Toward the Human Nanoscale Connectome: Neuronal Morphology Format, Modeling, and Storage Requirement Estimation

Wiesław L. Nowiński

he human brain is an enormous scientific challenge. Knowledge of the complete map of neural connections (connectome) is essential for understanding how neural circuits encode information and the brain works in health and disease. Nanoscale connectomes are created for a few small animals but not for human. Moreover, existing models and data formats for neuron morphology description are “merely” at the microscale.

This work (1) formulates a complete set of morphologic parameters of the entire neuron at the nanoscale and introduces a new neuronal nanoscale data format; (2) proposes four geometric neuronal models: straight wireframe, enhanced wireframe, straight polygonal, and enhanced polygonal, based on the introduced neuronal format; and (3) estimates storage required for these neuronal models.

The straight wireframe model requires 18 petabytes (PB). The parabolic wireframe model needs 36 PB and the cubic model 54 PB. The straight polygonal model requires 24 PB. The parabolic polygonal model needs 48 PB and the cubic model 72 PB.

To my best knowledge, this is the first work providing for the human brain (1) the complete set of neuronal morphology parameters, (2) neuronal nanoscale data format, and (3) storage requirement estimation for volumetric and geometric neuronal morphology models at the micro and nanoscales. This work opens an avenue in human brain nanoscale modeling enabling the estimation of computing resources required for the calculation of the nanoscale connectome.