@albertcardona

Thanks for these citations! I like that we can now stop talking about "the #connectome". A single #connectome doesn't exist. Anymore than "a single #genome" does. We need to start seeing species as populations with variability (this is how #evolution works! - by shifting those population distributions around).

As a practical note (coming back from #SFN2023), I'm getting worried about all of the experiments that are taking some specific mouse strain, making some observation (specific connections from a small subset of cells in structure A project to this specific part of structure B), and generalizing from that to all mice (and all rats and all humans). I wonder how much the various very specific connections that are being traced with viral techniques are specific to that "genetic family" of mice and how much variation we should be expecting.

I think we are vastly underestimating the variability in these life forms we are studying.

@elduvelle_neuro @BenoitGirard @Raphael_Brito

A few notes.

1. Remember that even the #SharpWaveSequences that Pfeiffer and Foster 2013 [https://pubmed.ncbi.nlm.nih.gov/23594744/] saw going ahead of the animal is a very very small proportion. (Home was twice as likely as the other 35 options. So it's 2/37 vs 1/37 or an increase of 2.7%. ) Still real. But small. Also, lots of people have seen #SWRSequences go to places rats are not going to go. (Such as Gupta et al 2010 [https://pubmed.ncbi.nlm.nih.gov/20223204/], where it was more likely to go to the other side if the animal was NOT going there next - perhaps "keeping the map flat"?)

2. We know that in Wikenheiser and Redish 2016 (https://pubmed.ncbi.nlm.nih.gov/25559082/), #ThetaSequences on the first part of the journey go longer when the rat is going to run longer (where start of journey is same, but distance from rat to goal varies), but on the last part of the journey, the sequences are the same length (when start of journey is different, but distance from rat to goal is the same).

3. We also know that both time of second half of theta and sequences go longer the more time it will take to reach the goal. (Schmidt and Redish 2019 [https://pubmed.ncbi.nlm.nih.gov/30892976/]).

4. That all being said, @elduvelle_neuro is correct that on two-alternative-forced-choice tasks (2AFC) #ThetaSequences while deliberating do not reflect the final choice made in any way we've been able to detect, and that when they do (such as in Johnson and Redish 2007 [https://pubmed.ncbi.nlm.nih.gov/17989284/] or Kay...Frank 2020 [https://pubmed.ncbi.nlm.nih.gov/32004462/]) the rat does not seem to be deliberating anymore.

My suspicion is that this may be because of the 2AFC structure of the task, where knowing you don't want to go one way is just as informative as saying you want to go the other way. We are now starting to try to develop tasks with multiple paths to goals (so not 2AFC). @elduvelle_neuro 's cool star-shaped task is a good one for this. As are a bunch of the cool new hex tasks from the Loren Frank lab that were presented at #SFN2023 this year.