心理学报 ›› 2022, Vol. 54 ›› Issue (9): 1031-1047.doi: 10.3724/SP.J.1041.2022.01031
孙芳#, 宋巍#, 温晓通a(), 李欢欢a(), 欧阳李晟, 魏诗洁
收稿日期:
2021-12-16
发布日期:
2022-07-21
出版日期:
2022-09-25
通讯作者:
温晓通,李欢欢
E-mail:wenxiaotong@163.com;psylihh@ruc.edu.cn
作者简介:
# 为共同一作者
基金资助:
SUN Fang#, SONG Wei#, WEN Xiaotonga(), LI Huanhuana(), OUYANG Lisheng, WEI Shijie
Received:
2021-12-16
Online:
2022-07-21
Published:
2022-09-25
Contact:
WEN Xiaotong,LI Huanhuan
E-mail:wenxiaotong@163.com;psylihh@ruc.edu.cn
摘要:
采用支持向量机的特征递归选择算法, 创新性采用三维心理痛苦量表和自我参照情感激励延迟任务, 建构自杀意念分类模型的重要特征集, 并比较自杀意念和抑郁的分类模型重要特征集差异。结果发现, 痛苦逃避是自杀意念分类模型的首位特征; 基于痛苦加工特征的自杀意念多模态分类模型效能优良。研究首次证实了在机器学习建构复杂的自杀意念分类模型中, 痛苦逃避及其相关脑电成分的重要性。拓展了结合心理痛苦三因素模型和机器学习算法对自杀预测的临床应用可行性。
中图分类号:
孙芳, 宋巍, 温晓通, 李欢欢, 欧阳李晟, 魏诗洁. (2022). 痛苦逃避和自我参照惩罚条件下脑电特征对自杀意念的分类效能. 心理学报, 54(9), 1031-1047.
SUN Fang, SONG Wei, WEN Xiaotong, LI Huanhuan, OUYANG Lisheng, WEI Shijie. (2022). Efficacy of suicide ideation classification based on pain avoidance and the EEG characteristics under self-referential punishment. Acta Psychologica Sinica, 54(9), 1031-1047.
变量 | HC (n = 32) | HSI (n = 25) | LSI (n = 20) | F/χ2 | pa | Post hocb |
---|---|---|---|---|---|---|
年龄(岁) | 22.03 (2.80) | 20.40 (2.14) | 19.85 (1.87) | 6.10 | 0.004 | HSI < HC, LSI < HC |
性别(男/女) | 14/18 | 10/15 | 6/14 | 0.99 | 0.608 | — |
BDI | 3.38 (2.41) | 20.68 (6.10) | 18.40 (4.25) | 131.23 | < 0.001 | HSI > HC, LSI > HC |
BSI-C | 0.13 (0.34) | 6.92 (5.03) | 0.30 (0.47) | 45.96 | < 0.001 | HSI > HC, HSI > LSI |
BSI-W | 1.81 (2.65) | 17.84 (7.23) | 3.50 (3.44) | 87.91 | < 0.001 | HSI > HC, HSI > LSI |
TDPPS | 31.69 (11.81) | 53.48 (11.27) | 42.85 (12.75) | 23.70 | < 0.001 | HSI > LSI > HC |
痛苦唤醒 | 13.94 (5.47) | 24.20 (6.24) | 19.65 (7.45) | 19.03 | < 0.001 | HSI > HC, LSI > HC |
痛苦体验 | 14.31 (6.17) | 22.16 (4.22) | 19.55 (4.74) | 16.60 | < 0.001 | HSI > HC, LSI > HC |
痛苦逃避 | 3.44 (1.22) | 7.12 (3.13) | 3.65 (1.57) | 24.83 | < 0.001 | HSI > HC, HSI > LSI |
表1 样本人口统计学特征和临床量表得分
变量 | HC (n = 32) | HSI (n = 25) | LSI (n = 20) | F/χ2 | pa | Post hocb |
---|---|---|---|---|---|---|
年龄(岁) | 22.03 (2.80) | 20.40 (2.14) | 19.85 (1.87) | 6.10 | 0.004 | HSI < HC, LSI < HC |
性别(男/女) | 14/18 | 10/15 | 6/14 | 0.99 | 0.608 | — |
BDI | 3.38 (2.41) | 20.68 (6.10) | 18.40 (4.25) | 131.23 | < 0.001 | HSI > HC, LSI > HC |
BSI-C | 0.13 (0.34) | 6.92 (5.03) | 0.30 (0.47) | 45.96 | < 0.001 | HSI > HC, HSI > LSI |
BSI-W | 1.81 (2.65) | 17.84 (7.23) | 3.50 (3.44) | 87.91 | < 0.001 | HSI > HC, HSI > LSI |
TDPPS | 31.69 (11.81) | 53.48 (11.27) | 42.85 (12.75) | 23.70 | < 0.001 | HSI > LSI > HC |
痛苦唤醒 | 13.94 (5.47) | 24.20 (6.24) | 19.65 (7.45) | 19.03 | < 0.001 | HSI > HC, LSI > HC |
痛苦体验 | 14.31 (6.17) | 22.16 (4.22) | 19.55 (4.74) | 16.60 | < 0.001 | HSI > HC, LSI > HC |
痛苦逃避 | 3.44 (1.22) | 7.12 (3.13) | 3.65 (1.57) | 24.83 | < 0.001 | HSI > HC, HSI > LSI |
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|
1. BDI | — | ||||||
2. BSI-C | 0.44*** | — | |||||
3. BSI-W | 0.58*** | 0.81*** | — | ||||
4. TDPPS | 0.63*** | 0.44*** | 0.61*** | — | |||
5. 痛苦唤醒 | 0.59*** | 0.35** | 0.54*** | 0.96*** | — | ||
6. 痛苦体验 | 0.59*** | 0.32** | 0.49*** | 0.93*** | 0.83*** | — | |
7. 痛苦逃避 | 0.46** | 0.74*** | 0.73*** | 0.71*** | 0.61*** | 0.54*** | — |
表2 临床量表得分之间的相关分析(r)
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|
1. BDI | — | ||||||
2. BSI-C | 0.44*** | — | |||||
3. BSI-W | 0.58*** | 0.81*** | — | ||||
4. TDPPS | 0.63*** | 0.44*** | 0.61*** | — | |||
5. 痛苦唤醒 | 0.59*** | 0.35** | 0.54*** | 0.96*** | — | ||
6. 痛苦体验 | 0.59*** | 0.32** | 0.49*** | 0.93*** | 0.83*** | — | |
7. 痛苦逃避 | 0.46** | 0.74*** | 0.73*** | 0.71*** | 0.61*** | 0.54*** | — |
痛苦体验 | 痛苦逃避 | 抑郁b | 自杀意念b |
---|---|---|---|
他人_惩中_cue-CNV | 他人_奖中_target-P3 | 痛苦体验 | 痛苦逃避 |
他人_奖中_cue-CNV | 自我_惩中_pos-LPP | 痛苦唤醒 | 抑郁 |
他人_惩中_cue-delta | 自我_奖中_neg-LPP | 年龄 | 自我_惩中_cue-CNV |
自我_惩中_cue-P3 | 自我_惩中_pos-P3 | 自我_惩中_neg-FRN | 自我_惩中_neg-LPP |
自我_奖中_neg-LPP | 自我_奖中_target-delta | 自我_奖中_neg-FRN | 自我_惩中_target-P3 |
他人_奖中_pos-P3 | 自我_惩中_target-P3 | 自我_奖中_neg-LPP | 自我_惩中_neg-P3 |
自我_奖中_cue-beta | 他人_惩中_cue-theta | 自我_惩中_target-delta | 他人_奖中_cue-theta |
a他人_奖中_neg-theta | 自我_奖中_neg-delta | 自我_奖中_cue-delta | 自我_奖中_target-delta |
自我_惩中_cue-CNV | 自我_奖中_cue-P3 | 他人_奖中_cue-theta | 他人_惩中_target-delta |
自我_惩中_cue-beta | 他人_惩中_neg-LPP | 痛苦逃避 | 他人_奖中_target-P3 |
表3 四个分类模型的重要特征集
痛苦体验 | 痛苦逃避 | 抑郁b | 自杀意念b |
---|---|---|---|
他人_惩中_cue-CNV | 他人_奖中_target-P3 | 痛苦体验 | 痛苦逃避 |
他人_奖中_cue-CNV | 自我_惩中_pos-LPP | 痛苦唤醒 | 抑郁 |
他人_惩中_cue-delta | 自我_奖中_neg-LPP | 年龄 | 自我_惩中_cue-CNV |
自我_惩中_cue-P3 | 自我_惩中_pos-P3 | 自我_惩中_neg-FRN | 自我_惩中_neg-LPP |
自我_奖中_neg-LPP | 自我_奖中_target-delta | 自我_奖中_neg-FRN | 自我_惩中_target-P3 |
他人_奖中_pos-P3 | 自我_惩中_target-P3 | 自我_奖中_neg-LPP | 自我_惩中_neg-P3 |
自我_奖中_cue-beta | 他人_惩中_cue-theta | 自我_惩中_target-delta | 他人_奖中_cue-theta |
a他人_奖中_neg-theta | 自我_奖中_neg-delta | 自我_奖中_cue-delta | 自我_奖中_target-delta |
自我_惩中_cue-CNV | 自我_奖中_cue-P3 | 他人_奖中_cue-theta | 他人_惩中_target-delta |
自我_惩中_cue-beta | 他人_惩中_neg-LPP | 痛苦逃避 | 他人_奖中_target-P3 |
指标 | 痛苦体验 | 痛苦逃避 | 抑郁 | 自杀意念 | ||
---|---|---|---|---|---|---|
单模态 | 多模态 | 单模态 | 多模态 | |||
Accuracy | 63.31% | 75.11% | 62.21% | 73.83% | 65.43% | 85.66% |
Precision | 0.67 | 0.44 | 0.65 | 0.76 | 0.40 | 0.82 |
Recall | 0.76 | 0.16 | 0.85 | 0.83 | 0.21 | 0.73 |
AUC | 0.64 | 0.67 | 0.63 | 0.80 | 0.57 | 0.92 |
表4 四个分类模型的评估指标
指标 | 痛苦体验 | 痛苦逃避 | 抑郁 | 自杀意念 | ||
---|---|---|---|---|---|---|
单模态 | 多模态 | 单模态 | 多模态 | |||
Accuracy | 63.31% | 75.11% | 62.21% | 73.83% | 65.43% | 85.66% |
Precision | 0.67 | 0.44 | 0.65 | 0.76 | 0.40 | 0.82 |
Recall | 0.76 | 0.16 | 0.85 | 0.83 | 0.21 | 0.73 |
AUC | 0.64 | 0.67 | 0.63 | 0.80 | 0.57 | 0.92 |
频段 | 年龄 | BDI | BSI-C | BSI-W | TDPPS | 痛苦唤醒 | 痛苦体验 | 痛苦逃避 |
---|---|---|---|---|---|---|---|---|
Delta | -0.28* | -0.12 | -0.18 | -0.26* | -0.29* | -0.30** | -0.23+ | -0.26* |
Theta | -0.23* | -0.10 | 0.02 | -0.09 | -0.12 | -0.16 | -0.08 | -0.02 |
Beta | -0.30** | -0.07 | -0.18 | -0.24* | -0.27* | -0.28* | -0.22+ | -0.23+ |
附表1 三组被试静息态各频段能量与临床量表的相关关系(r)
频段 | 年龄 | BDI | BSI-C | BSI-W | TDPPS | 痛苦唤醒 | 痛苦体验 | 痛苦逃避 |
---|---|---|---|---|---|---|---|---|
Delta | -0.28* | -0.12 | -0.18 | -0.26* | -0.29* | -0.30** | -0.23+ | -0.26* |
Theta | -0.23* | -0.10 | 0.02 | -0.09 | -0.12 | -0.16 | -0.08 | -0.02 |
Beta | -0.30** | -0.07 | -0.18 | -0.24* | -0.27* | -0.28* | -0.22+ | -0.23+ |
变量 | BDI | BSI-C | BSI-W | TDPPS | 痛苦唤醒 | 痛苦体验 | 痛苦逃避 |
---|---|---|---|---|---|---|---|
他人_奖励-FRN | 0.021 | -0.061 | -0.098 | -0.273* | -0.246* | -0.237* | -0.276* |
他人_惩罚-FRN | 0.002 | -0.069 | -0.099 | -0.224* | -0.184 | -0.192+ | -0.281* |
他人_中性-FRN | 0.020 | -0.068 | -0.083 | -0.277* | -0.248* | -0.228* | -0.315** |
自我_奖励-FRN | -0.026 | -0.065 | -0.070 | -0.220* | -0.181 | -0.205+ | -0.240* |
自我_惩罚-FRN | 0.090 | 0.062 | 0.038 | -0.150 | -0.131 | -0.119 | -0.190+ |
自我_中性-FRN | -0.062 | -0.066 | -0.094 | -0.271* | -0.279* | -0.195+ | -0.267* |
自我_中性-LPP | -0.148 | -0.141 | -0.138 | -0.194+ | -0.167 | -0.200+ | -0.143 |
他人_奖励_delta | 0.205 | 0.174 | 0.209 | -0.231* | -0.244* | 0.171 | 0.205 |
自我_奖励_delta | 0.080 | 0.062 | 0.053 | 0.211 | -0.256* | 0.097 | -0.232* |
自我_中性_delta | 0.041 | 0.206 | 0.240* | 0.14 | 0.114 | 0.108 | 0.208 |
a他人_奖励_theta | -0.342** | 0.202 | -0.241* | -0.254* | -0.261* | 0.203 | 0.209 |
a自我_中性_theta | 0.075 | 0.232* | 0.258* | 0.133 | 0.109 | 0.089 | 0.228* |
b他人_奖励_theta | -0.311** | 0.182 | 0.216 | -0.234* | -0.235* | 0.197 | 0.184 |
b自我_中性_theta | 0.069 | 0.228* | 0.248* | 0.129 | 0.104 | 0.088 | 0.221 |
附表2 负反馈条件下脑电成分平均波幅(能量)与量表相关结果(r)
变量 | BDI | BSI-C | BSI-W | TDPPS | 痛苦唤醒 | 痛苦体验 | 痛苦逃避 |
---|---|---|---|---|---|---|---|
他人_奖励-FRN | 0.021 | -0.061 | -0.098 | -0.273* | -0.246* | -0.237* | -0.276* |
他人_惩罚-FRN | 0.002 | -0.069 | -0.099 | -0.224* | -0.184 | -0.192+ | -0.281* |
他人_中性-FRN | 0.020 | -0.068 | -0.083 | -0.277* | -0.248* | -0.228* | -0.315** |
自我_奖励-FRN | -0.026 | -0.065 | -0.070 | -0.220* | -0.181 | -0.205+ | -0.240* |
自我_惩罚-FRN | 0.090 | 0.062 | 0.038 | -0.150 | -0.131 | -0.119 | -0.190+ |
自我_中性-FRN | -0.062 | -0.066 | -0.094 | -0.271* | -0.279* | -0.195+ | -0.267* |
自我_中性-LPP | -0.148 | -0.141 | -0.138 | -0.194+ | -0.167 | -0.200+ | -0.143 |
他人_奖励_delta | 0.205 | 0.174 | 0.209 | -0.231* | -0.244* | 0.171 | 0.205 |
自我_奖励_delta | 0.080 | 0.062 | 0.053 | 0.211 | -0.256* | 0.097 | -0.232* |
自我_中性_delta | 0.041 | 0.206 | 0.240* | 0.14 | 0.114 | 0.108 | 0.208 |
a他人_奖励_theta | -0.342** | 0.202 | -0.241* | -0.254* | -0.261* | 0.203 | 0.209 |
a自我_中性_theta | 0.075 | 0.232* | 0.258* | 0.133 | 0.109 | 0.089 | 0.228* |
b他人_奖励_theta | -0.311** | 0.182 | 0.216 | -0.234* | -0.235* | 0.197 | 0.184 |
b自我_中性_theta | 0.069 | 0.228* | 0.248* | 0.129 | 0.104 | 0.088 | 0.221 |
[1] | Albanese, B. J., Macatee, R. J., Gallyer, A. J., Stanley, I. H., Joiner, T. E., & Schmidt, N. B. (2019). Impaired conflict detection differentiates suicide attempters from ideating nonattempters: Evidence from event-related potentials. Biological Psychiatry Cognition Neuroscience Neuroimaging, 4(10), 902-912. |
[2] |
Angus, D. J., Latham, A. J., Harmon-Jones, E., Deliano, M., Balleine, B., & Braddon-Mitchell, D. (2017). Electrocortical components of anticipation and consumption in a monetary incentive delay task. Psychophysiology, 54(11), 1686-1705.
doi: 10.1111/psyp.12913 URL |
[3] | Bao, J. M., Li, H. H., Song, W., & Jiang, S.Y. (2020). Being bullied, psychological pain and suicidal ideation among Chinese adolescents: A moderated mediation model. Children and Youth Services Review, 109, e104744. |
[4] |
Beck, A. T., Brown, G. K., Steer, R. A., Dahlsgaard, K. K., & Grisham, J. R. (1999). Suicide Ideation at its worst point: A Predictor of eventual suicide in psychiatric outpatients. Suicide and Life-Threatening Behavior, 29(1), 1-9.
pmid: 10322616 |
[5] |
Beck, A. T., Steer, R. A., & Ranieri, W. F. (1988). Scale for suicide ideation: Psychometric properties of a self-report version. Journal of Clinical Psychology, 44(4), 499-505.
pmid: 3170753 |
[6] | Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck depression inventory. San Antonio, TX: Psychological Corporation. |
[7] |
Becker, M. P., Nitsch, A. M., Miltner, W. H., & Straube, T. (2014). A single-trial estimation of the feedback-related negativity and its relation to BOLD responses in a time- estimation task. Journal of Neuroscience, 34(8), 3005-3012.
doi: 10.1523/JNEUROSCI.3684-13.2014 URL |
[8] |
Belsher, B. E., Smolenski, D. J., Pruitt, L. D., Bush, N. E., Beech, E. H., Workman, D. E., ... Skopp, N. A. (2019). Prediction models for suicide attempts and deaths: A systematic review and simulation. JAMA Psychiatry, 76(6), 642-651.
doi: 10.1001/jamapsychiatry.2019.0174 URL |
[9] | Benschop, L., Baeken, C., Vanderhasselt, M.-A., van de Steen, F., van Heeringen, K., & Arns, M. (2019). Electroencephalogram resting state frequency power characteristics of suicidal behavior in female patients with major depressive disorder. The Journal of Clinical Psychiatry, 80(6), 18m12661. |
[10] |
Bernat, E. M., Nelson, L. D., & Baskin-Sommers, A. R. (2015). Time-frequency theta and delta measures index separable components of feedback processing in a gambling task. Psychophysiology, 52(5), 626-637.
doi: 10.1111/psyp.12390 URL |
[11] |
Broyd, S. J., Richards, H. J., Helps, S. K., Chronaki, G., Bamford, S., & Sonuga-Barke, E. J. (2012). An electrophysiological monetary incentive delay (e-MID) task: A way to decompose the different components of neural response to positive and negative monetary reinforcement. Journal of Neuroscience Methods, 209(1), 40-49.
doi: 10.1016/j.jneumeth.2012.05.015 URL |
[12] |
Burke, T. A., Ammerman, B. A., & Jacobucci, R. (2019). The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review. Journal of Affective Disorders, 245, 869-884.
doi: 10.1016/j.jad.2018.11.073 URL |
[13] |
Burke, T. A., Jacobucci, R., Ammerman, B. A., Piccirillo, M., McCloskey, M. S., Heimberg, R. G., & Alloy, L. B. (2018). Identifying the relative importance of non-suicidal self-injury features in classifying suicidal ideation, plans, and behavior using exploratory data mining. Psychiatry Research, 262, 175-183.
doi: 10.1016/j.psychres.2018.01.045 URL |
[14] |
Campos, R. C., Holden, R. R., & Lambert, C. E. (2019). Avoidance of psychological pain and suicidal ideation in community samples: Replication across two countries and two languages. Journal of Clinical Psychology, 75(12), 2160-2168.
doi: 10.1002/jclp.22837 pmid: 31332793 |
[15] |
Campos, R. C., Simões, A., Costa, S., Pio, A. S., & Holden, R. R. (2020). Psychological pain and suicidal ideation in undergraduates: The role of pain avoidance. Death Studies, 44(6), 375-378.
doi: 10.1080/07481187.2018.1554610 pmid: 30912716 |
[16] | Cao, Y., Tung, W.-W., Gao, J. B., Protopopescu, V. A., & Hively, L. M. (2004). Detecting dynamical changes in time series using the permutation entropy. Physical Review. E, 70(4), e046217. |
[17] |
Cichy, R. M., & Oliva, A. (2020). A M/EEG-fMRI fusion primer: Resolving human brain responses in space and time. Neuron, 107(5), 772-781.
doi: 10.1016/j.neuron.2020.07.001 URL |
[18] | Cohen, M. X., & Cavanagh, J. F. (2011). Single-trial regression elucidates the role of prefrontal theta oscillations in response conflict. Frontiers in Psychology, 2(30), 1-12. |
[19] | Colic, S., Richardson, D. J., Reilly, P. J., & Hasey, M. G. (2018). Using machine learning algorithms to enhance the management of suicide ideation. Paper presented at the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). |
[20] | Cortes, C., & Vapnik, V. (1995). Support vector networks. Machine Learning, 20(3), 273-297. |
[21] | Dan, M. P., Mircea, O., & Mihaela, M. (2000). EEG: Relative power versus absolute power mapping advantages, disadvantages. Romanian Journal of Neurology, 38(1/2), 21-33. |
[22] |
de Aguiar Neto, F. S., & Rosa, J. L. G. (2019). Depression biomarkers using non-invasive EEG: A review. Neuroscience & Biobehavioral Reviews, 105, 83-93.
doi: 10.1016/j.neubiorev.2019.07.021 URL |
[23] |
Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21.
doi: 10.1016/j.jneumeth.2003.10.009 pmid: 15102499 |
[24] |
Dolsen, M. R., Cheng, P., Arnedt, J. T., Swanson, L., Casement, M. D., Kim, H. S., ... Deldin, P. J. (2017). Neurophysiological correlates of suicidal ideation in major depressive disorder: Hyperarousal during sleep. Journal of Affective Disorders, 212, 160-166.
doi: 10.1016/j.jad.2017.01.025 URL |
[25] |
Dong, M., Wang, S. B., Li, Y., Xu, D. D., Ungvari, G. S., Ng, C. H., ... Xiang, Y. T. (2018). Prevalence of suicidal behaviors in patients with major depressive disorder in China: A comprehensive meta-analysis. Journal of Affective Disorders, 225, 32-39.
doi: S0165-0327(17)31155-2 pmid: 28779680 |
[26] |
Franklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., ... Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological Bulletin, 143(2), 187-232.
doi: 10.1037/bul0000084 pmid: 27841450 |
[27] |
Gibb, B. E., & Tsypes, A. (2019). Using event-related potentials to improve our prediction of suicide risk. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(10), 854-855.
doi: 10.1016/j.bpsc.2019.08.003 URL |
[28] |
Gilbert, J. R., Ballard, E. D., Galiano, C. S., Nugent, A. C., & Zarate, C. A., Jr. (2020). Magnetoencephalographic correlates of suicidal ideation in major depression. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5(3), 354-363.
doi: 10.1016/j.bpsc.2019.11.011 URL |
[29] |
Glazer, J. E., Kelley, N. J., Pornpattananangkul, N., Mittal, V. A., & Nusslock, R. (2018). Beyond the FRN: Broadening the time-course of EEG and ERP components implicated in reward processing. International Journal of Psychophysiology, 132(Pt B),184-202.
doi: S0167-8760(17)30473-7 pmid: 29454641 |
[30] | Gong, X., Huang Y. X., Wang Y., & Luo Y. J. (2011). Revision of the Chinese facial affective picture system. Chinese Mental Health Journal, 25(1), 40-46. |
[龚栩, 黄宇霞, 王妍, 罗跃嘉. (2011). 中国面孔表情图片系统的修订. 中国心理卫生杂志, 25(1), 40-46.] | |
[31] | Guo, T. (2017). Electrophysiological response to incentive delay task in depressed patients with suicide attempt and its relationship to psychological pain (Unpublished master’s thesis). Renmin university of China, Beijing. |
[郭婷. (2017). 自杀未遂抑郁症患者在激励延迟任务中的脑电特征及其与心理痛苦的关系 (硕士学位论文). 中国人民大学, 北京.] | |
[32] | Guo, T., Li, H. H., Wang, X., Lin, Y. X., Fan, L. J., Zhang, B., & Ouyang, Z. R. (2016). Comparative study of event-related EEG responses to process monetary and affective incentive delay tasks. Chinese Journal of Clinical Psychology, 24(6), 963-970. |
[郭婷, 李欢欢, 王湘, 林亦轩, 范乐佳, 张蓓, 欧阳紫榕. (2016). 金钱激励和情感激励延迟加工的事件相关电位比较研究. 中国临床心理学杂志, 24(6), 963-970.] | |
[33] | Hasey, G., Colic, S., Reilly, J., MacCrimmon, D., Khodayari, A., DeBruin, H., & Mistry, N. (2020). Detection of suicidal ideation in depressed subjects using resting electroencephalography features identified by machine learning algorithms. Biological Psychiatry, 87(9), S380-S381. |
[34] |
Hou, L. L., Chen, L. R., & Zhou, R. L. (2020). Altered reward processing in women with premenstrual syndrome: Evidence from ERPs and time-frequency analysis. Acta Psychologica Sinica, 52(6), 742-757.
doi: 10.3724/SP.J.1041.2020.00742 URL |
[侯璐璐, 陈莅蓉, 周仁来. (2020). 经前期综合征与奖赏进程失调——来自脑电的证据. 心理学报, 52(6), 742-757.] | |
[35] |
Jordan, P., Shedden-Mora, M. C., & Lowe, B. (2018). Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables. General Hospital Psychiatry, 51, 106-111.
doi: 10.1016/j.genhosppsych.2018.02.002 URL |
[36] |
Jorm, A. (2000). Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychological Medicine, 30(1), 11-22.
pmid: 10722172 |
[37] | Juba, B., & Le, H. S. (2019). Precision-recall versus accuracy and the role of large data sets. Proceedings of the AAAI Conference on Artificial Intelligence, 33, 4039-4048. |
[38] | Jung, Y. (2018). Multiple predicting K-fold cross-validation for model selection. Journal of Nonparametric Statistics, 30(1), 197-215. |
[39] |
Knyazev, G. G. (2012). EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neuroscience & Biobehavioral Reviews, 36(1), 677-695.
doi: 10.1016/j.neubiorev.2011.10.002 URL |
[40] |
Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Brak, I. V., Osipov, E. A., Filimonova, E. A., ... Aftanas, L. I. (2018). Task-positive and task-negative networks in major depressive disorder: A combined fMRI and EEG study. Journal of Affective Disorders, 235, 211-219.
doi: 10.1016/j.jad.2018.04.003 URL |
[41] |
Kudinova, A. Y., Owens, M., Burkhouse, K. L., Barretto, K. M., Bonanno, G. A., & Gibb, B. E. (2015). Differences in emotion modulation using cognitive reappraisal in individuals with and without suicidal ideation: An ERP study. Cognition Emotion, 30(5), 999-1007.
doi: 10.1080/02699931.2015.1036841 URL |
[42] | Lang, W. C., & Forinash, K. (1998). Time-frequency analysis by continuous wavelet transform. Bulletin of the Computational Statistics of Japan, 10(2), 93-101. |
[43] |
Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling, 20(1), 1-26.
doi: 10.1080/10705511.2013.742377 URL |
[44] |
Lee, P. F., Kan, D. P. X., Croarkin, P., Phang, C. K., & Doruk, D. (2018). Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study. Journal of Clinical Neuroscience, 47, 315-322.
doi: 10.1016/j.jocn.2017.09.030 URL |
[45] |
Lee, S. M., Jang, K. I., & Chae, J.-H. (2017). Electroencephalographic correlates of suicidal ideation in the theta band. Clinical EEG and Neuroscience, 48(5), 316- 321.
doi: 10.1177/1550059417692083 URL |
[46] |
Lew, B., Osman, A., Huen, J. M. Y., Siau, C. S., Talib, M. A., Cunxian, J., ... Leung, A. N. M. (2020). A comparison between American and Chinese college students on suicide- related behavior parameters. International Journal of Clinical and Health Psychology, 20(2), 108-117.
doi: 10.1016/j.ijchp.2020.03.005 URL |
[47] | Li, H. H., Fu, R., Zou, Y. M., & Cui, Y. Y. (2017). Predictive roles of three-dimensional psychological pain, psychache, and depression in suicidal ideation among Chinese college students. Frontiers in Psychology, 8, 1-8. |
[48] |
Li, H. H., Xie, W. Z., Luo, X. W., Fu, R., Shi, C., Ying, X. Y., ... Wang, X. (2014). Clarifying the role of psychological pain in the risks of suicidal ideation and suicidal acts among patients with major depressive episodes. Suicide and Life-Threatening Behavior, 44(1), 78-88.
doi: 10.1111/sltb.12056 URL |
[49] | Li, X. Y., Fei, L. P., Zhang, Y. L., Xu, D., Dong, Y. S., Yang, F. D., & Kuang, L. (2011). Reliability and validity of the Chinese version of Beck Scate for Suicide Ideation (BSI-CV) among university students. Chinese Mental Health Journal, 25(11), 862-866. |
[李献云, 费立鹏, 张亚利, 徐东, 童永胜, 杨甫德, 况利. (2011). Beck自杀意念量表中文版在大学学生中应用的信效度. 中国心理卫生杂志, 25(11), 862-866.] | |
[50] |
Liu, J., Li, J. Q., Shen, C. R., Hu, X. H., Zhao, T. H., Guan, Q., & Luo, Y. J. (2020). The neural mechanism of approximate number processing for mathematical anxious individuals: An EEG study. Acta Psychologica Sinica, 52(8), 958-970.
doi: 10.3724/SP.J.1041.2020.00958 URL |
[刘洁, 李瑾琪, 申超然, 胡小惠, 赵庭浩, 关青, 罗跃嘉. (2020). 数学焦虑个体近似数量加工的神经机制: 一项EEG研究. 心理学报, 52(8), 958-970.] | |
[51] |
Mahato, S., & Paul, S. (2018). Detection of major depressive disorder using linear and non-linear features from EEG signals. Microsystem Technologies, 25(3), 1065-1076.
doi: 10.1007/s00542-018-4075-z URL |
[52] |
Marco-Pallares, J., Cucurell, D., Cunillera, T., Garcia, R., Andrés-Pueyo, A., Munte, T. F., & Rodriguez-Fornells, A. (2008). Human oscillatory activity associated to reward processing in a gambling task. Neuropsychologia, 46(1), 241-248.
pmid: 17804025 |
[53] | McKewen, M., Cooper, P. S., Wong, A. S. W., Michie, P. T., Sauseng, P., & Karayanidis, F. (2020). Task-switching costs have distinct phase-locked and nonphase-locked EEG power effects. Psychophysiology, 57(5), e13533. |
[54] |
Meerwijk, E. L., & Weiss, S. J. (2016). Does suicidal desire moderate the association between frontal delta power and psychological pain? PeerJ, 4, e1538.
doi: 10.7717/peerj.1538 URL |
[55] | Mei, S., Li, Q., Liu, X., & Zheng, Y. (2018). Monetary incentives modulate feedback-related brain activity. Scientific Reports, 8(1), e11913. |
[56] |
Miller, A. B., & Prinstein, M. J. (2019). Adolescent suicide as a failure of acute stress-response systems. Annual Review of Clinical Psychology, 15(1), 425-450.
doi: 10.1146/annurev-clinpsy-050718-095625 URL |
[57] | Mohammadi, Y., Hajian, M., & Moradi, M. H. (2019). Discrimination of depression levels using machine learning methods on EEG signals. Paper presented at the 2019 27th Iranian Conference on Electrical Engineering (ICEE). |
[58] | Nguyen, T., Tran, T., Gopakumar, S., Phung, D., & Venkatesh, S. (2016). An evaluation of randomized machine learning methods for redundant data: Predicting short and medium- term suicide risk from administrative records and risk assessments. arXiv. https://doi.org/10.48550/arXiv.1605.01116. |
[59] |
Patterson, A. A., & Holden, R. R. (2012). Psychache and suicide ideation among men who are homeless: A test of Shneidman’s model. Suicide and Life-Threatening Behavior, 42(2), 147-156.
doi: 10.1111/j.1943-278X.2011.00078.x pmid: 22324750 |
[60] |
Peng, W., Meng, J., Lou, Y., Li, X., Lei, Y., & Yan, D. (2019). Reduced empathic pain processing in patients with somatoform pain disorder: Evidence from behavioral and neurophysiological measures. International Journal of Psychophysiology, 139, 40-47.
doi: 10.1016/j.ijpsycho.2019.03.004 URL |
[61] |
Qin, P. (2011). The impact of psychiatric illness on suicide: Differences by diagnosis of disorders and by sex and age of subjects. Journal of Psychiatric Research, 45(11), 1445-1452.
doi: 10.1016/j.jpsychires.2011.06.002 URL |
[62] | Shim, M., Jin, M. J., Im, C. H., & Lee, S. H. (2019). Machine- learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features. Neuroimage Clinical, 24, e102001. |
[63] |
Shneidman, E. S. (1993). Suicide as psychache. Journal of Nervous and Mental Disease, 181(3), 145-147.
pmid: 8445372 |
[64] | Song, W. (2019). The relationship among self-related emotional processing, psychological pain and suicide in college students with depressive symptoms (Unpublished master’s thesis). Renmin university of China, Beijing. |
[宋巍. (2019). 抑郁大学生自我相关情绪信息加工模式及其与心理痛苦、自杀的关系 (硕士学位论文). 中国人民大学, 北京.] | |
[65] |
Song, W., Li, H. H., Guo, T., Jiang, S. Y., & Wang, X. (2019). Effect of affective reward on cognitive event-related potentials and its relationship with psychological pain and suicide risk among patients with major depressive disorder. Suicide and Life-Threatening Behavior, 49(5), 1290-1306.
doi: 10.1111/sltb.12524 pmid: 30390328 |
[66] | Song, W., Li, H. H., Guo, T., & Wang, X. (2018). The event-related EEG responses of MDD patients with suicide attempts to monetary incentive delay tasks and its relationship with the three-dimensional psychological pain. Chinese Journal of Clinical Psychology, 26(6), 1049-1056. |
[宋巍, 李欢欢, 郭婷, 王湘, 王淼. (2018). 金钱激励延迟任务下抑郁症自杀者的神经电生理特征及其与心理痛苦的关系. 中国临床心理学杂志, 26(6), 1049-1056.] | |
[67] |
Sun, X., Li, H., Song, W., Jiang, S., Shen, C., & Wang, X. (2020). ROC analysis of three-dimensional psychological pain in suicide ideation and suicide attempt among patients with major depressive disorder. Journal of Clinical Psychology, 76(1), 210-227.
doi: 10.1002/jclp.22870 URL |
[68] |
Tacikowski, P., & Nowicka, A. (2010). Allocation of attention to self-name and self-face: An ERP study. Biological Psychology, 84(2), 318-324.
doi: 10.1016/j.biopsycho.2010.03.009 pmid: 20298741 |
[69] |
Troister, T., & Holden, R. R. (2012). A two-year prospective study of psychache and its relationship to suicidality among high-risk undergraduates. Journal of clinical psychology, 68(9), 1019-1027.
doi: 10.1002/jclp.21869 pmid: 22644790 |
[70] |
Tsypes, A., Owens, M., & Gibb, B. E. (2020). Reward responsiveness in suicide attempters: An electroencephalography/event- related potential study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(1), 99-106.
doi: 10.1016/j.bpsc.2020.04.003 URL |
[71] |
Watts, A. T. M., Bachman, M. D., & Bernat, E. M. (2017). Expectancy effects in feedback processing are explained primarily by time-frequency delta not theta. Biological Psychology, 129, 242-252.
doi: 10.1016/j.biopsycho.2017.08.054 URL |
[72] |
Welch, P. D. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70-73.
doi: 10.1109/TAU.1967.1161901 URL |
[73] |
Winer, E. S., Drapeau, C. W., Veilleux, J. C., & Nadorff, M. R. (2016). The association between anhedonia, suicidal ideation, and suicide attempts in a large student sample. Archives of Suicide Research, 20(2), 265-272.
doi: 10.1080/13811118.2015.1025119 URL |
[74] | World Health Organization. (2021). Suicide [Fact sheet]. Retrieved from http://www.who.int/mediacentre/factsheets/fs398/en/ |
[75] | Wu, X., Zhong, C. P., Ding, Y. L., & Qu, Z. (2018). Application of time-frequency analysis in investigating non-phase locked components of EEG. Advances in Psychological Science, 26(8), 1349-1364. |
[武侠, 钟楚鹏, 丁玉珑, 曲折. (2018). 利用时频分析研究非相位锁定脑电活动. 心理科学进展, 26(8), 1349-1364.] | |
[76] |
Xie, W., Li, H. H., Luo, X. W., Fu, R., Ying, X. Y., Wang, N., ... Shi, C. (2014). Anhedonia and pain avoidance in the suicidal mind: Behavioral evidence for motivational manifestations of suicidal ideation in patients with major depressive disorder. Journal of Clinical Psychology, 70(7), 681-692.
doi: 10.1002/jclp.22055 URL |
[77] |
Yao, D., Qin, Y., Hu, S., Dong, L., Bringas Vega, M. L., & Valdés Sosa, P. A. (2019). Which reference should we use for EEG and ERP practice? Brain Topography, 32(4), 530- 549.
doi: 10.1007/s10548-019-00707-x URL |
[78] |
Zhu, X., Wu, H., Yang, S., & Gu, R. (2017). The influence of self-construal type on outcome evaluation: Evidence from event-related potentials. International Journal of Psychophysiology, 112, 64-69.
doi: 10.1016/j.ijpsycho.2016.12.010 URL |
[79] |
Zou, Y. M., Li, H. H., Shi, C., Lin, Y. X., Zhou, H. Y., & Zhang, J. Q. (2017). Efficacy of psychological pain theory- based cognitive therapy in suicidal patients with major depressive disorder: A pilot study. Psychiatry Research, 249, 23-29.
doi: 10.1016/j.psychres.2016.12.046 URL |
[1] | 谢慧, 林轩怡, 胡婉柔, 胡晓晴. 情绪调节促进负性社会反馈的遗忘:来自行为和脑电的证据[J]. 心理学报, 2023, 55(6): 905-919. |
[2] | 李为, 边子茗, 陈曦梅, 王俊杰, 罗一君, 刘永, 宋诗情, 高笑, 陈红. 9~12岁儿童应激与额颞区的关联: 来自多模态脑影像的证据[J]. 心理学报, 2023, 55(4): 572-587. |
[3] | 郝子雨, 李欢欢, 林亦轩. 抑郁症自杀未遂者的痛苦逃避与背外侧前额叶-脑岛有效连接特征[J]. 心理学报, 2023, 55(12): 1966-1978. |
[4] | 孙芳, 李欢欢, 郭玥言, 魏诗洁. “危”亦或“机”: 家庭-学校-社区风险和资源的潜在剖面结构与青少年心理危机的关系[J]. 心理学报, 2023, 55(11): 1827-1844. |
[5] | 覃慧怡, 丁丽洪, 段威, 雷旭. 脑电的重测信度:在多项静息态和任务态实验中的对比[J]. 心理学报, 2023, 55(10): 1587-1596. |
[6] | 章文佩, 沈群伦, 宋锦涛, 周仁来. 基于事件相关电位(ERPs)和机器学习的考试焦虑诊断 *[J]. 心理学报, 2019, 51(10): 1116-1127. |
[7] | 孙鑫, 黎坚, 符植煜. 利用游戏log-file预测学生推理能力和数学成绩——机器学习的应用[J]. 心理学报, 2018, 50(7): 761-770. |
[8] | 宫火良,王学志. 自杀意念高中生的社会信息编码特征[J]. 心理学报, 2012, 44(3): 304-313. |
[9] | 薛贵, 陈传升,吕忠林,董奇. 脑成像技术及其在决策研究中的应用[J]. 心理学报, 2010, 42(01): 120-137. |
[10] | 罗跃嘉,南云,李红. ERP研究反映感数与计数的不同脑机制[J]. 心理学报, 2004, 36(04): 434-441. |
[11] | 李德明,孙福立,焦艳. 额区脑波年老化特点及其与某些认知能力的相关性[J]. 心理学报, 1996, 28(1): 76-81. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||