- Storage and parallel computation in the brain are very expansive and cheap, so the brain prefers to store rather than compute where it can.
- Above all, the brain's storage is highly content-addressable. Similar things in the world are stored with similar representations, so that the brain can generalize, and see commonalities. This is not a graph - graphs are discretized - this is much more flexible.
- Even the acts of storage and retrieval are themselves a kind of computation, a transformation, a compression and a learning experience.
- Memories are not clean silos. Storing a new memory can subtly (and not so subtly) affect other nearby or related memories
- Different parts of the brain use different storage parameters. For instance, the hippocampus is like a hash table, storing each memory relatively cleanly and in isolation, but can only be accessed with exactly the cue. In contrast, the cortex stores memories in a much more content-addressable, overlapping way that's invariant to many small differences (e.g. we can recognize a face whether it's rotated, sunny, tanned, close up, obscured).
What does it say about me that that all makes perfect intuitive sense?
As computer scientists, we get really attached to binary logic because that's how computers work. I think sometimes it doesnt occur to us that it might not actually be the best way to model the universe.
It's also very, very high-dimensional. Imagine a gigantic space, where similar thoughts could be placed next to one another. Thinking would be moving around this space. Free association would be taking a step or two in a random direction. Comparison would be a vector.
This captures a little of the nature of semantic representations (storage of meanings and concepts). But of course, semantic representations differ hugely from, say, representations of a tennis serve, or the phone number you're repeating under your breath while you key it in...
Can you distinguish between the storage schemes in short vs. long term memory? A transition takes place at some point. Long-term storage may not be the best indicator of actual structures used in working memory, which is where the computation actually happens.
Also, content-addressability may be implemented fairly independently of the actual structure, that is an encoding problem that is analogous to an error correcting code in a higher dimensional vector space.
Some forms of short-term storage are volatile, like RAM. They store by coaxing the neural activation into a stable attractor - as long as all the neurons keep firing in sequence, the memory stays alive. This is fast to create, since it doesn't require any hardware writes (changes in synaptic weights).
In contrast, long-term storage involves permanent changes in the synaptic weights between neurons, which survive any fluctuations in activation, and can then subtly influence computation ever after.
And for medium-term storage (from minutes to months, say), you have the hippocampus, which has a big hash table of pointers to long-term structures.
If you're interested in pursuing this, I'd start here (Ken was my former PhD advisor, but I still think this is a rich but comprehensible introduction):
I wrote on this elsewhere:
http://blog.memrise.com/2011/05/how-is-memory-stored-in-brai...
http://blog.memrise.com/2011/05/how-are-brains-different-fro...
For instance:
- Storage and parallel computation in the brain are very expansive and cheap, so the brain prefers to store rather than compute where it can.
- Above all, the brain's storage is highly content-addressable. Similar things in the world are stored with similar representations, so that the brain can generalize, and see commonalities. This is not a graph - graphs are discretized - this is much more flexible.
- Even the acts of storage and retrieval are themselves a kind of computation, a transformation, a compression and a learning experience.
- Memories are not clean silos. Storing a new memory can subtly (and not so subtly) affect other nearby or related memories
- Different parts of the brain use different storage parameters. For instance, the hippocampus is like a hash table, storing each memory relatively cleanly and in isolation, but can only be accessed with exactly the cue. In contrast, the cortex stores memories in a much more content-addressable, overlapping way that's invariant to many small differences (e.g. we can recognize a face whether it's rotated, sunny, tanned, close up, obscured).