2026-04-20 10:52 |
[FZJ-2026-02256]
Dissertation / PhD Thesis
Hoheisel, L.
Computational Modelling of Brain Network Dynamics in Psychotic and Affective Disorders
143 pp. (2025)2025 = Dissertation, Universität zu Köln, 2025
his dissertation explores the role of dynamic functional connectivity (dFC) as an intermediate phenotype linking neurobiological characteristics and clinical outcomes in psychotic and affective disorders. The thesis aims to reveal alterations in dFC in psychotic and affective patients, study the impact of neurobiology on static and dynamic FC patterns, and identify neurobiological processes which might contribute to static and dynamic FC changes in psychotic and affective disorder. [...]
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2026-04-20 10:48 |
[FZJ-2026-02255]
Dissertation / PhD Thesis
Sauter, A.
Neural Underpinnings of Adaptive Control in Fronto-Subthalamic Networks. Dissertation
183 pp. (2025)2025 = Dissertation, Universität zu Köln, 2025
In an environment as complex and unpredictable as our human society, we cannot merely rely on hard-wired reflexes and short-term incentives for successful behavior. Instead, our brain uses cognitive control to derive expectations from current and prior information and adapts strategically to changing demands. [...]
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2026-04-20 10:39 |
[FZJ-2026-02254]
Dissertation / PhD Thesis
Friedrich, M.
Strukturelle und funktionelle Konnektivität in Tumorpatienten
136 pp. (2025)2025 = Dissertation, Universität zu Köln, 2025
The functional organization of the human brain is based on neuronal connections (edges) between cortical regions (nodes), known as structural connectivity. This may become disrupted by tumor growth or multimodal treatments, leading to cognitive impairment. [...]
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2026-04-20 10:32 |
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2026-04-18 13:01 |
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2026-04-17 11:36 |
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2026-04-17 11:22 |
[FZJ-2026-02245]
Preprint
Ji, Y. ; Chen, Z.-Y. ; Roth, M. ; et al
Quantum Deep Learning: A Comprehensive Review
Quantum deep learning (QDL) explores the use of both quantum and quantum-inspired resources to determine when deep learning's core capabilities, such as expressivity, generalization, and scalability, can be enhanced based on specific resource constraints. Distinct from broader quantum machine learning, QDL emphasizes compositional depth at the pipeline level and the integration of quantum or quantum-inspired components within end-to-end workflows. [...]
OpenAccess: PDF;
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2026-04-17 11:18 |
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2026-04-17 11:14 |
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2026-04-17 10:47 |
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