Rupert R. Lanzenberger

Cellular and mitochondrial correlates of regional glucose metabolism in the human cortex

The paper investigates the cellular and mitochondrial factors influencing regional glucose metabolism in the human cortex using multimodal data integration.

Subacute effects of ketamine on neural correlates of reward processing

This study examines ketamine's subacute effects on reward processing using fMRI and finds no significant modulation of neural activation during the MID task five hours post-infusion.

Open-access template and database approaches for pseudo-CT generation in brain PET/MRI attenuation correction

The paper presents an open-access framework for PET attenuation correction using pseudo-CT methods with a database of MRI-CT scans, showing that UCL achieves the lowest quantification error.

Network-specific metabolic cost of functional connectivity in the human brain

The paper examines network-specific metabolic costs of functional connectivity in the human brain using PET/MR data, revealing differences in metabolic demand across brain networks and changes in Alzheimer's disease.

Reconfiguration of default mode metabolic demands and network organization during acute stress

This study examines how acute psychosocial stress reconfigures brain metabolism and network organization using PET/MRI, revealing changes in the default mode network and its interactions with other networks.

Test-Retest Reliability of Dopaminergic fPET and fMRI Measures During Reward Processing

This study evaluates the test-retest reliability of fPET and fMRI during reward processing, finding comparable reliability but differing in target areas and dynamic assessment capabilities.

High-temporal resolution metabolic connectivity resolved by component-based noise correction

This paper develops a noise correction method for high-temporal resolution fPET data, showing it improves metabolic connectivity estimation across different scanners and frequency bands.

A Comparative Evaluation of Molecular Connectivity and Covariance Approaches

This paper compares molecular connectivity (MC) and covariance (mCov) methods using fPET data to assess metabolic associations between brain regions, finding that different methods perform better at varying temporal resolutions.

Hedonic experiences emerge from an orchestrated balance of synergistic and redundant information processing

The paper investigates how ketamine affects hedonic experiences by analyzing neural dynamics during music-evoked peak experiences using fMRI and information-theoretical measures.

A Unified Approach for Identifying PET-based Neuronal Activation and Molecular Connectivity with the functional PET toolbox

The paper introduces a unified fPET toolbox for analyzing neuronal activation and molecular connectivity, validated across cognitive tasks and radiotracers.

Evaluation of Data-based Motion Correction Techniques for High Temporal Resolution Functional PET

This study evaluates motion correction techniques for high temporal resolution fPET and finds that neither deep learning nor sliding window averaging significantly improves motion artifact mitigation compared to standard methods.

Optimal filtering strategies for task-specific functional PET imaging

This study evaluates filtering techniques for fPET data, finding that dNLM and MRI-MRF filters improve signal-to-noise ratio and test-retest reliability, with dNLM reducing sample size needs.

On the analysis of functional PET (fPET)-FDG: baseline mischaracterization can introduce artifactual metabolic (de)activations

This study shows that incorrect baseline modeling in fPET-FDG can create false metabolic activity patterns, affecting GLM analyses.

Connecting the Dots: Approaching a Standardized Nomenclature for Molecular Connectivity Combining Data and Literature

The paper introduces a standardized nomenclature for PET-based molecular connectivity and covariance to improve reproducibility and interpretation across imaging modalities and radiotracers.

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET

This paper introduces a method to assess cerebral glucose metabolism changes during tasks without blood sampling, using GLM beta values and percent signal change, showing strong correlation with standard CMRGlu measurements.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

This study uses high-temporal resolution PET/MRI to show synchronized metabolic and hemodynamic brain responses during working memory tasks.

Active Suppression of the Nigrostriatal Pathway during Optogenetic Stimulation Revealed by Simultaneous fPET/fMRI

This study uses simultaneous fPET/fMRI to show that optogenetic stimulation suppresses nigrostriatal pathway activity through presynaptic autoinhibition, revealing a dissociation between BOLD signal depression and neuronal inactivity.

Metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

The paper investigates how metabolic demands of the posteromedial default mode network (DMN) are influenced by task-positive networks during attention-demanding tasks.

Regional gene expression patterns are associated with task-specific brain activationduring reward and emotion processing measured with functional MRI

The paper correlates gene expression patterns with fMRI activation maps during reward and emotion tasks, identifying gene regulators linked to depression risk.

Learning induces coordinated neuronal plasticity of metabolic demands and functional brain networks

This study investigates how learning affects brain network interactions and metabolic demands, finding that resting-state and task-specific changes in functional connectivity and glucose metabolism are complementary for skill acquisition.

Correlation of receptor density and mRNA expression patterns in the human cerebral cortex

The paper examines the correlation between mRNA expression and receptor density in the human cerebral cortex using autoradiography and transcriptomic data from multiple sources.

Escitalopram Administration, Neuroplastic Effects and Relearning: A Diffusion Tensor Imaging Study in Healthy Individuals

This study investigates escitalopram's effect on white matter plasticity during learning and relearning using diffusion tensor imaging in healthy individuals, finding no significant changes in DTI metrics.

A causal role for estradiol in human reinforcement learning

This study shows estradiol increases reward sensitivity in men, with effects moderated by baseline dopamine levels.

Functional dynamics of dopamine synthesis during monetary reward and punishment processing

The paper introduces a novel fPET approach to assess dopamine synthesis during reward and punishment processing, revealing sex-specific differences in dopamine response to monetary gains and losses.

Effects of Escitalopram and Relearning on Cortical and Subcortical Grey Matter in Healthy Humans

This study examines the effects of escitalopram and relearning on grey matter in healthy humans but finds no significant effect of the SSRI on structural neuroplasticity during relearning.

Effects of learning and escitalopram administration on serum BDNF levels, a randomised placebo-controlled trial

This study examines how associative learning and escitalopram affect serum BDNF levels in healthy humans, finding significant time effects during learning and a negative correlation between citalopram and sBDNF levels.

Serotonin modulates learning content-specific neuroplasticity of functional brain networks

This study shows that escitalopram modulates functional brain network connectivity during relearning, with content-specific effects on neuroplasticity.

No metabolic "default mode" of human brain function

This study shows that fMRI deactivations in the default mode network (DMN) during cognitive control do not reflect reduced synaptic metabolism, revealing functional heterogeneity in the DMN.

Differential brain atrophy and neurogenetic profiles in cognitively-defined Alzheimer's disease subgroups

The paper identifies cognitive subgroups in Alzheimer's disease based on MRI-derived atrophy patterns and links them to specific biological pathways using transcriptomic data.