EBRAINS (Human Brain Project Infrastructure)

Upload patient MRI/DTI data to TVB on EBRAINS.

Construct a personalized virtual brain model.

Simulate seizure propagation patterns.

Virtually 'resect' brain areas to find the most effective surgical outcome.

Define network architecture using PyNN.

Map the SNN onto the SpiNNaker hardware via the EBRAINS portal.

Train the network using event-based datasets.

Benchmark energy consumption against standard NVIDIA H100 GPU clusters.

Deploy the MIP (Medical Informatics Platform) node at each hospital.

Define the analytical query (e.g., hippocampal volume correlation).

Execute federated analysis across all hospital nodes.

Aggregate results centrally without transferring raw image data.

Select a robotic arm model in the Neurorobotics Platform.

Interface it with a simulated motor cortex model.

Run closed-loop grasping simulations.

Optimize neural parameters based on kinematic performance.

Access molecular-level models of ion channels in EBRAINS.

Simulate drug binding affinity and its impact on neural firing.

Scale the simulation to a meso-scale circuit level.

Analyze emergent behavioral changes in the virtual model.

Query the Knowledge Graph for human connectivity datasets.

Extract structural connectivity matrices (connectomes).

Initialize weights in an artificial neural network based on biological sparsity.

Evaluate learning speed and generalization.

Load high-resolution BigBrain images from the EBRAINS data store.

Apply deep learning segmentation pipelines on HPC nodes.

Refine results using human-in-the-loop annotation tools.

Integrate the new layers into the Multilevel Atlas.