<p>Understanding how memories are stored and retrieved in the brain is actually a pretty popular topic in <a href="https://neuronaldynamics.epfl.ch/" rel="nofollow noreferrer">neuronal dynamics</a>. The mathematical theory of <a href="https://en.wikipedia.org/wiki/Dynamical_system" rel="nofollow noreferrer">dynamical systems</a> comes in handy here. A population of neurons can be modeled as a complete weighted graph (all possible connections between nodes are present and have a weight). The weights of these connections (read, synapses) is what encodes the memory. To understand how retrieval works, we need to talk about attractors in the theory of dynamical systems. Attractors are states toward which a dynamical system tends toward and stabilizes in. An attractor network is a graph like ours, which invariably tends toward an attractor. A simple model of memory that is an attractor network is the <a href="https://en.wikipedia.org/wiki/Hopfield_network" rel="nofollow noreferrer">Hopfield network</a>. Once retrieval has been initiated, the population of neurons will eventually settle on a single memory.</p>
<p>For instance, <a href="http://learnmem.cshlp.org/content/14/11/714.full" rel="nofollow noreferrer">certain studies</a> consider the existence of such attractor networks in the hippocampus, a major part of the brain's memory system.</p>

CC BY-SA 4.0
2021-11-29T21:39:18.570Z
2021-11-29T21:39:18.570Z
David Cian
<p>Lately, I (as someone with no experience or prior knowledge in the topic) have been thinking about...thinking. The part that intrigues me the most is memory. As a computer-y type person, I tend to think in logic and organized systems of bytes, but I understand this way of thinking about the brain is <a href="https://www.eklavya.in/pdfs/Sandarbh/Sandarbh_105/01-14_The_Empty_Brain.pdf" rel="noreferrer">incorrect</a>.</p>

<p>From what I can half-understand half-guess from the limited information I can find online, the brain is made up of neurons which build up memories in their interactions through <a href="http://www.mrburkholder.com/uploads/7/5/2/1/7521101/how_our_brains_make_memories__science__nature__smithsonian_magazine.pdf" rel="noreferrer">synapses</a>, which send chemicals to each other.</p>

<p>In order to visualize, say, a thumbtack, I would need a lot of information. I think trying to recall an image of a thumbtack would send a "trigger" to a neuron, telling it to pass it on to other neurons, building up an image from these chemicals. I think I've read these chemicals are also what causes emotions (dopamine especially being the one that comes to mind), but I could be mixing things up.</p>

<p>So when thinking about a thumbtack, those neurons would connect in a pattern, to ensure I get all the right signals to envision one. This makes a lot of a sense to me, and explains things like forgetting and the ability to imagine and visualize inexactly with ease, but not remember exact values or images.</p>

<p>Could anyone provide any insight into whether my somewhat informed guesses are correct, or to any more accurate explanations of what is currently known? Thanks!</p>

CC BY-SA 4.0
2020-01-03T18:56:48.713Z
Possibly related: [The computer model of the brain](https://psychology.stackexchange.com/q/19983/7001).
Arnon Weinberg
<neuroscience><memory>
Are memories stored as patterns of chemicals/emotions?
rydwolf
# Are memories stored as patterns of chemicals/emotions?

(Asked by: username_0 on 2020-01-03)

Lately, I (as someone with no experience or prior knowledge in the topic) have been thinking about...thinking. The part that intrigues me the most is memory. As a computer-y type person, I tend to think in logic and organized systems of bytes, but I understand this way of thinking about the brain is [incorrect](https://www.eklavya.in/pdfs/Sandarbh/Sandarbh_105/01-14_The_Empty_Brain.pdf).

From what I can half-understand half-guess from the limited information I can find online, the brain is made up of neurons which build up memories in their interactions through [synapses](http://www.mrburkholder.com/uploads/7/5/2/1/7521101/how_our_brains_make_memories__science__nature__smithsonian_magazine.pdf), which send chemicals to each other.

In order to visualize, say, a thumbtack, I would need a lot of information. I think trying to recall an image of a thumbtack would send a "trigger" to a neuron, telling it to pass it on to other neurons, building up an image from these chemicals. I think I've read these chemicals are also what causes emotions (dopamine especially being the one that comes to mind), but I could be mixing things up.

So when thinking about a thumbtack, those neurons would connect in a pattern, to ensure I get all the right signals to envision one. This makes a lot of a sense to me, and explains things like forgetting and the ability to imagine and visualize inexactly with ease, but not remember exact values or images.

Could anyone provide any insight into whether my somewhat informed guesses are correct, or to any more accurate explanations of what is currently known? Thanks!

**Tags:** neuroscience, memory

> **Comments:**
> **username_1**: Possibly related: [The computer model of the brain](https://psychology.stackexchange.com/q/19983/7001).  

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## 1 answers

### Answer by username_2 on 2021-11-29. Score: 4

Understanding how memories are stored and retrieved in the brain is actually a pretty popular topic in [neuronal dynamics](https://neuronaldynamics.epfl.ch/). The mathematical theory of [dynamical systems](https://en.wikipedia.org/wiki/Dynamical_system) comes in handy here. A population of neurons can be modeled as a complete weighted graph (all possible connections between nodes are present and have a weight). The weights of these connections (read, synapses) is what encodes the memory. To understand how retrieval works, we need to talk about attractors in the theory of dynamical systems. Attractors are states toward which a dynamical system tends toward and stabilizes in. An attractor network is a graph like ours, which invariably tends toward an attractor. A simple model of memory that is an attractor network is the [Hopfield network](https://en.wikipedia.org/wiki/Hopfield_network). Once retrieval has been initiated, the population of neurons will eventually settle on a single memory.

For instance, [certain studies](http://learnmem.cshlp.org/content/14/11/714.full) consider the existence of such attractor networks in the hippocampus, a major part of the brain's memory system.


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