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El Duvelle 🌍

@ElDuvelle

Maybe you think that hippocampal #PlaceCells encode the value πŸ“ˆ of spatial goals?

You might also think that their place fields always accumulate at goals 🎯?

*** think again - they do not! ***

Thread on our 2019 #JNeurosci paper:
https://www.jneurosci.org/content/39/13/2522

1/πŸ”½

23/04/2021, 17:07:08

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Retweets: 28

El Duvelle 🌍

@ElDuvelle

Why a thread now, two years later?
because:
- I wasn’t on Twitter yet😞
- People seem to regularly misinterpret it – but really, it’s quite simple 😊
- It's a really cool paradigm (yes, I'm biased)😎
- I can add things not included in the paperπŸ˜‰
- we can discuss!

2/

23/04/2021, 17:07:08

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El Duvelle 🌍

@ElDuvelle

Summary of main findings if you are in a hurry:
1. rats can remember the location of 2 uncued spatial goals
2. rats can associate different values to these goals
3. place fields do *not* over-represent goals
4. place cells do *not* encode goal value in their firing rate.

3/

23/04/2021, 17:07:08

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El Duvelle 🌍

@ElDuvelle

Hippocampal place cells are a strikingly beautiful example of how a tiny biological entity (a cell!) can represent something that is not directly perceivable: the location of the animal.

[region of high activity = place field]

(video from @rmgrieves: https://figshare.com/articles/media/Place_cell_50_minutes_t12c9/8063324)
4/

23/04/2021, 17:07:13

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El Duvelle 🌍

@ElDuvelle

An intact #hippocampus is necessary when rats have to locate a hidden goal and flexibly navigate to it (e.g. watermaze).

So, we asked if hippocampal place cells represent spatial goals as well as their value (e.g. where is your fridge and is it full, half-full, or empty)?

5/

23/04/2021, 17:07:14

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El Duvelle 🌍

@ElDuvelle

To test this we adapted a task used in the LNC (Marseille): the 'continuous navigation task'.

We trained rats to choose between 2 hidden spatial goals and alternate waiting there (for 2s) with searching for a reward released elsewhere in the environment.
(see Tweet1)

6/

23/04/2021, 17:07:17

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El Duvelle 🌍

@ElDuvelle

Why not delivering food at the goal like in most experiments? Because we are interested in the representation of the spatial goal itself, not of reward!

We alternated sessions with equal goal values and sessions where one of the goals consistently delivered 0 or 3 rewards.

7/

23/04/2021, 17:07:18

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El Duvelle 🌍

@ElDuvelle

We were happy to find that the rats differentiated the two goals and adjusted their visits with the changing values, even though goal & reward were dissociated!

Here, >0 numbers indicate preference for the goal with highest value πŸ”½
(left: example, right: average/sessions)

8/

23/04/2021, 17:07:19

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El Duvelle 🌍

@ElDuvelle

(small digression: learning the 2-goals takes a looong time - ~6 weeks πŸ˜… - and was done in steps; we tested the 1-0 condition during learning a bit, but not so much the 1-3, which is why it was a good surprise to see it working!)

9/

23/04/2021, 17:07:20

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El Duvelle 🌍

@ElDuvelle

Here are the (speed-filtered) rate maps of some example place cells recorded in the taskπŸ”½
Note that we were able to follow these cells for several days (2 days shown here), by matching their waveforms. See any change specific to goal value?

(note, plots are rotated a bit)
10/

23/04/2021, 17:07:21

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El Duvelle 🌍

@ElDuvelle

To look for goal-value coding, we analysed place field locations, cumulated firing rates, average firing rates, overdispersion (variability of firing): no significant difference was found in any of these.
Note also: no overrepresentation of the goals, even of high-value!

11/

23/04/2021, 17:07:23

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El Duvelle 🌍

@ElDuvelle

In previous studies (e.g. Hok et al., 2007) most place cells were found to express some firing at the goal, *outside* of their place field. We also found this (CA1 &CA3, left).

Could it reflect value coding? Nope! The goal firing did not change with goal value (right).

12/

23/04/2021, 17:07:24

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El Duvelle 🌍

@ElDuvelle

(note, in the previous plots, the slightly different temporal profile at the end of the delay period for the 0 value goal, with less of a decrease - this might be related to having no food dispenser sound for that goal, so rat staying for longer?πŸ€”)

13/

23/04/2021, 17:07:24

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El Duvelle 🌍

@ElDuvelle

Focusing on individual cells, we tested if their firing at a given goal was significantly modulated by goal value across sessions (compared to a shuffle). This was sometimes the case for a single session, but *0* (zero!) cells consistently showed this for multiple sessions.

14/

23/04/2021, 17:07:25

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El Duvelle 🌍

@ElDuvelle

We (here, @rmgrieves) also looked at theta rhythm. As in previous reports, while rats were immobile at the goal, theta was still there (with lower power &frequency).
Neither P nor F at the goal differed between values of 1 & 3. BUT frequency was different between 1 and 0...

15/

23/04/2021, 17:07:26

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El Duvelle 🌍

@ElDuvelle

(which could be investigated further in future studies. Maybe something to do with theta sequences?)

16/

23/04/2021, 17:07:26

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El Duvelle 🌍

@ElDuvelle

A few more findings:
- I repeat, place fields did *not* overrepresent the goals! (Tweet11)
- place cells did not globally remap between foraging & goal-directed paths
- many Silent Cells (with no place field) were active at the goal! what does it mean?!πŸ”½[not in paper]

17/

23/04/2021, 17:07:27

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El Duvelle 🌍

@ElDuvelle

Conclusion: while in other tasks place cells sometimes over-represent goals and track goal value, in this spatial task with flexible, multiple trajectories to uncued goals, place cells were purely spatial. Suggests that value-related info really comes from other brain areas.

18/

23/04/2021, 17:07:28

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El Duvelle 🌍

@ElDuvelle

Let's see... are you still with me? (don't worry, it's almost finished!)

19/

23/04/2021, 17:07:28

Favs: 1

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El Duvelle 🌍

@ElDuvelle

Let's now criticise our own paper:
- we don't have many cells (104 place cells / 157 pyrs)
- we don't look at replay or theta sequences
- we don't do super-fancy analyses
- I spent way too much time screening (i.e. searching for cells-not that anyone cares)
Anything else?

20/

23/04/2021, 17:07:29

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El Duvelle 🌍

@ElDuvelle

This project took place mostly during my PhD, in @LNC_Space_team with Etienne Save, Bruno Poucet and @vincent_hok but also in the lab of @AngeloArleo; it was finalised with the help and support of @drkjjeffery and @rmgrieves. I would like to thank all of these amazing people!
21/

23/04/2021, 17:07:29

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El Duvelle 🌍

@ElDuvelle

I would also like to thank the people who trained me (including @PierreY83952112 ), generally helped me (@LLogiaco) and supported me (@MarciaBecu) (plus many others not on twitter!) 😘😘😘

22/

23/04/2021, 17:07:29

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El Duvelle 🌍

@ElDuvelle

Unfortunately, I haven't taken the time yet to make the data publicly available... But if you were potentially interested in collaborating to analyse other aspects of it... It might motivate me to make it available, also, I have several ideas! So, let me knowπŸ˜ƒ

23/

23/04/2021, 17:07:30

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Retweets: 0

El Duvelle 🌍

@ElDuvelle

Here are a few references if you want to dig deeper:
- goal coding
https://www.jneurosci.org/content/27/3/472.short
https://www.nature.com/articles/nn.2599
https://www.sciencedirect.com/science/article/pii/S2352154616302832

- value coding
https://onlinelibrary.wiley.com/doi/abs/10.1002/hipo.10056
https://journals.physiology.org/doi/full/10.1152/jn.00091.2011
https://www.jneurosci.org/content/32/43/15053.short
https://pubmed.ncbi.nlm.nih.gov/28241404/

almost the end/

23/04/2021, 17:07:30

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Retweets: 0

El Duvelle 🌍

@ElDuvelle

I hope you understood & enjoyed this thread and learned some new things!
One of the goals is to discuss this study, and the general question of representation of goals by place cells, as well as answer any questions you might have on any of these tweets so, fire away! πŸ˜ƒ

end/

23/04/2021, 17:07:31

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