Marwan Abdellah

The paper uses simulations to study how synaptic plasticity interacts with network structure and dendritic organization to shape cortical microcircuit function and learning.

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 method to generate geometrically realistic and watertight neuronal manifolds from morphological data for in silico simulations.

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.

Ultraliser creates high-fidelity 3D models of neuroscientific structures for in silico simulations, enabling detailed structural analysis and scalable experiments.

The paper proposes a calcium-based plasticity model that predicts LTP and LTD dynamics across multiple pyramidal connections in the neocortex.

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 develops an in silico model of voltage-sensitive dye imaging to show that VSDI signals reflect inhibitory responses to ongoing excitatory dynamics in rodent neocortical circuits.

The paper objectively classifies neocortical pyramidal cells using algebraic topology, identifying seventeen types in the rat somatosensory cortex without expert input.

The paper presents a software workflow to create large-scale, realistic volumetric models of neocortical circuits for in silico optical studies.