Manuel S. Schröter

A perturbation atlas of mouse neural organoids resolves macroglial reactivity and nominates drivers of degeneration

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

In vitro programming and pseudounipolarization of human iPSC-derived sensory neurons

This study demonstrates the generation of functional human sensory neurons from iPSCs using NBI factors, showing their electrophysiological properties and disease relevance.

Functional Cell-Type Identification in Neuronal Networks Using High-Density Microelectrode Arrays

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.

Homophilic wiring principles underpin neuronal network topology in vitro

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

Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing

This study uses retrograde tracing to characterize neuron-tumor networks in glioblastoma and shows that targeting these networks can enhance therapeutic outcomes.

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains

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.

Scalable covariance-based connectivity inference for synchronous neuronal networks

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.

Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking

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.

Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics electrophysiological phenotype of the A53T mutation

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.

Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays

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

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level

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.