<h2>Well, regarding this short definition of a connectome from <a href="https://en.wikipedia.org/wiki/Connectome" rel="nofollow noreferrer">Wiki</a>:</h2>
<blockquote>
<p>A connectome (/kəˈnɛktoʊm/) is a comprehensive map of neural
connections in the brain, and may be thought of as its &quot;wiring
diagram&quot;. More broadly, a connectome would include the mapping of <strong>all
neural connections</strong> within an organism's nervous system.</p>
</blockquote>
<p>Therefore <strong>you could read out <em>all</em> information, assuming you have enough computational power.</strong> (A perfect connectome would represent all information processes in the brain. Because processing information through connections is all the brain does, right? :D)</p>
<p>In the real world however, we need <strong>'models' as simplifications</strong> to deal with these phenomena. A connectome is nothing else than such a model.</p>
<h2>Influential Factors to consider</h2>
<ol>
<li><p>To <strong>make predictions of real-world constructs, you need to assess real-world phenomena</strong>. F.i. you need to have
postulated some outcome-variables (for lets say Schizophrenia) that need to
be quantified in the real-world <em>(external validity)</em> to be related to
inner-brain processes. These real-world concepts of psychological
processes, speaking of the behavioral, emotional and cognitive
aspects (which can be measured), are inherently fuzzy, which raises
the question, to which certainty we will be able to predict
psycho-physiological correlates.</p>
</li>
<li><p>Not to forget, memories are mainly coded as '<strong>processes over-time</strong>',
something like chains of activation (other than distinct anatomy and
brain-areas who would define thoughts). Also noisyness and
randomness is always a variable you need to consider. (I think the
Hippocampus functioning of neurons induces randomness by design, but
I have no source right now.)</p>
</li>
<li><p>Also to mention:
The <strong>individuality of brains</strong> leads to decreased prediction of the model or a general model that would hold for every individual</p>
</li>
<li><p>The <strong>plasticity</strong> of the brain states states the ability to change and
evolve over time.  (Concepts like Imprinting and so on). A static
model might also not be sufficient to represent these (also highly
individualized) processes.</p>
</li>
<li><p><strong>Situational- or environmental dependency</strong> also influences your
current state of mind. (It is not possible to 'control' all
environmental factors, unless you had infinite computational power.)</p>
</li>
<li><p>Also the brain and <strong>toughts are highly self-/auto-activating, recurring and in parallel</strong>.
Millions of neurons firing at the same time and oscillating in
rhythms. Thoughts that become conscious might only be the tip of the
iceberg in a sea of thoughts that are below a certain threshold.</p>
</li>
</ol>
<h2>My proposal to your question: &quot;What exactly can you get from a connectome?&quot;</h2>
<p><em>In principle everything is possible, but practically we might never truely decode everything from a philosopical and mathematical point-of-view (we needed to create a perfect connectome, which would be a perfect simulation of the entire brain). We might however be able to find <strong>very accurate brain-markers</strong> that help in <strong>predicting real-world concepts</strong> that seem relevant for humans</em> :)</p>
<h2>Resources</h2>
<p>Because it is great: <a href="https://youtu.be/sROKYelaWbo" rel="nofollow noreferrer">Video of synchronizing fireflies</a></p>
<p>Buszaki: <a href="https://global.oup.com/academic/product/rhythms-of-the-brain-9780199828234?cc=de&amp;lang=en&amp;" rel="nofollow noreferrer">Rhythms of the Brain</a> is a nice read on some how information is created in the brain and different processes</p>

CC BY-SA 4.0
2019-05-16T14:20:24.127Z
Each synapse and each neuron surely plays a part of the communication processes. But I guess more implicitely in the case of a Connectome. like any communication/information process in the world is using atoms, though you would usually not describe these processes on an atom level. (Maybe (Quantum) Information Theory does). A Connectome would probably focus on whole brain communication processes.
bambamfox
CC BY-SA 4.0
2019-05-16T14:29:49.383Z
It is the job of scientists to extract information out of a fuzzy world. Didn't say otherwise. 
And because everything is interconnected, you cannot ultimately explain the brain by either a large scale communcation model (connectome as 'one' out of many models for large-scale dynamics), or a synapse level or a chemical level, and so on, all alone. The Connectome just focusses on the larger scale communication.
bambamfox
CC BY-SA 4.0
2019-05-20T15:53:15.030Z
A Connectome (not sure about where the word is originating, it might not be a widely used term in neuroscience) is simply a mapping of connections in the brain on a larger scale. What region communicates with what region. If you could measure all the details, every synapse as well, the model could be way more complex, but the technologies have its limits. As I said, there are technologies for measuring behavior of single neurons as well, and so on, there is a lot more neurophysiological technologies. Currently I think the Connectome is nearly solely based on fMRI.
bambamfox
CC BY-SA 4.0
2019-05-20T22:34:00.437Z
Well kind of, the eye is a classic example - a signal travelling from the eye to some nuclei to the back of your head. https://en.wikipedia.org/wiki/Visual_system (Neuroanatomy topic is essentially the same as a connectome, which roots from the fMRI research area)  If you could anatomically rebuild exactly every neuron, then this would be the perfect model, but this is not possible and 'would need infinite processing power'
bambamfox
CC BY-SA 4.0
2019-05-20T22:36:54.873Z
sure^^ you're welcome
bambamfox
CC BY-SA 4.0
2019-05-15T09:26:39.733Z
2021-01-19T18:06:27.763Z
2021-01-19T18:06:27.763Z
bambamfox
<p>I am not a brain scientist but the following question seems reasonable to me. </p>

<p>Prof. Sebastian Seung has given a TED talk named "I Am My Connectome". If I understand correctly, connectome is basically the graph whose vertices are neurons and whose edges are synapses (strictly speaking, there are many different kinds of neurons so the vertices of the graph should be colored, but let us forget it for now). </p>

<p>The title then appears to be a (probably intentional) oversimplification, since even though we do not understand how exactly memories are stored in the brain (and there are many different kinds of memories), things I will roughy call "electrical and chemical variables" play some role in it (so simply remembering whether there is a link or not between two neurons is not going to fly). I understand that studying these "electrical and chemical variables" is like over a half of the brain science but the exact definition is not particularly important for this question. If my understanding is correct, then one should not get overly excited about the present achievements of the Brain Preservation Foundation (the most promising one is, I think, preserving the connectome of a mammal for some time after its death using a chemical solution/freezing), since they have not shown that they can preserve any of the "electrical and chemical variables".</p>

<p>The question is: what information can you actually extract out of a connectome, assuming you do not know anything else about the brain? Like something about a person's health, personality, anything? The chance of them having schizophrenia? Their most likely age?</p>

<neuroscience><memory><brain>
What information does the connectome actually contain?
connectome
# What information does the connectome actually contain?

(Asked by: username_0 on 2019-05-14)

I am not a brain scientist but the following question seems reasonable to me.

Prof. Sebastian Seung has given a TED talk named "I Am My Connectome". If I understand correctly, username_0 is basically the graph whose vertices are neurons and whose edges are synapses (strictly speaking, there are many different kinds of neurons so the vertices of the graph should be colored, but let us forget it for now).

The title then appears to be a (probably intentional) oversimplification, since even though we do not understand how exactly memories are stored in the brain (and there are many different kinds of memories), things I will roughy call "electrical and chemical variables" play some role in it (so simply remembering whether there is a link or not between two neurons is not going to fly). I understand that studying these "electrical and chemical variables" is like over a half of the brain science but the exact definition is not particularly important for this question. If my understanding is correct, then one should not get overly excited about the present achievements of the Brain Preservation Foundation (the most promising one is, I think, preserving the username_0 of a mammal for some time after its death using a chemical solution/freezing), since they have not shown that they can preserve any of the "electrical and chemical variables".

The question is: what information can you actually extract out of a username_0, assuming you do not know anything else about the brain? Like something about a person's health, personality, anything? The chance of them having schizophrenia? Their most likely age?

**Tags:** neuroscience, memory, brain


---

## 1 answers

### Answer by username_1 on 2019-05-15. Score: 1

## Well, regarding this short definition of a username_0 from [Wiki](https://en.wikipedia.org/wiki/Connectome):

> A username_0 (/kəˈnɛktoʊm/) is a comprehensive map of neural
> connections in the brain, and may be thought of as its "wiring
> diagram". More broadly, a username_0 would include the mapping of **all
> neural connections** within an organism's nervous system.

Therefore **you could read out *all* information, assuming you have enough computational power.** (A perfect username_0 would represent all information processes in the brain. Because processing information through connections is all the brain does, right? :D)

In the real world however, we need **'models' as simplifications** to deal with these phenomena. A username_0 is nothing else than such a model.

## Influential Factors to consider

1. To **make predictions of real-world constructs, you need to assess real-world phenomena**. F.i. you need to have
   postulated some outcome-variables (for lets say Schizophrenia) that need to
   be quantified in the real-world *(external validity)* to be related to
   inner-brain processes. These real-world concepts of psychological
   processes, speaking of the behavioral, emotional and cognitive
   aspects (which can be measured), are inherently fuzzy, which raises
   the question, to which certainty we will be able to predict
   psycho-physiological correlates.
2. Not to forget, memories are mainly coded as '**processes over-time**',
   something like chains of activation (other than distinct anatomy and
   brain-areas who would define thoughts). Also noisyness and
   randomness is always a variable you need to consider. (I think the
   Hippocampus functioning of neurons induces randomness by design, but
   I have no source right now.)
3. Also to mention:
   The **individuality of brains** leads to decreased prediction of the model or a general model that would hold for every individual
4. The **plasticity** of the brain states states the ability to change and
   evolve over time. (Concepts like Imprinting and so on). A static
   model might also not be sufficient to represent these (also highly
   individualized) processes.
5. **Situational- or environmental dependency** also influences your
   current state of mind. (It is not possible to 'control' all
   environmental factors, unless you had infinite computational power.)
6. Also the brain and **toughts are highly self-/auto-activating, recurring and in parallel**.
   Millions of neurons firing at the same time and oscillating in
   rhythms. Thoughts that become conscious might only be the tip of the
   iceberg in a sea of thoughts that are below a certain threshold.

## My proposal to your question: "What exactly can you get from a username_0?"

*In principle everything is possible, but practically we might never truely decode everything from a philosopical and mathematical point-of-view (we needed to create a perfect username_0, which would be a perfect simulation of the entire brain). We might however be able to find **very accurate brain-markers** that help in **predicting real-world concepts** that seem relevant for humans* :)

## Resources

Because it is great: [Video of synchronizing fireflies](https://youtu.be/sROKYelaWbo)

Buszaki: [Rhythms of the Brain](https://global.oup.com/academic/product/rhythms-of-the-brain-9780199828234?cc=de&lang=en&) is a nice read on some how information is created in the brain and different processes

> **Comments:**
> **username_1**: Each synapse and each neuron surely plays a part of the communication processes. But I guess more implicitely in the case of a Connectome. like any communication/information process in the world is using atoms, though you would usually not describe these processes on an atom level. (Maybe (Quantum) Information Theory does). A Connectome would probably focus on whole brain communication processes.  
> **username_1**: It is the job of scientists to extract information out of a fuzzy world. Didn't say otherwise.  And because everything is interconnected, you cannot ultimately explain the brain by either a large scale communcation model (username_0 as 'one' out of many models for large-scale dynamics), or a synapse level or a chemical level, and so on, all alone. The Connectome just focusses on the larger scale communication.  
> **username_1**: A Connectome (not sure about where the word is originating, it might not be a widely used term in neuroscience) is simply a mapping of connections in the brain on a larger scale. What region communicates with what region. If you could measure all the details, every synapse as well, the model could be way more complex, but the technologies have its limits. As I said, there are technologies for measuring behavior of single neurons as well, and so on, there is a lot more neurophysiological technologies. Currently I think the Connectome is nearly solely based on fMRI.  
> **username_1**: Well kind of, the eye is a classic example - a signal travelling from the eye to some nuclei to the back of your head. https://en.wikipedia.org/wiki/Visual_system (Neuroanatomy topic is essentially the same as a username_0, which roots from the fMRI research area)  If you could anatomically rebuild exactly every neuron, then this would be the perfect model, but this is not possible and 'would need infinite processing power'  
> **username_1**: sure^^ you're welcome  

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