Is it necessary to simulate the quantum chemistry of a biological neural network in order to functionally approximate a BNN with an ANN?

A biological systems and fields model for cognition:

Spreading activation in a dynamic graph with cycles and magnitudes ("activation potentials",) that change as neurally-regulated heart-generated electron potentials (and,) reverberate fluidically with intersecting paths. And a partially extra-cerebral induced field which nonlinearly affects the original signal source through local feedback; Representational shift.

Representational shift: "Neurons Are Fickle. Electric Fields Are More Reliable for Information" (2022) https://neurosciencenews.com/electric-field-neuroscience-201...

Spreading activation: https://en.wikipedia.org/wiki/Spreading_activation

Re: 11D (11-Dimensional) biological network hyperparameters, ripples in (hippocampal, prefrontal,) association networks: https://news.ycombinator.com/item?id=18218504

M-theory String theory is also 11D, but IIUC they're not the same dimensions

Diffusion suggests fluids, which in physics and chaos theory suggests Bernoulli's fluid models (and other non-differentiable compact descriptions like Navier-Stokes), which are part of SQG Superfluid Quantum Gravity postulates.

Can e.g. ONNX or RDF with or without bnodes represent a complete connectome image/map?

Connectome: https://en.wikipedia.org/wiki/Connectome