Pramod Kumbhar

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

STEPS 4.0 improves scalability, performance, and memory efficiency for stochastic reaction-diffusion simulations of neurons.

The paper modernizes the NEURON simulator to improve sustainability, portability, and performance through new tools and optimizations.

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

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