psychiatry 72, 160–168 (2015).
Minzenberg, M. J. & Carter, C. S. Developing treatments for impaired cognition in schizophrenia. Trends Cogn. Sci. 16, 35–42 (2012).
Suppes, P., Han, B., Epelboim, J. & Lu, Z.-L. Invariance of brain-wave representations of simple visual images and their names. Proc. Natl Acad. Sci. USA 96, 14658–14663 (1999).
Kessler, R. C. et al. Predicting suicides after psychiatric hospitalization in US Army soldiers. JAMA Psychiatry 72, 49–57 (2015).
Wechsler, D. Wechsler Abbreviated Scale of Intelligence (Harcourt Assessment, 1999).
Beck, A. T., Schuyler, D. & Herman, I. in The Prediction of Suicide (eds Beck, A. T. et al.) 45–56 (Charles Press, Bowie, MD, 1974).
Oquendo, M. A., Halberstam, B. & Mann, J. J. in Standardized Evaluation in Clinical Practice (ed. First, M. B.) 103–129 (American Psychiatric Press, Washington DC, 2003).
Posner, K. et al. Columbia-Suicide Severity Rating Scale (C-SSRS) (Columbia Univ. Medical Center, New York, NY, 2008).
Reynolds, W. M. Professional Manual for the Suicidal Ideation Questionnaire (Psychological Assessment Resources, Odessa, FL, 1987).
Achenbach, T. M., Howell, C. T., McConaughy, S. H. & Stanger, C. Six-year predictors of problems in a national sample: IV. Young adult signs of disturbance. J. Am. Acad. Child Adolesc. Psychiatry 37, 718–727 (1998).
Achenbach, T. Adult Self Report Measure for Ages 18–59 (Univ. Vermont, Burlington, VT, 2003).
Kroenke, K., Spitzer, R. L. & Williams, J. B. W. The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16, 606–613 (2001).
Spielberger, C. D. State Trait Anxiety Inventory for Adults: Sampler Set: Manual, Test, Scoring Key;[form Y] (Mind Garden, Menlo Park, CA, 1983).
Bernstein, D. P. et al. Initial reliability and validity of a new retrospective measure of child abuse and neglect (CTQ). Am. J. Psychiatry 151, 1132–1136 (1994).
This research was partially supported by the National Institute of Mental Health Grant MH029617 and an Endowed Chair in Suicide Studies at the University of Pittsburgh School of Medicine. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Supplementary Methods, Supplementary Table 1, Supplementary Figures 1–4, Supplementary Notes and Supplementary References
About this article
Cite this article
Just, M., Pan, L., Cherkassky, V.L. et al. Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth. Nat Hum Behav 1, 911–919 (2017). https://doi.org/10.1038/s41562-017-0234-y
Reply to: Towards increasing the clinical applicability of machine learning biomarkers in psychiatry
Nature Human Behaviour (2021)
npj Science of Learning (2021)
Default mode and salience network alterations in suicidal and non-suicidal self-injurious thoughts and behaviors in adolescents with depression
Translational Psychiatry (2021)
Nature Human Behaviour (2021)