Редактирование: Whole brain emulation (раздел)

=== Levels of Abstraction ===

The following table depicts the various levels of organization and scale at which the brain can be emulated -- Which increasing accuracy, increasing scanning difficulty, and increasing computational complexity. However, the amount of undestanding required is reduced the further we go: The first level of abstraction requires complete, high-level understanding of the ''mind''. Not the brain, but the abstract processes of cognition. The lowest level can be done with off-the-shelf software (If you have a couple thousand dollars to buy a copy of [[Software#Gaussian|Gaussian]]), but requires hardware beyond Greg Egan's imagination and scanning at the level of single atoms.

{| border="1" align="center" style="text-align:center;" class=wikitable
| '''Level''' || '''Kind''' || '''Description'''
|-
| 1 || Abstract model of the mind || align="left" | "Classic AI", high level representations of information and information processing. Built from the top down knowing the person's personality, ideas, etc., or using species-generic characteristics.
|-
| 2 || Brain region connectivity || align="left" | Each area represents a functional module, connected to others according to an abstract, species-generic connectome.
|-
| 3 || Analog network population model || align="left" | The population of neurons and their connectivity. Activity and states of neurons are represented as time-averages. This is similar to connectionist models using Artificial Neural Networs, rate-model neural simulations and cascade models.
|-  style="color:black; background-color:#ffffcc;" 
| 4 || Spiking neural network || align="left" | As above, plus firing properties, firing state and dynamical synaptic states. Integrate and fire models, reduce compartment models (But also some minicolumn models, eg<ref>Johansson C., Landser A. "Towards cortex sized artificial neural systems". ''Neural Networks'', 20: 48‐61, 2007.</ref>, and the Izhikevich model.
|-  style="color:black; background-color:#ffffcc;" 
| 5 || Electrophysiology || align="left" | As above, plus membrane sates (Ion channel types, properties, distribution, states), ion concenrtations, currents, voltages, modulation states. Multi-compartment model simulations only.
|-  style="color:black; background-color:#ffffcc;" 
| 6 || Metabolome || align="left" | As above, plus concentrations of metabolites and neurotransmitters in compartments.
|-
| 7 || Proteome || align="left" | As above, plus concentrations of proteins and gene expression levels.
|-
| 8 || States of protein complexes || align="left" | As above, plus protein quaternary structures.
|-
| 9 || Distribution of complexes || align="left" | As above, plus "locome" information and internal cellular geometry.
|-
| 10 || Molecular dynamics || align="left" | As above, plus molecular coordinates and molecular-level scanning.
|-
| 11 || Quantum chemistry || align="left" | Quantum interactions, orbitals. Requires a '''complete .pdb of the entire brain''', besides being completely computationally intractable.
|}