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Aging brains blend memories together instead of just forgetting them

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Re: Aging brains blend memories together instead of just forgetting them

#141

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 dimensiona…

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 cel…

> This spatial segregation of memory is the worst hangover from the “brain is a computer” analogy.

It's a computer, it's just not a digital computer

But even digital computers can have stuff like processing-in-memory. "Computers" doesn't need to mean whatever architecture usually run as of 2026

Re: Aging brains blend memories together instead of just forgetting them

#142

Earlier quoted context omitted.

I’m not sure what you think I’m arguing against but saying that it matches with one of the cognitive models du jour is… odd. The problem with the hopfield model is it simplifies the brain too much. The base unit is “the neuron”. Ok… but what about the Astrocyte? Mathematically you can write it as a different kind of neuron. Or ignore it. But why, as a biologist, must I buy this model which ignores the third partner o…

> Ok, but my argument wasn’t with the OP mentioning capacity, but with their analogy. Am I not allowed to break down that analogy with evidence? If someone makes an analogy between aspects of A and B, then there is an implicit assumed shared understanding that A & B are DIFFERENT, and what is being pointed out is that they nonetheless may be considered as having something, typically fairly abstract, in common. Callin…

Kind of done with the other guy, but reading this reminded me of a paper I saw a while ago but admit I haven't read yet. https://journals.aps.org/prx/pdf/10.1103/6shh-9h5m

It's more about computational complexity it seems but maybe it cites stuff that might interest you.

It's using computational neural networks that no one has ever believed represent the biology of the brain, but I think I must still disclose the following to save the precious time of the genius solving the problem all by himself:

It doesn't fully account for every biological detail ever documented, so it's probably a meaningless "curiosity".

Oh it probably also doesn't account for every detail discovered since publication so even if had value at time of publication it is not worth reading now.

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