Stefan Rotter

This study uses a homeostatic structural plasticity model to explain varying effects of tDCS on motor learning based on timing, polarity, and targeting.

This paper develops a spiking neural network model to study how cortico-thalamic feedback affects V1 neuron activity, finding it enhances orientation selectivity and signal-to-noise ratio, particularly at low contrasts.

This paper uses computational modeling to show that rTMS induces dose-dependent homeostatic structural plasticity in neuronal networks, influenced by stimulation parameters and inhibition.

The paper models how neurons in the primary visual cortex integrate retinal inputs to produce feature-specific responses through a two-step process involving random projections and spike threshold rectification.

A survey of the German neuroscience community identifies key barriers to reproducible research and outlines strategies for improving research data management.

This paper shows that homeostatic plasticity alone can form stable memory engrams in recurrent neural networks through structural remodeling and distributed storage.

NEST Desktop provides an installation-free web-based GUI for neuronal network simulations, enabling non-programmers to explore computational neuroscience concepts without prior programming knowledge.

The paper studies the time course of homeostatic structural plasticity in mouse anterior cingulate cortex following optogenetic stimulation, showing dynamic changes in neural activity and morphology.

This study investigates how correlations in basal ganglia output affect thalamic rebound spikes and motor signal transmission using a Hodgkin-Huxley model.

The paper models layered mouse visual cortex connectivity to show how it explains orientation selectivity and introduces a method for optogenetic stimulation design.

This paper models how tDCS induces network remodeling through synaptic plasticity, showing that focal and repetitive stimulation enhances cell assembly formation.