27 Jan 2009

Nick Bostrom & Anders Sandberg: Whole Brain Emulation (WBE) (Mental Uploading / Mental Downloading) Part I, Section 2, Little Need for...

by Corry Shores
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[My more developed Deleuzean critique of mental uploading can be found here. The following summarizes Nick Bostrom's & Anders Sandberg's new study on whole brain emulation. My commentary is in brackets.]

Nick Bostrom & Anders Sandberg,
"Whole Brain Emulation: A Roadmap"

Part I: The Concept of Brain Emulation

Section II: "Little Need for Whole System Understanding"

One approach to replicating the brain would be to learn everything possible about its parts and their interactions. However, this information
1) might not also tell us about how the brain produces consciousness or intelligence, and
2) is not all necessary for the task of emulating the functional operation of the brain. For, we might exactly replicate the behavior of the brain without using precisely the same inner workings.

in order to emulate the brain we do not need to understand the whole system, but rather we just need a database containing all necessary low‐level information about the brain and knowledge of the local update rules that change brain states from moment to moment. (8)
Even a simpler database containing just the "parts list" for the brain would prove highly useful for other studies of the brain.

Bostrom & Sandberg explain that
Computational neuroscience attempts to understand the brain by making mathematical or software models of neural systems.
For the most part, the models are not yet sophisticated enough to be as complex as the neural systems they replicate.

In most cases, models look at both the brain's local and global structures and relations. Connectionist models in particular
build more complex models of cognition or brain function on these simpler parts. The end point of this pursuit would be models that encompass a full understanding of the function of all brain systems. (9)

This "qualitative" approach offers a formalized account of the way that human behavior results from the functioning of the simple parts, but they might not succeed in exhibiting the intelligence or complexity of human behavior.

The "quantitative" approach would instead examine the biological details of neuronal composition, structure, behavior, and interaction. The aim would be to provide a complete list of the brain's biological parts and to accurately model their interaction.

Given this information increasingly large and complex simulations of neural systems can be created. WBE represents the logical conclusion of this kind of quantitative model: a 1‐to‐1 model of brain function. (9)
[Here then is something incredibly interesting and important about Bostrom's & Sandberg's approach: it is based on emergentist principles. According to this theory, such higher-level properties as consciousness "emerge" from the lower level properties of the neuronal activity. This is why Bostrom & Sandberg do not think we need to obtain "whole system understanding." For, so long as we replicate the lower-level properties of brain functioning, we can expect such higher ones as consciousness to emerge. Thus if we can replicate these neuronal properties accurately enough in computer software, Bostrom & Sandberg would conclude that thereby we have created consciousness. A mind will "emerge" from the computer's operations just as it emerges from the totality of all our brain's neuronal activity.]

As Bostrom & Sandberg write:
Note that the amount of functional understanding needed to achieve a 1‐to‐1 model is small. Its behaviour is emergent from the low‐level properties, and may or may not be understood by the experimenters. (my emphasis, 9)

Computational neuroscience often uses hybrid models that are dually quantitative and qualitative in nature, because both approaches have their advantages and disadvantages.

There are interacting factors that determine the sort of model used to create a neural emulation.
1) the need to make the model faithful to the biological properties of the original neural system: what Bostrom & Sandberg call "biological realism."
2) the extent to which conditions allow-for either quantitative or qualitative simulations: "tractability."
3) the manner by which the experimenter mentally represents the main components of the system: "understanding."
If the mind will emerge from the workings of the lower-level parts, brain emulation scientists then do not need a highly sophisticated mental representation of how the emergence happens. They only need to know the conditions which bring that about. But then they also need a firm grasp on the dynamics of the lower-level processes. This then requires a high degree of biological realism, so that they can be accurately replicated.

Yet, what we want to obtain are such higher-level phenomena as consciousness and intelligence. So we have to have some sense of the dynamics of higher-level functioning to test the emulations and to determine the data that will confirm their success. Nonetheless, the focus will still remain almost exclusively the lower-level activities, which are the most essential for creating the conditions that allow for minds to emerge. (9-10)

Sandberg, A. & Bostrom, N. (2008): Whole Brain Emulation: A Roadmap, Technical Report #2008‐3, Future of Humanity Institute, Oxford University.
Available online at:

Nick Bostrom's page, with other publications:

Anders Sandberg's page, also with other publications:

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