I wonder how much of this is directly related to age (biological aging), and how much is just someone's brain becoming "full" due to more memories getting added every year?
It seems that memories must be stored as embeddings with single multi-neuron assemblies (cortical columns?) storing multiple embeddings as a kind of contents-addressable memory that is able to keep memories distinct due to the very high dimensional space (# neurons per assembly) being used. However, you'd expect that at some point if you store too many memories in a single assembly the recall accuracy is going to go down.
You'd expect that with big brains being so costly, evolution has only equipped us with brains big enough to store a lifetime of memories, so it would be odd if memory didn't suffer as we get old.
To make a computer analogy, it's a bit like a hash table getting too full. Say you had a hash table without any overflow mechanism... up to a point recall may still be pretty good, but as the table gets closer to full there will be more hash collisions and likelyhood of "false recall". Obviously the brain is not a computer, but the analogy may hold up reasonably well if you consider the hash table keys and values as embeddings and the store operation being an embedding merge rather than overwrite.
A fascinating story of "Patient Sh." [1], the man who did not forget.
[1] https://en.wikipedia.org/wiki/Solomon_Shereshevsky
"His memory was so powerful that he could still recall decades-old events and experiences in the smallest details. After he discovered his own abilities, he performed as a mnemonist; but this created confusion in his mind. He went as far as writing things down on paper and burning it, so that he could see the words in cinders, in a desperate attempt to forget them. Some later mnemonists have speculated that this was a mentalist's technique for writing things down to later commit to long-term memory. Reportedly, in his late years, he realized that he could forget facts with just a conscious desire to remove them from his memory, although Luria did not test this directly."
I believe that one need to have superhuman memorization abilities to have definite confusion due to too much remembered. More trivial explanation of this effect in normal ageing persons is age-related brain shrinkage.
> Obviously the brain is not a computer,
Our brain consists of approximately 86 billions quantum computers [2] controlling tens-of-thousands chemical neural networks with at least 10 coefficients, communicating [4] using lasers [5] (coherent light is laser light). [2] https://www.nature.com/articles/s41598-024-62539-5
[3] https://pmc.ncbi.nlm.nih.gov/articles/PMC11655932/
[4] https://pmc.ncbi.nlm.nih.gov/articles/PMC12230014/
[5] https://pubmed.ncbi.nlm.nih.gov/6204761/
Live with that. ;)I see it differently: as a teen, I could remember the exact word for lots of things, I could recall numbers and data with high precision. Nowadays, I'm pretty bad at all those things, but I can very well understand metaphors and connects concepts from wildly different topics — which I couldn't back then.
I see this kind of "interconnecting ideas" of my current years as somewhat connected with "fuzzy memory". It's like, when I retrieve data, it's not as precise, and sometimes I get neighbouring data, but that can actually of use.
I feel like I feel this increasingly as I age. I used to be able to remember nuanced details of API and computer systems. Now, so many of those memories simply get stored as “FLAG: double check the docs” (because I’ll forget).
I’m a lot better at assessing things from a high level, knowing where to find the information I need, and knowing how to assess it for accuracy - but I can’t remember details anymore. Books become summaries. Trips become a few key snapshots representing the trip.
I am not a biologist so I cannot say this authoritatively, but I’m fairly certain that’s not how neuroplasticity works.
I don't think there is a "full" state, but watching the changes as the years go by I have thought of collisions. Not really like a hash table, though--most collisions are with things that would be filed together. I think it's more like the brain returns a random item matching the category. Brains are expensive, memory that gets fuzzy with age is probably the better choice than trying to feed a brain that does better.
The brain does not have the Von Neumann bottleneck. Unlike most current digital systems, the brain doesn’t have a separate memory registry it needs to pull from.
Engrams, that is, the physical trace of a memory, are not stable through life. They start out in the hippocampus, but as the stimulus recedes in time without reinforcement, it moves away.
No evidence exists though that the memory is encoded in one set of cells. This spatial segregation of memory is the worst hangover from the “brain is a computer” analogy. Even if it is, why in the world would it be like our digital devices which specifically have the Von Neumann bottleneck? In biology, memory and processing are not segregated.
There’s growing evidence the memory is much more distributed over the network, and is recomposed based on salience overlap with a new stimulus.
Another factor to keep in mind is circadian rhythms. There’s growing evidence for how much the memory system and timekeeping system overlap, at a molecular level. Every neuron (and other cell) has an intrinsic clock that ticks at roughly 24 hours, and continues to do so even in total darkness.
When you encode the memory has a lot to say, based on your chronotype, on how and how well you will remember it. Same with learning: there’s a time of day based variation.
Sleep, and dreaming, is when these memories seem to get replayed and critical features and connections are incorporated into the system and its regime, awaiting the right triggers to access a state similar to when the memory formed.
I’m stitching across a lot of different research, and I want to be clear many aspects of this system are not yet fully worked out.
But what we do know points to a system that works with different physical and algorithmic priors, and the dynamics are sharply distinct from current digital computers.