hjalli.com – Hjálmar Gíslason

Third in Wetware’s line of Grand Challenge reviews, we take a look at the ‘Architecture of Brain and Mind project‘ proposal.

This proposal, moderated by Mike Denham, Professor of Neural and Adaptive Systems at the University of Plymouth, draws from a number of similar original Grand Challenge submissions. The proposal is to create a computational architecture of the brain and mind on both neuronal and cognitive levels.

Or as stated in the proposal paper:

To create a computational architecture of the brain and mind which is inspired both by the neuronal architecture of the brain and high level cognitive functioning in humans; captures the information processing principles present in the brain; describes how low level neuronal processes are linked and integrated with high level cognitive capabilities, such as adaptability, self awareness and creativity; provides a major input into the worldwide scientific endeavour to control or eliminate a range of human mental disorders; and will allow the creation of intelligent artefacts which incorporate a significant subset of human cognitive functional capabilities.

A very ambitious plan indeed. The authors certainly know so, and reflect that in the proposal’s text:

However, whilst this Grand Challenge is guided by the long term scientific goal of understanding how the human brain functions in supporting the full range of human mental processes, it is not claimed here that this goal can be achieved in fifteen years [the suggested timespan for the Grand Challenge projects]: on the contrary a far longer time will be required. Nevertheless, within ten to fifteen years major progress is possible that will provide a solid foundation for further research in the decades that follow.

Over the last ten years however, we have seen a leap in the understanding of neural systems and the human brain. A great overview of these recent developments can be found in the September 2003 issue of Scientific American (some articles require subscription). These advances are largely due to new brain imaging technologies, such as fMRI that allow scientists to monitor brain activity in a conscious human being and research done on neuronal activity and connectivity in living neurons.

These recent developments have given people high hopes that we are on the verge of breaking the age old mystery of how the mind works. However, these developments have so far failed to explain most higher-level functionality of the mind / brain, even though an increasing majority of brain researchers and mind philosophers link it to some sort of emergent properties of relatively simple neuron interactions. My essay A Mind Emerges, discusses this idea in detail.

The ‘Architecture of Brain and Mind’ project aims to “abstract and formalise principles of operation rather than attempting to directly mimic the intricate chemical and physical mechanisms of biology.” This sounds reasonable, but the question is always how accurately do models have to represent reality to become sufficiently accurate to serve the purpose. Is it possible that you have to go all the way down to the mentioned level of mimicking in order to get the desired results? This was also part of my critic of the In Vivo In Silicio project.

This is of course no reason for not to go ahead with the project, but rather an obsevation to keep in mind.

In a similar way as the In Vivo In Silicio project, the research could lead to interesting developments in computer science:

…the need to create working models of the brain/mind architecture can be expected to lead to radically new brain-inspired hardware architectures;

…and I might add, new ideas in software architecture and development.

As the proposal cleverly notes:

The primary function of the nervous system is to gather, represent, interpret, use, store and transmit information; thus, neuroscience is inherently a computational discipline.

That said, studying the incredible computational machine (I’m deliberately avoiding the word computer) that the human brain is, is bound to advance our much more primitive computational methods, probably rather as an inspiration for ideas than a precise blueprint of the actual implementation.

Even though the project is very broad and has rather vaguely defined goals, it has some of the more intriguing points of any of the Grand Challenge proposals. My guess is that both the broadening and the wealth of interesting ideas are due to the fact that the ‘Architecture of Brain and Mind’ project proposal is melted together from several more specific project proposals.

Links:
DARPA’s Cognitive Systems project