Naked Science Forum
Life Sciences => Physiology & Medicine => Topic started by: lyner on 20/04/2007 23:11:34
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I know there is no real comparison between the way your brain stores information and the storage of information on a computer, but there must be a rough equivalent, in gigabytes - or terabytes, to the storage capacity of the human brain.
We must be using a far more efficient form of data compression than JPEGs or ZIP and, of course, there is a much more sophisticated data access system in our heads. (Having said that, I realise that my short-term memory is seriously on the wane and I often can't remember what I'm doing when I come into a room or even even how I intended to end a - now where was I?
Can anyone enlighten me? Someone must have done the sums.
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I doubt there are any sums for this, and I suspect that everyone's memory dramatically differs from other people's. I'm not sure if it is even sensible or possible to compare the storage capacity of a human brain with a computer's. I also don't think that we can measure our memory storage, using computer units, such as gigabytes and terabytes.
But, if there is an approximate answer, I would be delighted if anyone could tell me too. [;D]
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Firstly, the brain uses lossy compression (more like JPEGs or MP3 than ZIP), which is why you forget things.
The brain also has a high degree of redundancy (as, to some extent, do all systems within the human body), so allowing you to lose lots of neurons, and still maintain some degree of integrity in you memory.
The other problem is that the brain stores data in several levels (short term memory, long term memory; and probably separates out memory in other ways). Thus it would be very difficult to set a particular value on all of that, and the more so since the brain is constantly reconfiguring itself.
One question that one has to start by asking is whether you are talking about storage capacity, or actual amount of memory stored. I don't say that either calculation has ever been done, but one can suppose some calculation possible to judge the number of neurons one has, and the number of possible states in which those neurons can be configured, and thus judge if there was absolutely no redundancy, what is the maximum total theoretical storage capacity the of the brain. This clearly is not a realistic sum, since the brain is designed not for optimal efficiency, but for long term survival (at least for around 70 years), and so it must substantially compromise on the efficiency it could have if it was only looking for a 2 year survival time.
How much memory is stored in the brain is far more difficult to even know where to start calculating than what is the theoretical maximum capacity, since one really has no idea as to the full extent of what the brain actually stores (it may remember lots of things we are not even aware of it remembering; while we know that lots of things we believe we have remembered, we actually synthesise from partial recollections. How then do you even begin to quantify how much memory is actually stored?
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Not an easy question to answer, I know. But someone must have done some sort of estimate, if only for Artificial Intelligence research.
Clearly, there isn't a 'structural' equivalence between synapses and storage bytes. Also the power of adressability by content of our brains makes what we actually do remember much more useful than even the most sophisticated relational databases.
I must say, on this subject, I am really looking forward to the next step in Googling, where we search for ideas and meanings rather than keywords.
Problem is that there is less money in such a search engine. If you could specify , as you do with your brain, "Nothing to do with advertising in any form" amongst your search criteria then that would be the end of all sponsorship.
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I'm not sure that you can compare it at all, the brain is an analogue device and a computer hard drive digital. Both store and retrieve information differently.
Having said that, I sometimes think that when we dream it is the brains way of defragmenting similar to a hard drive defragmenting.
Bee
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I'm not sure that you can compare it at all, the brain is an analogue device and a computer hard drive digital. Both store and retrieve information differently.
While this distinction is true, it is not as real a distinction as you might think.
In both cases, the issue has to be the numberr of possible states a system can be in. In reality, although the brain is an analogue device, it does not have an infinite number of states.
As a comparison, look at a modem - a modem is an analogue device that encodes digital signals, but there is a limit to the number of states that a modem can transmit in a given timeframe because bandwidth limitations make it impossible to distinguish states that are too similar.
So too with the brain, if two analogue states are too similar as to be below the threshold where the brain can distinguish between them, then they must be considered the same state, and so provide an upper bound for the number of states that the brain can indeed distinguish.
Trying to measure how fine a granularity the human brain can distingush between separate states is another problem, and again.
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Shannon's basic information theory makes no real distinction between forms of information. And he is the daddy. It's all to do with signal to noise and bandwidth, however you like to dress it up.
So, come on, don't tell me how or why it can't be done. Give me an answer chaps.
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Maybe not an answer to your question, but moving in that direction:
http://news.bbc.co.uk/1/hi/technology/6600965.stm
US researchers have simulated half a virtual mouse brain on a supercomputer.
The scientists ran a "cortical simulator" that was as big and as complex as half of a mouse brain on the BlueGene L supercomputer.
In other smaller simulations the researchers say they have seen characteristics of thought patterns observed in real mouse brains.
Now the team is tuning the simulation to make it run faster and to make it more like a real mouse brain.
Life signs
Brain tissue presents a huge problem for simulation because of its complexity and the sheer number of potential interactions between the elements involved.
The three researchers, James Frye, Rajagopal Ananthanarayanan, and Dharmendra S Modha, laid out how they went about it in a very short research note entitled "Towards Real-Time, Mouse-Scale Cortical Simulations".
Half a real mouse brain is thought to have about eight million neurons each one of which can have up to 8,000 synapses, or connections, with other nerve fibres.
Modelling such a system, the trio wrote, puts "tremendous constraints on computation, communication and memory capacity of any computing platform".
The team, from the IBM Almaden Research Lab and the University of Nevada, ran the simulation on a BlueGene L supercomputer that had 4,096 processors, each one of which used 256MB of memory.
Using this machine the researchers created half a virtual mouse brain that had 8,000 neurons that had up to 6,300 synapses.
The vast complexity of the simulation meant that it was only run for ten seconds at a speed ten times slower than real life - the equivalent of one second in a real mouse brain.
On other smaller simulations the researchers said they had seen "biologically consistent dynamical properties" emerge as nerve impulses flowed through the virtual cortex.
In these other tests the team saw the groups of neurons form spontaneously into groups. They also saw nerves in the simulated synapses firing in a ways similar to the staggered, co-ordinated patterns seen in nature.
The researchers say that although the simulation shared some similarities with a mouse's mental make-up in terms of nerves and connections it lacked the structures seen in real mice brains.
Imposing such structures and getting the simulation to do useful work might be a much more difficult task than simply setting up the plumbing.
For future tests the team aims to speed up the simulation, make it more neurobiologically faithful, add structures seen in real mouse brains and make the responses of neurons and synapses more detailed.
There is no mention about the bit level capacity of the machine on which the simulation was running (and it is only half a mouse - how much more for the whole of a human brain?).