Romy Lorenz

This study uses fMRI meta-analyses to compare brain activity during memory encoding and retrieval in depression versus non-depressed individuals, finding stage- and content-specific differences.

This study shows that vascular draining affects laminar decoding in fMRI and that deconvolution can improve specificity but not fully resolve ambiguities.

This study investigates how spatial and feature attention interact in the frontoparietal cortex to selectively code task-relevant information during a visual discrimination task.

This paper replicates a laminar dissociation in human dlPFC during working memory tasks but finds no deep-layer activation during response execution, refining models of laminar organization.

This paper develops a deep learning model to automate scoring of the Rey-Osterrieth Complex Figure (ROCF) drawings, outperforming human raters and clinicians in accuracy and consistency.

This study examines layer-specific responses in the dlPFC during a working memory task using fMRI, finding differential activation patterns in superficial and deep layers across task phases.

TemplateFlow provides a FAIR framework for sharing and managing multi-scale, multi-species brain models to improve reproducibility in neuroimaging.

This paper uses Bayesian optimisation with fMRI to rapidly map residual brain network function in stroke patients, revealing patient-specific abnormalities linked to behavioural performance.

The paper investigates neural correlates of visual, rule, and motor conflict using fMRI, finding distinct but overlapping activation patterns in Multiple Demand Cortex (MDC) regions.

This paper investigates how task-switching predictability affects posterior default-mode network activation using fMRI, finding increased PCC/PrCC activity during predictable switches.

This study uses Bayesian optimization to assess how tACS phase differences affect phosphene perception and cognitive effects.

This paper uses neuroadaptive Bayesian optimization to identify cognitive tasks that dissociate ventral and dorsal frontoparietal networks, finding tasks different from those predicted by meta-analysis.

This paper improves brain age prediction by using Bayesian optimisation to select optimal MRI pre-processing parameters, achieving better accuracy than default settings.

This study investigates how LSD affects brain activity during music listening, finding increased cortical and subcortical activity linked to timbral complexity and enhanced emotional responses.