0-Year-Kohorte

Forschungsinteressen: • theoretical neuroscience • machine learning • graph theory • random matrices

Forschungsinteressen: • heart-brain interactions • somatosensory perception • consciousness • decision-making • EEG and TMS applications

Research interests: • learning and decision making under uncertainty • development and application of computational cognitive models

Forschungsinteressen: • Janus-faced role of the endogenous cannabinoid system in fear, reward regulation and cognition • mouse models combined with molecular assays, pharmacological tools and sophisticated behavioral tests • consequences of selective alterations in endocannabinoid levels

Forschungsinteressen: • learning with deep neural networks • brain-inspired machine learning • cognitive computational neuroscience • visual perception

Forschungsinteressen: • brain network analysis • linear and non-linear interactions in • electrophysiological signals • Brain Computer Interface (BCI) • (blind) source separation • multilinear methods in machine learning

Forschungsinteressen: • investigating the resemblance between expert and machine driven biomedical image segmentation • structural and functional properties of the human visual system • high-resolution cytoarchitectonic brain mapping in big data sets • machine learning applications for biomedical image segmentation

Forschungsinteressen: • developmental psychobiology • childhood adversity • neural plasticity • plastic reorganization • sensitive periods of brain development

Forschungsinteressen: • mechanisms underlying neuronal and cognitive plasticity in the adult brain • combination of molecular and imaging techniques with behavioral data to understand the neural control of birdsong • neuronal circuits and gene networks involved in vocal learning and language acquisition

Forschungsinteressen: • combination of computer science, mathematics and statistics to interpret biological data • development, implementation and application of artificial intelligence and machine learning techniques • analysis of sequential data, specifically genetic and transcriptional data

Forschungsinteressen: • ambulatory assessment • bipolar disorders • eHealth/mHealth • digital phenotyping

Forschungsinteressen: • interplay of sleep and memory in the aging brain • mechanisms causing normal age-related and pathological memory decline • different neuroimaging methods like EEG, polysomnography (PSG), and MRI with behavioral memory paradigms

Forschungsinteressen: • spatial navigation and virtual reality in neuropsychology • neurorehabilitation • clinical and cognitive neuroscience

Forschungsinteressen: • surface-based neuroanatomical brain patterns in psychiatric disorders • personalized prognostic tools using machine learning • international validation of multivariate predictive models

Forschungsinteressen: • machine learning and cognitive neuroscience • utilizing deep learning methods to analyze neuroimaging data

Forschungsinteressen: • hormonal transition states and implications for brain structure, cognition, emotional well-being • depression susceptibility and resilience • sex hormones, menstrual cycle, premenstrual dysphoric disorder • multimodal neuroimaging (MRI, PET, EEG)