Necessity of molecular detail for meaningful whole-brain simulation

Ascertain whether incorporating molecular-level detail—such as protein identities, distributions, and other molecular annotations—is necessary for meaningful whole-brain simulation, and, if so, delineate the minimum molecular data and metrics required to enable accurate whole-brain models.

Background

In discussing model parameterization, the report contrasts neuroscience with machine learning, noting the absence of scaling laws or clear metrics that link data quantity and type to simulation accuracy.

The authors specifically flag uncertainty around how much molecular information must be represented in whole-brain models, raising the question of whether such detail is needed at all and, if it is, what minimum scope would suffice.