Michael Gevaert

The paper creates a detailed computational model of rat somatosensory cortex anatomy, including 4.2 million neurons and 14.2 billion synapses, and identifies limitations in connectivity prediction from morphology.

The paper presents a large-scale biophysically detailed model of somatosensory cortex to simulate and validate cortical dynamics and experimental results.

The paper presents a full-scale in silico model of rat hippocampal CA1 integrating diverse experimental data and validates it through simulations of theta rhythm and other experiments.

The paper develops a computational model of mouse thalamoreticular microcircuitry to study sensory enhancement and sleep spindle properties, revealing mechanisms of network-level activity across brain states.

The paper digitally reconstructs the neuro-glia-vascular system in rat somatosensory cortex to understand astrocyte-vascular-neuron interactions and their anatomical constraints.

The paper introduces the SONATA data format to efficiently describe large-scale network models in neuroscience, enabling model construction, simulation, and sharing.

The paper introduces Neuron_Reduce, an analytical method that significantly speeds up nonlinear neuron simulations while preserving key dynamics and dendritic computations.

The paper builds a statistical model of the mouse whole-neocortex micro-connectome using region-to-region connectivity and axon reconstructions, revealing a novel targeting principle for predicting individual axon innervation.