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Several scientific projects are trying to map the connectome, such as The Human Connectome Project. The connectomes of other organisms, such as C. elegans, have been mapped already.

Having an organism's connectome, what information can we extract from it? And, most importantly, what information will still be missing?

For example, can we extract the following functional information from the connectome:

  1. Is the synapse connection excitatory or inhibitory?
  2. Which ions does the synaptic connection use?
  3. What is the strength of the synaptic connection?

For simplicity, let's assume that we're using the best imaging and data gathering techniques available (including combinations of techniques).

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    $\begingroup$ Ideally connectome will contain the information 1,2,3. However, depending on the technique (e.g. electron microscopy on slices) it may not get them. I think it would be more clear if you dissociate the technique from the goal of connectomics itself. $\endgroup$
    – Memming
    Apr 3, 2014 at 6:22
  • $\begingroup$ @Memming, let's assume we're using state of the art technique(s) to get the most information we can. $\endgroup$
    – Victor L
    Apr 3, 2014 at 15:26
  • $\begingroup$ @VictorLyuboslavsky Why do you want to know? $\endgroup$
    – Decrypted
    Sep 5, 2014 at 18:37

3 Answers 3

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First at all, the connectome must be interpreted like a static picture of the brain. So anything related with plasticity and dynamical processes will be lost in this map. There are connectome at macroscopic areas using fNMR but I'm going to focus in the cellular level.

We can define three types:

  • Dense Connectome - It is the classical idea of connectome that consist in mapping all the neuronal connections of the whole nervous system or a part of it.
  • Functional Connectome - It is focus only in the connections that play any role in a process (i.e. perception of a color, motor action,...)
  • Saturated Connectome - It is the most wide definition. It is the mappping of all the cells and organelles in the nervous system.

Before answer your questions I need to advise that all of this is limited by the technology. The most extended technique is the electron microscopy (EM) because we obtain a nice resolution for mapping, the problem is that is very hard automatize the annotation step (Characterize different cells and processes). The last year a new technique was released called Clarity this can be used in the connectome but it's too early to see results. In response to your questions:

  1. Yes, with techniques like Clarity we can use markers for the different neurotransmitters. I'm not completely sure if we can characterize the vesicle type with EM, but we can define the pre and post synapses and know the strength (via the amount of vesicles).
  2. Do you mean the amount of ions in the synaptic terminal and in the extracellular space? I think that it could be realize with markers but it is out of the connectome purpose. (Maybe in the Saturated connectome)
  3. Yes. (Answer 1)

In my opinion the most interesting part of the connectome is the mathematical analysis of the network topology.

Check the authors bibliography in the 3 connectome kinds for more info.

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An answer to Question 1 about synapse connections might possibly be found in a New Scientist article earlier this month on brain maps of human foetuses using laser microdissection:

the team has already found that a collection of genes associated with autism is particularly active in the newly developed excitatory neurons in the cortex.

Ed Lein et al "Transcriptional landscape of the prenatal human brain" Nature, DOI:10.1038/nature3185

"Brain map to zoom in on neural blips" New Scientist, 5 April 2014

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It's also possible to extract functional information on a larger measurement scale (especially cognitive function, which depends on the interaction of many parts) from the connectome by running some neurocomputational simulations. This is what the Human Brain Project aims to do, for example, even though it's been getting a lot of criticism lately (one of the reasons being a lack of detail in current connectome information). Some of the areas that are challenging for connectomics to dive into are the dynamic ones, such as neural plasticity - in reality we all have physically unique brains that have learned from experience.

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