#neuroscience

src: New Yorker

Reading about the malleability of memory, and relating this to the recent ideas from #neuroscience on how our cells work through linear algebra (see [[rotation-dynamics-in-neurons]] and [[neural-code-for-faces]]), I wonder if there’s a similar way of coding the curious properties of memory as artefacts of linear algebra.

A few key ideas:

• I assume memory is projected information, and so reconstructing it involves remembering the correct angle
• the malleability, or degradation of memory over time might come from the fact that you’re sharing the same space, and so over time, as you write to the same space (at various angles), you’re inevitably going to get corruption
  • a prediction would be that if your ability to form new memories is lost, then you’re going to get much less corruption (though basically that holds for any memory process that involves some sort of overwriting).
• It’s clear that memory and emotions are heavily intertwined, though I don’t see how this model is able to capture that
• It’s also clear that memory and stories are related:
  • one way to think about this is that stories are either simple building blocks that help with prediction (i.e. if you have a story framework, then it sort of tells itself).
  • so it’s sort of like having lower dimensional representations of our memories, that are able to capture the essense of the memory, without actually having to store all the particulars.