1. Neuroscience

Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients

  1. Zhihao Wang
  2. Tian Nan
  3. Fengmei Lu
  4. Yu Yue
  5. Xiao Cai
  6. Zongling He  Is a corresponding author
  7. Yuejia Luo
  8. Ting Wang  Is a corresponding author
  9. Bastien Blain
  1. Center for Neurocognition and Social Behavior, Institute of Artificial Intelligence, Shenzhen University of Advanced Technology, China
  2. CNRS - Centre d'Economie de la Sorbonne, Panthéon-Sorbonne University, France
  3. Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, China
  4. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, China
  5. China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, China
  6. Institute for Brain Research and Rehabilitation, South China Normal University, China
  7. Department of Experimental Psychology, University College London, United Kingdom
https://doi.org/10.7554/eLife.108002.4
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Cite this article
  1. Zhihao Wang
  2. Tian Nan
  3. Fengmei Lu
  4. Yu Yue
  5. Xiao Cai
  6. Zongling He
  7. Yuejia Luo
  8. Ting Wang
  9. Bastien Blain
(2026)
Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients
eLife 14:RP108002.
https://doi.org/10.7554/eLife.108002.4
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15 figures, 15 tables and 1 additional file

Figures

Figure 1
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Task design, outcome and time effects on mood, and group differences in mood.

(A) Gambling task with mood ratings. On each trial, participants were asked to choose between a certain option and a gambling option (self-paced). Once selected, the chosen option was highlighted in yellow for 500 ms. Then the corresponding outcome was displayed in the center of the screen for 1000 ms. The cumulated score was always shown in the right-upper corner. Every two to three trials, participants were asked to complete a self-paced rating of their happiness, answering the question ‘How happy are you at the moment’ on a slider from 0 (very unhappy) to 100 (very happy). (B) Patients and healthy controls felt happier after winning than losing. (C) Mood drifted over time. (D) Group difference in mood before the task shows weakened mood in S+. (E) Group difference in average mood displays lower mood experience in S+. (F) Mood variance was similar for all three groups, as indexed by the standard deviation of happiness ratings across the task. (G) Each group earned about the same amount of points by the end of the task. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; *p < 0.05. Error bars correspond to the standard error.

Figure 2
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Choice results.

(A) Group differences in gambling behavior. The gray dots represent the winning model prediction. (B) The estimated parameters from the winning choice model differed across groups. S+ exhibited stronger approach motivation than S− and HC. (C) The mediation model among the group, βgain, and gambling behavior in the gain condition. The approach parameter mediated the effects of STB group on increased gambling behavior in the gain condition. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; *p < 0.05.

Figure 3
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Effect of Suicidal thoughts and behavior on mood dynamics.

(A) Group difference in mood baseline, β0. (B) Group differences in mood sensitivity to certain reward (CR) and gamble reward (GR). (C) Correlational difference in S− and S+ between mood sensitivity to CR and gambling behavior. The lighter, semi-transparent dots represent individual participants, while the dark dot with an error bar indicates the mean of binned scores (for illustration purposes only). Abbreviations: CR, certain reward; GR, gamble reward; HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; *p < 0.05.

Figure 4
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Validation of suicidal-related results in an independent dataset of general populations (n = 747).

(A) Group difference in gambling behavior in the gain domain. (B) The estimated parameters from the winning choice model (pseudo R2 = 0.479) differed across groups, with higher approach behavior for S+. (C) The mediation model among the group, βgain, and gambling behavior in the gain condition. The approach parameter mediated the group effect on increased gambling behavior in the gain condition. (D) Group difference in mood before the task shows weakened mood in S+. (E) Group difference in average mood displays lower mood experience in S+. (F, G) The estimated parameters from the CR–GR mood model (mean R2 = 0.588). (F) Group difference in mood baseline, β0. (G) Group differences in mood sensitivity to certain reward (CR) and gamble reward (GR). Abbreviations: S−, general participants without suicidal thoughts and behavior; S+, general participants with suicidal thoughts and behavior; *p < 0.05, +p < 0.1.

Appendix 1—figure 1
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Suicidal attempts vs. suicidal thoughts.
Appendix 1—figure 2
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Control analysis for age and other anxiolytics in patients, which were significant between groups.
Appendix 1—figure 3
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Control analysis for childhood maltreatment and emotion regulation problems in patients, which were significant between groups.
Appendix 1—figure 4
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Control analysis for depression/anxiety symptoms in patients, which were significant between groups.
Appendix 1—figure 5
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Choice and mood model recovery.

Mood model recovery was performed in a stage-by-stage manner, mirroring the model comparison procedure used in the main analyses because each model comparison step addresses a specific question and doing so prevents dispersion of model evidence across multiple similar models. Specifically, rather than entering all mood models into a single recovery space, recovery was evaluated separately within each comparison space used for model selection. Thus, each confusion matrix reflects recovery among only the models that were directly compared at that stage.

Appendix 1—figure 6
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Parameter recovery for the winning choice and mood models (cM3; mM3).
Appendix 1—figure 7
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Replication of Rutledge et al., 2017’s findings using BDI.

Depression symptom measured by BDI was negatively correlated with the baseline mood parameter.

Appendix 1—figure 8
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RPE model results (M1).

(A) Group differences in mood sensitivity to certain reward (CR), expected value (EV), and reward prediction error (RPE). (B) Correlation between Suicidal Ideation score at current time (BSI-C) and mood sensitivity to CR. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; BSI-C, Beck Scale for Suicidal Ideation at the current time; *p < 0.05.

Appendix 1—figure 9
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Expectation effect on mood.

(A) Group differences in mood sensitivity to certain reward (CR), gamble reward (GR), and expected value (EV). (B) Correlation between Suicidal Ideation score at current time (BSI-C) and mood sensitivity to CR. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; BSI-C, Beck Scale for Suicidal Ideation at the current time; *p < 0.05.

Appendix 1—figure 10
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Results from M5.

(A) Group differences in mood sensitivity to certain reward (CR), better gamble reward (GRbetter), and worse gamble reward (GRworse). (B) Correlation between Suicidal Ideation score at current time (BSI-C) and mood sensitivity to CR. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; BSI-C, Beck Scale for Suicidal Ideation at the current time; *p < 0.05.

Appendix 1—figure 11
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Permutation tests.

We conducted permutation tests (1,000,000 iterations) to evaluate the robustness of our main results, ensuring consistency with the same normal distribution, and sample size. Specifically, in each permutation, we randomly drew five samples from the S+ group and repeated this process 20 times to construct a suicidal group (100 samples). The same procedure was applied to the S− group to construct a control group. We then calculated the t-values between the two constructed groups on variables of interest, including the proportion of gambling choices, the approach parameter, and mood sensitivity to certain rewards (CR). The 1,000,000 t-values formed the H1 distributions of between-group differences. Nonparametric p values were calculated as the proportion of permutations that generated t-values failing to reach significance (parametric p > 0.05), divided by 1,000,000. Across these variables, the S+ group significantly differed from the S− group (ps < 0.038).

Tables

Table 1
Demographics, clinical, psychological characteristics of patients with and without suicidal thoughts and behaviors.
GroupGroup contrastS+ vs. S−
HC (n = 118)S− (n = 25)S+ (n = 58)F/χ2pt/χ2p
Sex (female/male)75/4316/941/170.9120.6340.3630.547
Age15.31 ± 2.1515.68 ± 1.7514.83 ± 1.801.8680.1571.9970.049
BSI-C1.29 ± 3.622.84 ± 2.6618.02 ± 7.56224.230<0.001–9.754<0.001
BSI-W3.58 ± 6.604.04 ± 3.2227.98 ± 6.02326.242<0.001–18.723<0.001
CTQ13.98 ± 11.2922.64 ± 12.3433.00 ± 17.0340.023<0.001–2.7430.008
ERQ-R14.77 ± 4.3813.08 ± 6.348.48 ± 5.3931.317<0.0013.3760.001
ERQ-S6.86 ± 3.648.80 ± 3.7710.79 ± 3.7922.322<0.001–2.2000.031
Suicidal attempts history (yes)------29------------
Illness duration (months)---31.76 ± 18.8031.38 ± 18.70------0.0850.933
Family history (yes)---210------1.2060.272
Current diagnosis (GAD/MDD/BD)---24/55/910/17/6------1.7900.409
Medication (yes)---2557------0.4360.509
SSRI---1639------0.0820.775
SNRI---02------0.8830.347
Trazodone---616------0.1150.734
Antipsychotics---1432------0.0050.945
BZDs---2045------0.0600.807
Other anxiolytics---1213------5.4340.020
Mood stabilizer---1318------3.2820.070
TAI43.49 ± 8.5450.38 ± 12.1965.36 ± 7.62108.863<0.001–6.276<0.001
PSWQ44.75 ± 10.9450.67 ± 15.1768.56 ± 9.5880.213<0.001–5.990<0.001
BDI9.45 ± 9.4318.62 ± 15.1138.30 ± 9.67129.516<0.001–6.573<0.001
CESD32.96 ± 11.0942.86 ± 15.6662.52 ± 9.99118.084<0.001–6.347<0.001

  1. Note: For anxiety/depression-related questionnaires (TAI, PSWQ, BDI, and CESD), due to time limitation, data from eight participants in the S+ group and four participants in the S− group was not collected. Bold values indicate an unexpected statistically significant difference. Abbreviations: HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior; BSI-C, Beck Scale for Suicidal Ideation at the current time; BSI-W, Beck Scale for Suicidal Ideation at the worst time; CTQ, Childhood Trauma Questionnaire; ERQ-R, Emotion Regulation Questionnaire-Reappraisal; ERQ-S, Emotion Regulation Questionnaire-Suppression; AD, anxiety disorders; MDD, major depressive disorders; BD, bipolar disorders; SSRI, Selective Serotonin Reuptake Inhibitor; SNRI, serotonin-norepinephrine reuptake inhibitors; BZDs, Benzodiazepines; TAI, Trait Anxiety Inventory; PSWQ, Penn State Worry Questionnaire; BDI, Beck Depression Inventory; CESD, Center for Epidemiologic Studies Depression Scale.

Table 2
Choice model comparison.
Model #Model specification# of parametersΔ BICMean R2Δ BIC for each group
HCS−S+
1µ13873.160.082272.48370.191230.49
2λ, α, µ33153.790.181822.07263.971067.75
3λ, α, βgain, βloss, µ500.37000

  1. ΔBIC, Bayesian information criterion relative to the winning model (cM3); HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior.

Table 3
Mood model comparison.
Model #Model specification# of parametersΔ BICMean R2Δ BIC for each group
HCS−S+
1β0, βCR, βEV, βRPE, γ5–106.770.48–182.0432.5442.73
2β0, βCR, βEV, βRPE, γCR, γEV, γRPE7140.000.54–69.4083.20126.20
3β0, βCR, βGR, γ400.42000
4β0, βCR, βGR, γCR, γGR5–146.810.48–272.1526.3798.97
5β0, βCR, γ32395.620.181379.96264.87749.79
6β0, βGR, γ3403.460.34228.6921.24153.52

  1. ΔBIC, Bayesian information criterion relative to the winning model in S+ group (mM3); HC, healthy control; S−, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior.

Table 4
Suicidal risk prediction from computational parameters.
Internal validation (n = 201)External validation (n = 747)
Cross-validationRho (mean ± SD)Rho [min, max]p valuesRhop value
Fivefold0.205 ± 0.016[0.146, 0.230]<0.0390.0730.045
Tenfold0.207 ± 0.011[0.172, 0.226]<0.0140.0730.045
Appendix 1—table 1
A short summary for risk measurement in STB.

Abbreviations: BIS, Barratt Impulsiveness Scale; IGT, Iowa Gambling Task; CGT, Cambridge Gambling Task; BART, the Balloon analog risk task.

StudyMeasurementsToolsAnalysis levelHypothesesResultsCategoryModel specification
Millner et al., 2020QuestionnaireUPPS-P Impulsive
Behavior Scale + BIS		Sum (sub)scale scoresHeightened impulsiveness in STBnsSelf-report
Zakowicz et al., 2021QuestionnaireBISSum (sub)scale scoresHeightened impulsiveness in STBnsSelf-report
Jollant et al., 2005TaskIGTModel-agnosticMore risky behavior in STBTask performance: STB < controlRisk +Ambiguity + Learning
Bridge et al., 2012TaskIGTModel-agnosticMore risky behavior in STBTask performance: STB < controlRisk +Ambiguity + Learning
Martino et al., 2011TaskIGTModel-agnosticMore risky behavior in STBTask performance: STB < controlRisk +Ambiguity + Learning
Chamberlain et al., 2013TaskCGTModel-agnosticMore risky (irrational) behavior in STBProportion of rational choices: STB < controlRisk
Ackerman et al., 2015TaskCGTModel-agnosticMore risky behavior in STBProportion of bet: STB > controlRisk
Dir et al., 2020TaskBARTModel-agnosticMore risky behavior in STBTask performance: STB < controlRisk +Ambiguity + Learning
Liu et al., 2022TaskBARTModel-basedDecision-making bias in STBTask performance: STB > control
Loss aversion: STB > control		Risk +Ambiguity + LearningExponential‐Weight Model: loss aversion, risk preference, updating exponent, prior belief of exploding
Baek et al., 2017-riskTaskGambling (gain + loss)Model-basedHeightened risk aversion in STBRisk aversion: STB > controlRiskRisk discount model: discount parameter
Baek et al., 2017-lossTaskGambling (mix)Model-basedHeightened loss aversion in STBLoss aversion: STB > controlriskPsychophysics; indifference point
Alacreu-Crespo et al., 2020TaskIGTModel-basedMore risky behavior in STBTask performance: STB < control;
Loss aversion: STB < control;
Learning: STB > control		Risk +Ambiguity + LearningProspect valence learning delta model: learning/memory, choice consistency, loss aversion, and feedback sensibility
The current studyTaskGambling (gain + loss + mix)Model-basedMore risky behavior in STBGambling behavior: STB > control;
Approach parameter: STB > control		RiskThe Approach-Avoidance Prospect Theory Model: risk aversion, loss aversion, approach motivation, avoidance motivation, decision noise
Appendix 1—table 2
Contrasts for demographic and psychological characteristics.
S− vs. HCS+ vs. HC
t/χ2pt/χ2p
Gender0.0020.9670.8800.348
Age0.8160.416–1.4580.147
BSI-C2.0300.04419.889<0.001
BSI-W0.3420.73323.723<0.001
CTQ3.426<0.0018.822<0.001
ERQ-R–1.6090.110–8.278<0.001
ERQ-S2.4090.0176.650<0.001
TAI3.1740.00215.653<0.001
PSWQ2.1420.03413.364<0.001
BDI3.2990.00117.368<0.001
CESD3.522<0.00116.255<0.001
Appendix 1—table 3
Sample size for each diagnosis with and without comorbidity in S+ and S− groups.
DiagnosisS+S−Statistics
GAD12χ2 = 4.843
p = 0.304
MDD259
BD76
MDD and BD20
MDD and AD238
Appendix 1—table 4
Bivariate correlations between choice parameters and socio-demographic clinical variables.

All p values were above 0.05.

λαβgainβlossμ
DemographicsGenderrho = 0.00,
p = 1.000		rho = 0.15,
p = 0.179		rho = 0.08,
p = 0.495		rho = 0.14,
p = 0.197		rho = –0.00,
p = 0.961
Agerho = 0.13,
p = 0.230		rho = 0.07,
p = 0.517		rho = –0.19,
p = 0.079		rho = –0.03,
p = 0.811		rho = –0.17,
p = 0.114
Social variablesCTQrho = 0.01,
p = 0.946		rho = –0.19,
p = 0.090		rho = 0.08,
p = 0.495		rho = 0.04,
p = 0.700		rho = 0.20,
p = 0.075
ERQ-Erho = 0.14,
p = 0.215		rho = –0.11,
p = 0.338		rho = –0.17,
p = 0.114		rho = –0.21,
p = 0.059		rho = –0.03,
p = 0.769
ERQ-Srho = –0.13,
p = 0.230		rho = –0.04,
p = 0.727		rho = 0.15,
p = 0.187		rho = 0.10,
p = 0.346		rho = 0.17,
p = 0.128
Clinical variablesIllness durationrho = 0.08,
p = 0.480		rho = –0.04,
p = 0.737		rho = –0.05,
p = 0.650		rho = –0.02,
p = 0.849		rho = –0.10,
p = 0.351
Family historyrho = 0.16,
p = 0.142		rho = 0.04,
p = 0.706		rho = 0.05,
p = 0.648		rho = –0.04,
p = 0.700		rho = –0.01,
p = 0.908
MDDrho = –0.11,
p = 0.317		rho = 0.17,
p = 0.123		rho = 0.02,
p = 0.882		rho = –0.04,
p = 0.697		rho = –0.11,
p = 0.324
GADrho = 0.11,
p = 0.335		rho = 0.16,
p = 0.162		rho = 0.02,
p = 0.851		rho = 0.03,
p = 0.797		rho = –0.03,
p = 0.755
BDrho = 0.17,
p = 0.124		rho = –0.12,
p = 0.288		rho = 0.03,
p = 0.801		rho = 0.04,
p = 0.707		rho = 0.05,
p = 0.630
Appendix 1—table 5
Bivariate correlations between mood parameters and socio-demographic clinical variables.

p values lower than 0.05 were highlighted in bold.

βCRβGRγβo
DemographicsGenderrho = 0.15,
p = 0.168		rho = 0.23,
p = 0.033		rho = 0.08,
p = 0.465		rho = –0.17,
p = 0.126
Agerho = 0.07,
p = 0.503		rho = –0.27,
p = 0.012		rho = 0.06,
p = 0.615		rho = 0.28,
p = 0.010
Social variablesCTQrho = 0.04,
p = 0.739		rho = 0.07,
p = 0.545		rho = –0.06,
p = 0.610		rho = –0.02,
p = 0.866
ERQ-Erho = 0.09,
p = 0.440		rho = –0.26,
p = 0.017		rho = –0.13,
p = 0.255		rho = 0.46,
P < 0.001
ERQ-Srho = –0.19,
p = 0. 086		rho = –0.06,
p = 0.59 9		rho = –0.14,
p = 0.217		rho = –0.16,
p = 0.142
Clinical variablesIllness durationrho = –0.01,
p = 0.910		rho = –0.10,
p = 0.366		rho = –0.03,
p = 0.788		rho = –0.02,
p = 0.861
Family historyrho = 0.06,
p = 0.590		rho = –0.01,
p = 0.908		rho = –0.09,
p = 0.403		rho = 0.13,
p = 0.231
MDDrho = –0.02,
p = 0.864		rho = 0.09,
p = 0.396		rho = –0.07,
p = 0.521		rho = –0.21,
p = 0.053
GADrho = –0.06,
p = 0.569		rho = 0.05,
p = 0.627		rho = 0.01,
p = 0.912		rho = –0.08,
p = 0.491
BDrho = 0.16,
p = 0.153		rho = –0.07,
p = 0.542		rho = –0.02,
p = 0.888		rho = 0.16,
p = 0.160
Appendix 1—table 6
Mood model comparison by separating gambling outcomes into better and worse parts.
Model #Model specification# of parametersΔ BICMean R2Δ BIC for each group
HCS−S+
mM3β0, βCR, βGR, γ400.42000
mM7β0, βCR, βGR_better, βGR_worse, γ5–331.480.49–355.10–6.5630.18
mM8β0, βCR, βGR_better, βGR_worse, γCR, γGR_better, γGR_better7–105.400.56–313.0981.34126.34

  1. ΔBIC, Bayesian information criterion relative to the winning model in S+ group (mM3); HC, healthy control; S-, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior.

Appendix 1—table 7
Choice model comparison by integrating mood or adding traditional bias.
Model #Model specification# of parametersΔ BICMean R2Δ BIC for each group
HCS−S+
cM3λ, α, βgain, βloss, µ500.37000
cmM1λ, α, βgain, βloss, µ, βMood65530.230.39287.2068.76174.27
cmM2λ, α, βgain, βloss, µ, βMood-CR, βMood-GR71031.180.41577.03123.84330.32
cM4λ, α, µ, βbias4376.750.32277.6534.3164.79

  1. ΔBIC, Bayesian information criterion relative to the winning model (cM3); HC, healthy control; S-, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior.

Appendix 1—table 8
Mood model comparison by adding a term for whether participants gambled or not, independent of the gambling value.
Model #Model specification# of parametersΔ BICMean R2Δ BIC for each group
HCS-S+
mM3β0, βCR, βGR, γ400.42000
mM9β0, βCR, βGR βgamble, γ5–373.130.49–371.83–40.7439.45

  1. ΔBIC, Bayesian information criterion relative to the winning model in S+ group (mM3); HC, healthy control; S-, patients without suicidal thoughts and behavior; S+, patients with suicidal thoughts and behavior.

Appendix 1—table 9
Bayesian independent sample t-tests of median-split anxiety and depression scores (including TAI, PSWQ, BDI, and CESD) on main results (gambling rate, approach parameter (βgain), and mood sensitivity to certain rewards (βCR)) support that general symptoms of anxiety and depression overall did not influence our main results.

BF₀₁ is a Bayes factor comparing the null model (M₀) to the alternative model (M₁), where M₀ assumes no group difference. BF₀₁ >1 indicates that evidence favors M₀. Generally, Bayes Factors between 1 and 3 were interpreted as anecdotal evidence and between 3 and 10 as moderate evidence.

BF01TAIPSWQBDICESD
Gambling rate4.0802.7682.4250.820
βgain3.8193.9112.9871.128
βCR3.7043.8261.1853.178
Appendix 1—table 10
Linear regressions of gambling behavior, value-insensitive approach parameter (βgain), and mood sensitivity to certain rewards (βCR) on group as a predictor (1 for S+ group and 0 for S- group) and scores for anxiety and depression as covariates.
Gambling rateβgainβCR
Groupβ = 0.164, t = 2.305,
p = 0.024		β = 0.374, t = 2.257,
p = 0.027		β = –0.105, t = –3.461,
p = 0.001
TAIβ = –0.010, t = –1.796,
p = 0.077		β = –0.008, t = –0.649,
p = 0.519		β = 0.005, t = 1.921,
p = 0.059
PSWQβ = –0.001, t = –0.401,
p = 0.690		β = –0.008, t = –0.968,
p = 0.337		β = –0.002, t = –1.282,
p = 0.204
BDIβ = 0.002, t = 0.519,
p = 0.606		β = –0.003, t = –0.272,
p = 0.787		β = –0.004, t = –2.302,
p = 0.025
CESDβ = 0.006, t = 1.585,
p = 0.118		β = 0.015, t = 1.652,
p = 0.103		β = 0.003, t = 1.942,
p = 0.056
Appendix 1—table 11
Linear regressions of gambling behavior, value-insensitive approach parameter (βgain), and mood sensitivity to certain rewards (βCR) on group as a predictor (1 for S+ group and 0 for S- group) and orthogonal components of anxiety and depression as covariates.
Gambling rateβgainβCR
Groupβ = 0.164, t = 2.305,
p = 0.024		β = 0.378, t = 2.257,
p = 0.027		β = –0.105, t = –3.461,
p = 0.001
PC1β = –0.007, t = –0.425,
p = 0.672		β = –0.010, t = –0.247,
p = 0.806		β = 0.009, t = 1.169,
p = 0.247
PC2β = –0.073, t = –1.569,
p = 0.122		β = –0.164, t = –1.509,
p = 0.136		β = –0.011, t = –0.532,
p = 0.596
PC3β = 0.098, t = 1.429,
p = 0.158		β = 0.205, t = 1.283,
p = 0.204		β = 0.037, t = 1.255,
p = 0.214
PC4β = –0.086, t = –1.133,
p = 0.262		β = 0.010, t = 0.054,
p = 0.957		β = 0.086, t = 2.657,
p = 0.010

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  1. Zhihao Wang
  2. Tian Nan
  3. Fengmei Lu
  4. Yu Yue
  5. Xiao Cai
  6. Zongling He
  7. Yuejia Luo
  8. Ting Wang
  9. Bastien Blain
(2026)
Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients
eLife 14:RP108002.
https://doi.org/10.7554/eLife.108002.4