Juan Luis Riquelme

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 describes a massively collaborative project using spiking neural networks to study sound localization, involving 31 researchers across multiple countries.

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.

This study shows recurrent neural networks develop and evolve repeating spike sequences through synaptic plasticity, with structured inputs enabling stable yet flexible encoding.

The paper shows single spikes can trigger repeatable firing sequences in cortical networks through strong and weak connections, enabling controlled propagation and routing of activity.