All genres
2025
Journal Article
8 (1), 65 (2025)
Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms. npj digital medicine 2024
Journal Article
354, pp. 473 - 482 (2024)
Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity. Journal of Affective Disorders 2023
Journal Article
158, 105450 (2023)
The human affectome. Neuroscience and Biobehavioral Reviews 2022
Journal Article
16, 809269 (2022)
The attention-emotion interaction in healthy female participants on oral contraceptives during 1-week escitalopram intake. Frontiers in Neuroscience
Journal Article
13, 819143 (2022)
How social experiences affect interpretation bias among individuals with non-clinical depression: The role of ostracism. Frontiers in Psychiatry 2021
Journal Article
11 (10), 957 (2021)
Machine learning-based behavioral diagnostic tools for depression: Advances, challenges, and future directions. Journal of Personalized Medicine
Journal Article
141, pp. 199 - 205 (2021)
Machine learning-based diagnosis support system for differentiating between clinical anxiety and depression disorders. Journal of Psychiatric Research 2020
Journal Article
10 (1), 16381 (2020)
Using machine learning-based analysis for behavioral differentiation between anxiety and depression. Scientific Reports
Journal Article
108, pp. 559 - 601 (2020)
Neural correlates of emotion-attention interactions: From perception, learning and memory to individual differences and training interventions. Neuroscience and Biobehavioral Reviews 2020
Book Chapter
Attention toward negative stimuli. In: Cognitive biases in health and psychiatric disorders, pp. 19 - 40 (Eds. Aue, T.; Okon-Singer, H.). Academic Press, London (2020)
2019
Book Chapter
The neurobiology of emotion-cognition interactions. In: Cognitive dimensions of major depressive disorder: Cognitive, emotional and social cognitive processes, pp. 171 - C14.P84 (Eds. Baune, B. T.; Harmer, C.). Oxford University Press (2019)