Andreas R. Hierlemann

This study creates a perturbation atlas of mouse neural organoids to understand macroglial reactivity and identify drivers of degeneration.

This paper introduces RMO/RCASE, a method for rapidly estimating receptive fields in visual neurons across stages of the early visual system using structured stimuli, showing improved performance over conventional methods in mice but comparable results in primates.

The paper introduces a microfluidic system for long-term high-resolution imaging of organotypic brain slices to study neural responses to glutamate.

The paper develops a classifier to identify excitatory and inhibitory neurons using HD-MEA recordings without post-hoc labeling, revealing cell-type-specific network dynamics.

This study uses human colonic organoids to reveal how Enterococcus faecalis adapts to intestinal mucus, identifying key fitness determinants and colonization strategies not observed in vitro or in vivo.

The paper develops genetically-encoded biosensors to monitor antibiotic concentrations inside bacterial cells and tissues in real-time, revealing antibiotic exposure dynamics and penetration in infection models.

This study shows that structured firing sequences emerge in human and murine brain organoids and neonatal brain slices, suggesting innate rather than experience-dependent neural coding.

This paper develops a 3D human urothelial model to study UTI dynamics and therapeutic responses in real-time.

The paper shows that axonal propagation speeds in the human retina adjust to compensate for differences in axon length, ensuring synchronized action potential arrival times at the optic disc.

This study identifies homophilic wiring as a principle governing neuronal network topology in vitro, outperforming traditional models in explaining connectivity patterns.

PHIROS enables long-term, high-resolution imaging of organotypic brain slices with controlled perfusion, revealing dynamic tumor-astrocyte interactions and mitochondrial transfer.

RT-Sort detects and sorts action potentials in real time with millisecond latencies using propagation patterns and a convolutional neural network.

CardioMEA is a data-analysis platform for HD-MEA data from iPSC-CMs, enabling electrophysiological analysis of cardiac diseases and drug responses.

This paper introduces an ensemble artificial neural network (eANN) to improve neuronal connectivity inference from spike trains, showing it outperforms existing methods across different dynamical regimes.

This paper introduces a novel GR degrader, KH-103, which selectively degrades glucocorticoid receptors and shows improved efficacy over existing inhibitors.

This paper introduces FDDC, a method for inferring connectivity in neuronal networks, showing it outperforms existing methods and reveals a negative correlation between small-worldness and network synchrony.

The paper presents a method for fabricating 3D microelectrode arrays to interface with neural structures, demonstrating high-resolution recording from retinal ganglion cells.

The paper develops an experimental platform to analyze excitatory and inhibitory synaptic inputs in neurons and finds that spiking coincides with rapid changes in the E/I ratio.

This paper introduces a multi-modal fitting framework combining patch-clamp and HD-MEA data to build more accurate multicompartment neuron models.

The paper introduces a method to identify monosynaptic connections using dendritic spine Ca2+ imaging and extracellular spiking recordings, validated with simulations.

This study uses high-density electrode arrays to analyze neural activity in human brain organoids, revealing functional connectivity patterns and responses to benzodiazepine treatment.

The paper introduces DeePhys, a tool for functional phenotyping of neurons using electrophysiological data, and shows it can predict genotype and age in iPSC-derived DA neurons with the A53T SNCA mutation.

This paper introduces an automated method to reconstruct axons and estimate action-potential propagation velocities from high-density microelectrode array recordings.

The paper develops a human iPSC-derived neural model to study TDP-43 pathology, identifying NPTX2 misregulation as a key factor in ALS/FTLD neurotoxicity.

speedingCARs uses domain shuffling and single-cell sequencing to engineer CAR T cells, identifying effective variants with diverse transcriptional signatures and T cell phenotypes.

This study uses HD-MEAs to characterize electrophysiological phenotypes of iPSC-derived neurons and assess drug effects in Parkinson's and ALS models.

The paper introduces a platform for label-free electrophysiological live-cell imaging of neuronal networks, demonstrating its capabilities with long-term recordings and analysis tools.

This study compares cell-type development and transcriptomes in human retinal organoids and adult retinas, finding convergence in transcriptomes and cell-type-specific disease gene expression.

The paper introduces CHIME, a scalable neuronal recording system using microwires and CMOS arrays to overcome limitations in capturing neural activity in mammalian brains.

The paper introduces a neural recording system combining microwire arrays with CMOS chips to enable high-density, three-dimensional neural interfaces.