Background: Deficits in affective forecasting are closely associated with the development and maintenance of depression. While previous research has shown that emotional fluctuations and future thinking are prevalent in daily life, little is known about the psycho-physiological mechanisms of affective forecasting deficits in relation to specific daily events in depression. Methods: Dysphoric (N = 40) and non-dysphoric (N = 60) individuals completed assessments of their anticipatory emotions, experienced emotions, and consummatory emotions for specific daily events 3 times a day for consecutive 14 days. Heart rate variability (HRV) data was collected using customized smartwatches. Temporal network analysis was used to estimate time-lagged associations among anticipatory, experienced and consummatory emotions. Results: Dysphoric individuals reported significantly lower levels of anticipatory, experienced, and consummatory valence compared to non-dysphoric individuals. Furthermore, distinct patterns emerged in the temporal networks of anticipatory, experienced, and consummatory emotions between the dysphoric and non-dysphoric groups. Network density was considerably higher in dysphoric individuals than in non-dysphoric individuals. In addition, HRV was predictive of anticipatory valence across all participants. Moreover, the dynamic associations between anticipatory and experienced emotions predicted subsequent depression, even after accounting for baseline depressive symptoms. Conclusion: Our findings reveal provide novel insights into the psycho-physiological mechanisms of affective forecasting deficits in depression, with several clinical implications: (1) dysfunctional affective forecasting dynamics may serve as salient early warning signs and sensitive predictors of depression; and (2) improving the flexibility of affective forecasting may be a promising target for addressing depression.

Prospection bias (PB) plays a crucial role in the development and maintenance of depression. However, the symptom-level mechanisms linking specific depressive symptoms to distinct PB components remain unclear, limiting the precision of targeted interventions. This study employed a network analysis approach to elucidate the intricate symptom-level relationships between depression and PB in a large sample of 1162 university students (453 males and 709 females; mean age = 19.47 years, SD = 1.45). Participants completed self-report assessments of depressive symptoms and prospection bias. The network demonstrated high stability. Central symptoms within the depression–PB framework were identified as “suicidal ideation”, “blurry future imagery”, “lack of energy”, and “catastrophic negative future thinking”. Critically, “suicidal ideation”, “future imaginations of self-harm/suicide”, and “guilt” served as the pivotal bridge symptoms connecting depression and PB. The Network Comparison Test revealed no significant gender differences in network structure. These findings highlight that current suicidal ideation and future-oriented suicidal imagery may serve as key nodes in the network of depressive symptoms and prospection bias. The results may help inform early identification and targeted intervention among at-risk university students.