May 08 2007
A reader sent me the following questions:
“On your recent blog entry about the virtual simulation of the mouse brain, you said that the human brain is analog, not digital. I thought that the firing of a neuron was a digital process- it either fires or it doesn’t. I was under the impression that the strength of a signal is irrelevant once an action potential is generated. Is this not true? Does the intensity of a signal affect future syntactic connections?
“As a system, the human brain is definitely analog, as it produces different firing patterns (outputs) when the same stimuli (inputs) are presented to it. I’m just wondering whether the more basic level of neurons would be considered analog or digital.”
- Jordan Horowitz
This is an interesting question and provides an opportunity to explore some of the basics of the anatomy of neuronal connections. It is true that the firing of a neuron (conducting a signal from the cell body down its axon and ultimately synapse on another neuron or end organ) is all or none – a neuron cannot fire a little or a lot, it just fires. This would seem to make neuronal function digital, since it is a binary on/off phenomenon. However, there are three important reasons why this is ultimately not the case.
First let me also back up a bit and explain the difference between digital and analog, even though this is probably well known to most readers. An analog system is one that encodes information as a continuum. There is no inherent limit to values that can be assigned at any point. For example, if you consider a ruler without that is just a blank strip of wood one foot long, without any markings. You can line the ruler up along some thing you are measuring and then mark the length on the ruler. This would be an analog measure, because you can make the mark anywhere along the continuum.
A digital system is one in which information has discrete values. So a digital ruler would be one where you have to indicate the measured distance as 8 3/16 inches, and there is no way of indicating a measurement between 8 3/16 and 8 4/16. The advantage of digital systems is that they have greater fidelity, because information is locked into discrete values. Digital information is also more compatible with computer technology, that records discrete values and is ultimately based on a binary system of coding.
Another illustrative example of analog vs digital is in camera technology. Film is analog – light can have any intensity or color anywhere on the film. Digital photography involves specifying one of a limited number of colors at a specific pixel (yes, I know modern digital camera CCDs have much more complexity than this, but you get the idea).
Digital technology can mimic analog technology if the resolution is high enough. For example, if a digital picture has high enough resolution you cannot see the pixels. If a digital sound recording has a high enough bit rate then you cannot hear the difference it and a good analog recording. This topic also is applicable to artificial intelligence, as I have touched upon before. Our brains are ultimately analog, and duplicating their function with a digital computer is possible but will require greater digital processing power.
Now back to neurons. A net neurological effect is usually not the result of a neuron firing once, but rather a series of firings. A neuron can increase or decrease how much it is firing by changing the frequency of its repeated firing. The higher the frequency, the stronger the signal. So it is more accurate to think of a signal coming from a neuron not as a single all or nothing event, but an ongoing chain of signals at a certain frequency, and this frequency can be increased or decreased along a continuum – hence it is ultimately analog.
Second, a neuron receives signals typically from multiple other neurons – some of these will be excitatory and others will be inhibitory, and each of these signals can vary in strength. The net output of the neuron is determined partly by the sum of all the excitatory and inhibitory signals it is receiving – again varying along a continuum, and hence an analog signal. As an aside, I said partly due to the sum of its inputs because neuronal function is also modified by the local environment as well as its own biochemistry.
Finally, the strength of connections between neurons also varies along a continuum. A single firing of a neuron does not have the same effect on a neuron to which is synapses, because the firing neuron can have either a weak or a strong connection to the next neuron. Anatomically this is determined by the number of physical synapses that are formed and the tightness of those synapses – literally the distance from the pre-synaptic membrane to the post-synaptic membrane. So the signal strength of even a single neuronal firing (the fundamental unit of neuronal signaling) can vary in an analog fashion.
BTW – I am happy to answer reader questions on the blog. If you have a neuroscience or skeptical related question, please e-mail it to me at snovella<at>theness.com and I may address it in a future blog post.
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