Experimental protocol.

A) Study outline. This study aims to answer how depression and anxiety influence mood fluctuations. The first experiment assesses the bifactor structure that disentangling depression and anxiety in the psychometric dataset (N = 901). The second experiment with this battery of questionnaires and the gambling-induced mood fluctuations task tests correlational associations of depression and anxiety with RPE-induced mood fluctuations (the laboratory dataset, N = 44). The third and fourth experiments replicates the 2nd experiment in the online context (the online dataset 1, N = 747; the online dataset 2, N = 235). The fifth experiment with the mood fluctuations task tests the potential treatment of mood stabilizer on RPE-induced mood fluctuations in the clinical dataset (N = 61). B) Mapping between three factors and 128 items in the bifactor model. C) Factor loadings of items on the common factor, the anxiety-specific factor, and the depression-specific factor. D) Orthogonal nature between the common factor and the anxiety-specific factor and between the common factor and the depression-specific factor in a total of 1950 participants for each dataset. E) Mean correlations of factor scores with questionnaire scores. Overall, the common factor showed high correlations with all questionnaires. The depression-specific factor was mainly contributed by the TAIdep and the MASQad, while the anxiety-specific factor was mainly contributed by the remained questionnaires. These correlational results confirmed the bifactor structure underlying anxiety and depression. F) Gambling task design. On each trial, participants were asked to choose between a certain option and a gambling option. Once selected, the corresponding outcome was resolved in the center of the screen. The cumulative score was always shown in the right-upper corner. Every 2 or 3 trials, participants were asked to complete a self-pace rating of “How happy are you at the moment” on a slider from 0 (very unhappy) to 100 (very happy). G) Time dynamics of happiness ratings for the individual with mood variation in the top 25% (the first panel), the individual with mood variation in the top 75% (the second panel), healthy datasets, and the clinical dataset. H) Momentary mood model. I) Results of momentary mood model for each dataset. Abbreviations: MASQaa, the subscale of anxious arousal in the Mood and Anxiety Symptoms Questionnaire; TAIanx, the subscale of anxiety in the Trait Anxiety Inventory; CESD, Center for Epidemiologic Studies Depression Scale; BDI, Beck Depression Inventory; BFIn, the subscale of neuroticism in the Big Five Inventory; PSWQ, Penn State Worry Questionnaire; MASQad, the subscale of anhedonic depression in the Mood and Anxiety Symptoms Questionnaire; TAIdep, the subscale of depression in the Trait Anxiety Inventory; CR, certain reward; EV, expected value; RPE, reward prediction error.

Basic demographic details.

Results for depression vs. anxiety on mood fluctuations.

Correlations of depression and anxiety factor score with mood variation and mood parameter of RPE (βRPE) for the laboratory dataset (AE), the online dataset 1 (BF), the online dataset 2 (CG), and the combined dataset (N =1026; DH). I) The lower RPE-weighted mood parameter mediated the effects of depression on decreased mood fluctuations. J) The higher RPE-weighted mood parameter mediated the effects of anxiety on increased mood fluctuations. K) Depression-specific factor was specifically relevant to decreased mood sensitivity to RPE among mood parameters. L) Anxiety-specific factor was specifically relevant to increased mood sensitivity to RPE among mood parameters. The regression coefficients were represented by mean ± se, which were estimated by bootstrap. Abbreviations: CR, certain reward; EV, expected value; RPE, reward prediction error; *p<0.05.

Clinical validation for deficit RPE-based mood fluctuations with depression.

AB) Correlations of depression and anxiety factor score with mood variation and mood parameter of RPE (βRPE) for the clinical dataset. C) The mediation model among depression, βRPE, and mood variation in the clinical population. The regression coefficients were represented by mean ± se, which were estimated by bootstrap. Abbreviations: RPE, reward prediction error; *p<0.05.

Exploratory analysis for the g factor.

Consistent results for the common factor across the healthy and clinical dataset.

Negative associations of the common factor with the baseline mood parameter A) and risk attitude for gain B). The regression coefficients were represented by mean ± se. *p<0.05.