Ramona Leenings
A5035949410- Functional Brain Connectivity Studies
- Mental Health Research Topics
- Health, Environment, Cognitive Aging
- Machine Learning in Healthcare
- Tryptophan and brain disorders
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Electroconvulsive Therapy Studies
- Treatment of Major Depression
- Medical Image Segmentation Techniques
- Cell Image Analysis Techniques
- Genetic Associations and Epidemiology
- Memory and Neural Mechanisms
- Child and Adolescent Psychosocial and Emotional Development
- Schizophrenia research and treatment
- Machine Learning and Data Classification
- Diet and metabolism studies
- Cardiovascular Disease and Adiposity
- Digital Mental Health Interventions
- Single-cell and spatial transcriptomics
- Computational Physics and Python Applications
- Child Abuse and Trauma
- Neuroscience and Neuropharmacology Research
- Machine Learning and Algorithms
- Cognitive Abilities and Testing
University of Münster
2018-2025
Jena University Hospital
2024-2025
University Hospital Münster
2017-2020
Abstract Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced aging in adult MDD patients, whether this process clinical characteristics a large multicenter international dataset. performed mega-analysis by pooling measures derived from T1-weighted MRI scans 19 samples worldwide. Healthy was estimated predicting chronological age (18–75 years) 7 subcortical volumes, 34 cortical thickness...
Identifying neurobiological differences between patients with major depressive disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for decades. However, recent meta-analyses have raised concerns regarding the replicability relevance brain alterations in depression.
Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one the most prevalent and disabling disorders, major depressive disorder (MDD), no informative biomarkers have been identified.
Abstract Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between and structure using structural MRI ( n = 6420) genetic data 3907) from ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical subcortical abnormalities in both mass-univariate multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found...
We currently observe a disconcerting phenomenon in machine learning studies psychiatry: While we would expect larger samples to yield better results due the availability of more data, consistently show much weaker performance than numerous small-scale studies. Here, systematically investigated this effect focusing on one most heavily studied questions field, namely classification patients suffering from major depressive disorder (MDD) and healthy control (HC) based neuroimaging data. Drawing...
Abstract Background Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced aging in MDD patients, whether this process clinical characteristics a large multi-center international dataset. Methods performed mega-analysis by pooling measures derived from T1-weighted MRI scans 29 samples worldwide. Normative was estimated predicting chronological age (10-75 years) 7 subcortical volumes, 34...
Abstract A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling test out-of-sample prediction individual scores possible on basis voxel-wise gray matter volume....
Abstract Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology the variability symptomatic overlap within between diagnostic classes. This heterogeneity impedes timely targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical genetic features may profit from similar therapies. We used high-dimensional data clustering on deep transdiagnostic groups in a discovery...
A network-based quantification of brain aging uncovers and fixes a fundamental problem all previous approaches.
Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders given treatment) when using clinical routine data such as demographic questionnaire data, while neuroimaging achieved superior accuracy. However, these may be considerably biased due very limited sample sizes bias-prone...
Importance: Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities MDD. To explore this, we used normative modeling to index regional patterns variability cortical thickness (CT) across patients. Objective: use a large dataset from the ENIGMA MDD consortium obtain individualised CT deviations norm (relative age, sex site) examine relationship...
Abstract Concerns about the generalizability of machine learning models in mental health arise, partly due to sampling effects and data disparities between research cohorts real-world populations. We aimed investigate whether a model trained solely on easily accessible low-cost clinical can predict depressive symptom severity unseen, independent datasets from various contexts. This observational multi-cohort study included 3021 participants (62.03% females, M Age = 36.27 years, range 15–81)...
Abstract Background Electroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of non-randomized prospective study focusing on over time. Methods Twenty-nine severely depressed patients receiving addition inpatient treatment, 69 with treatment (NON-ECT) and 52 healthy controls (HC) took part study....
PHOTONAI is a high-level Python API designed to simplify and accelerate machine learning model development. It functions as unifying framework allowing the user easily access combine algorithms from different toolboxes into custom algorithm sequences. especially support iterative development process automates repetitive training, hyperparameter optimization evaluation tasks. Importantly, workflow ensures unbiased performance estimates while still fully customize analysis. extends existing...
Abstract Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain’s large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging a powerful tool quantify controllability—i.e., of one brain region over others regarding If how controllability related mental health remains elusive. Here, from Diffusion Tensor Imaging data, we inferred structural connectivity calculated...
Several studies have evaluated whether depressed persons older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived "brain age gap" has varied from study to study, likely driven by differences in training and testing sample (size), range, used modality/features. To validate our previously developed ENIGMA brain model identified gap, we aim replicate presence effect size estimate found largest depression date (N = 2126 controls & N 2675 cases; +1.08...