Reverse engineering the brain

A few months ago there was an article by T. Sejnowski in the Scientific American Mind Matters (here). The question was how long it will take to be able to build a brain resembling our own brains. He talked about the two front runners, who differ in their approach but have the same time estimate, about a decade for the first reverse-engineered brains.

The backdrop for the debate is one of dramatic progress. Neuroscientists are disassembling brains into their component parts, down to the last molecule, and trying to understand how they work from the bottom up. Researchers are racing to work out the wiring diagrams of big brains, starting with mice, cats and eventually humans, a new field called connectomics. New techniques are making it possible to record from many neurons simultaneously, and to selectively stimulate or silence specific neurons. There is an excitement in the air and a sense that we are beginning to understand how the brain works at the circuit level. Brain modelers have so far been limited to modeling small networks with only a few thousand neurons, but this is rapidly changing.

There is a dispute between Dharmendra Modha of IBM and Henry Markram of the Ecole Polytechnique Federale de Lausanne Blue Project. The two groups are the front runners but differ in philosophy.

Both groups are simulating a large number of model neurons and connections between them. Both models run much, much slower than real time. The neurons in Modha’s model only have a soma — the cell body containing the cell nucleus — and simplified spikes. In contrast, Markram’s model has detailed reconstructions of neurons, with complex systems of branching connections called dendrites and even a full range of gating and communication mechanisms such as ion channels. The synapses and connections between the neurons in Modha’s model are simplified compared to the detailed biophysical synapses in Markram’s model. These two models are at the extremes of simplicity and complex realism.

This controversy puts into perspective a tension between wanting to use simplified models of neurons, in order to run simulations faster, versus including the biological details of neurons in order to understand them. Looking at the same neuron, physicists and engineers tend to see the simplicity whereas biologists tend to see the complexity. The problem with simplified models is that they may be throwing away the baby with the bathwater. The problem with biophysical models is that the number of details is nearly infinite and much of it is unknown. How much brain function is lost by using simplified neurons and circuits?

I think it will take both types of simulation to understand consciousness and it will need simulation of the mid-brain as well as the cortex and the rest of the fore-brain. The hind-brain may even need to be included.


Addition – Reverse engineering rebuttal

It seems that at present there is a discussion about expecting reverse engineering of the brain in a decade. Ray Kurzweil who is a predictor of the future gave a speech at the Singularity Summit predicting that the brain would be reverse engineered in about 10 years. PZ Meyers in Pharyngula has attached Kurzweil’s logic. (here) Meyers is right in my opinion about the ignorance of biology on the part of Kurzweil – He seems to be in some other world and not worth listening to. However, Meyers himself shows his doubt about when reverse engineering will produce results. He feels 10 years is just wrong. Markram and Modha who are attempting it by different methods both hope to be somewhere significant in 10 years. They are not making foolish assumptions like Kurzweil. They are not starting with the genetic code etc. but with studies of architecture and the behavior of ion channels and the like. Meyers remarks do not touch their efforts as far as I can see.

 

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