Johannes H. Friedrich

GIAnT is a toolbox for analyzing glutamate imaging data that corrects motion, identifies active synapses, and improves signal quality.

This study evaluates improvements in direct RNA sequencing (DRS) using RNA004 chemistry and modified-base-calling models, showing enhanced throughput, accuracy, and detection of RNA modifications in clinical applications.

ModiDeC is a deep-learning classifier that identifies multiple RNA modifications from direct nanopore sequencing, validated on synthetic data and biological samples.

VolPy provides an automated, scalable pipeline for analyzing voltage imaging datasets, demonstrating strong performance in neuron localization and spike extraction.

This paper introduces two online algorithms for real-time analysis of microendoscopic calcium imaging data, improving computational efficiency and enabling closed-loop experiments.

The paper introduces a new genetically encoded voltage indicator, Voltron, which improves brightness and photostability for extended in vivo voltage imaging in mice, zebrafish, and fruit flies.

CaImAn, an open-source library, automates motion correction, source extraction, deconvolution and cross-session registration for calcium imaging, detecting neurons near human level (F1 0.75 batch, 0.76 online).

The paper benchmarks spike rate inference algorithms for two-photon calcium imaging data and finds that top-performing algorithms show high correlation despite diverse approaches.

OnACID processes streaming calcium imaging data in real time by combining online dictionary learning with motion correction, source extraction, and activity deconvolution, tracking hundreds of neurons for closed-loop experiments.

The paper introduces multi-scale approaches to improve imaging and analysis of large neuronal populations by decimating spatial and temporal resolution to enable faster imaging or larger field of view with minimal accuracy loss.