Predictive modeling of antidepressant efficacy based on cognitive neuropsychological theory.

BACKGROUND: We aimed to develop a clinical predictive model based on the cognitive neuropsychological (CNP) theory and machine-learning to examine SSRI efficacy in the treatment of MDD. METHODS: Baseline assessments including clinical symptoms (HAMD, HAMA, BDI, and TEPS scores), negative biases (NEO-PI-R-N and NCPBQ scores), sociodemographic characteristics (social support and SES), and a 5-min eye-opening resting-state EEG were completed by 69 participants with first-episode major depressive disorder (MDD) and 36 healthy controls. The clinical symptoms and negative bias were again assessed after an 8-week treatment of depression with selective serotonin reuptake inhibitors (SSRIs). A multi-modality machine-learning model was developed to predict the effectiveness of SSRI antidepressants. RESULTS: At baseline, we observed significant differences between MDD patients and healthy controls in terms of social support, clinical symptoms, and negative bias characteristics (p < 0.001). A negative association was found (p < 0.05) between neuroticism and alpha asymmetry in both the central and central-parietal areas, as well as between negative cognitive processing bias and alpha asymmetry in the parietal region. Compared to responders, non-responders exhibited less negative cognitive processing bias and greater alpha asymmetry in both central and central-parietal regions. Importantly, we developed a multi-modality machine-learning model with 83 % specificity using the above salient features. CONCLUSIONS: Research results support the CNP theory of depression treatment. To some extent, the multimodal clinical model constructed based on the CNP theory effectively predicted the efficacy of this treatment in this population. LIMITATIONS: Small sample and only focus on the mechanisms of delayed-onset SSRI treatment.

Understanding guilt-related interpersonal dysfunction in obsessive-compulsive personality disorder through computational modeling of two social interaction tasks.

BACKGROUND: Obsessive-compulsive personality disorder (OCPD) is a high-prevalence personality disorder characterized by subtle but stable interpersonal dysfunction. There have been only limited studies addressing the behavioral patterns and cognitive features of OCPD in interpersonal contexts. The purpose of this study was to investigate how behaviors differ between OCPD individuals and healthy controls (HCs) in the context of guilt-related interpersonal responses. METHOD: A total of 113 participants were recruited, including 46 who were identified as having OCPD and 67 HCs. Guilt-related interpersonal responses were manipulated and measured with two social interactive tasks: the Guilt Aversion Task, to assess how anticipatory guilt motivates cooperation; and the Guilt Compensation Task, to assess how experienced guilt induces compensation behaviors. The guilt aversion model and Fehr-Schmidt inequity aversion model were adopted to analyze decision-making in the Guilt Aversion Task and the Guilt Compensation Task, respectively. RESULTS: Computational model-based results demonstrated that, compared with HCs, the OCPD group exhibited less guilt aversion when making cooperative decisions as well as less guilt-induced compensation after harming others. CONCLUSION: Our findings indicate that individuals with OCPD tend to be less affected by guilt than HCs. These impairments in guilt-related responses may prevent adjustments in behaviors toward compliance with social norms and thus result in interpersonal dysfunctions.

Decision-making biases in suicide attempters with major depressive disorder: A computational modeling study using the balloon analog risk task (BART).

BACKGROUND: In the last decade, suicidality has been increasingly theorized as a distinct phenomenon from major depressive disorder (MDD), with unique psychological and neural mechanisms, rather than being mostly a severe symptom of MDD. Although decision-making biases have been widely reported in suicide attempters with MDD, little is known regarding what components of these biases can be distinguished from depressiveness itself. METHODS: Ninety-three patients with current MDD (40 with suicide attempts [SA group] and 53 without suicide attempts [NS group]) and 65 healthy controls (HCs) completed psychometric assessments and the balloon analog risk task (BART). To analyze and compare decision-making components among the three groups, we applied a five-parameter Bayesian computational modeling. RESULTS: Psychological assessments showed that the SA group had greater suicidal ideation and psychological pain avoidance than the NS group. Computational modeling showed that both MDD groups had higher risk preference and lower ability to learn and adapt from within-task observations than HCs, without differences between the SA and NS patient groups. The SA group also had higher loss aversion than the NS and HC groups, which had similar loss aversion. CONCLUSIONS: Our BART and computational modeling findings suggest that psychological pain avoidance and loss aversion may be important suicide risk factor that are distinguishable from depression illness itself.

State-independent and -dependent behavioral and neuroelectrophysiological characteristics during dynamic decision-making in patients with current and remitted depression.

BACKGROUND: It is unclear whether the altered decision-making (DM) observed in patients with major depressive disorder (MDD) is neurophysiological and whether it improves with remission of depressive symptoms. The aim of this study was to identify developmental patterns of DM behavior, related cognitive characteristics, and electrophysiological abnormalities in patients with MDD across clinical stages. METHODS: A sample of 48 first-episode MDD patients (FD group), 41 remitted MDD patients (RD group), and 43 healthy controls (HCs) completed psychometric assessments and performed the balloon analogue risk task (BART) while event-related potentials (ERPs) were recorded. RESULTS: The RD group had lower depressiveness, self-blame, rumination, and catastrophizing tendencies, and higher mental resilience scores than the FD group, but retained significant differences from HCs. MDD patients showed a more conservative DM strategy than HCs, with no significant difference between the FD and RD groups. Compared to the FD group, the RD group had a smaller FRN for negative feedback and a trend toward a smaller P3 for positive feedback. Compared with HCs, the RD group had a smaller P3 during the positive feedback phase. FRN amplitude correlated positively with depression level and negatively with mental resilience. LIMITATIONS: Because a comparative cross-section design was employed, longitudinal studies are needed to make causal inferences. CONCLUSION: MDD patients presented a stable risk-avoidance bias in actively depressed and remission periods, consistent with a state-independent impairment pattern. Significantly reduced FRN amplitudes during remission indicated a state-dependent impairment pattern, and FRN amplitudes correlated with depression level. An abnormal feedback P3 component may be a state-independent characteristic that may become more pronounced with MDD progression.

Hypersensitivity to negative feedback during dynamic risky-decision making in major depressive disorder: An event-related potential study.

BACKGROUND: Patients with major depressive disorder (MDD) exhibit a diminished ability to think or concentrate, indecisiveness, and altered sensitivity to reward and punishment. These impairments can influence complex risk-related decision-making in dynamic environments. The neurophysiological mechanisms mediating MDD effects on decision-making behavior are not well understood. METHODS: Patients with MDD (N=50) and healthy controls (HC, N=40) were enrolled. They completed a series of psychometric tests. Event-related potentials (ERPs) were recorded during the performance of a well-validated modified version of Balloon Analogue Risk Task (BART). RESULTS: BART behavior data were similar across the two groups except the MDD patients showed more stability of risk aversion. Neurophysiologically, BART losses generated larger P3 amplitudes than wins, and MDD patients had larger feedback-related negativity (FRN) components than HCs in response to negative feedback (losses). Greater FRN amplitudes in response to losses correlated with higher levels of depressiveness, psychological pain, and anhedonia. A longer FRN latency in MDD patients was associated with more severe suicidal ideation. LIMITATIONS: The findings are based on cross-sectional data, which are not powerful enough to make causal inferences. CONCLUSION: MDD patients exhibit enhanced FRNs in the frontocentral region after receiving negative feedback in a risky decision-making task. FRN magnitude is associated with depressive symptom severity. Punishment hypersensitivity may contribute to the maintenance of depressive symptoms in MDD patients, and FRN may be a useful index of such hypersensitivity.