Tag: Miniscope

I Think, Therefore I Eat

Why do you eat? We’ve come to realise that it’s far more complex than simply saying you eat because you are hungry. Anyone who’s been reading my blog will understand the complexity of the neural networks involved in the control feeding behaviour.

A paper came out a couple of weeks ago that splits out a number of the drivers for food intake by differentiating a subpopulation within the lateral hypothalamus (LH)1. This stems from an earlier paper that found that GABAergic (VGAT-expressing) neurones of the LH show heterogeneous feeding behaviours2:

  • Consummatory behaviour – the classic homeostatic drive to consume calories
  • Appetitive behaviour – the more complex drive for reward and rewarding foods

Anyway, back to the recent Siemian paper, where they investigate leptin receptor (LEPR)-expressing neurones of the LH as a subpopulation (~20 %) of the larger VGAT population. They start with my favourite method for inhibiting neurones, which is to ablate them using cre-dependent caspase (AAV-FlEX-tsCasp3-TEVp; Figure 1A/B). Ablating LH VGAT neurones with caspase causes a lean phenotype with reduced food intake (“consummatory behaviour”; Figure 1C/D), with delayed learning to cue-stimulated sucrose intake (“appetitive behaviour”; Figure 1E). However, LH Lepr-ablated mice had no change to gross food intake or body weight (Figure 1F/G), but did learn a cue-stimulated appetitive response (Figure 1H).

In order to directly control feeding behaviour, they next use my favourite method for driving neuronal activity, which is optogenetic stimulation of ChR2. Injecting cre-dependent ChR2 or the inhibitory NpHR into the LH of VGAT-cre or Lepr-cre mice (Figure 2A/B), they run two behaviour tests to mimic the data seen with caspase. In this case, because optogenetic stimulation is instantaneous (rather than the long-term chronic caspase), they use acute tests.

First is free-access feeding to assess consummatory behaviour; second is real-time place preference to assess appetitive behaviour. I use both these tests frequently, and find them to be both robust and informative. The data show, as expected, that optogenetic stimulation of VGAT neurones drives consummatory behaviour (Figure 2D/E) and a strong preference (Figure 2H/I), whereas stimulation of Lepr neurones induced place preference (Figure 2J/K) without any impact on consummatory behaviour (Figure 2F/G).

Next comes the data that I think is the most interesting part of this paper, and also the most complex, where the authors use a fluorescent miniscope to investigate GCaMP activity in the two populations of interest (Figure 3A/B). What’s really interesting here is how they split out the neuronal populations based on the timing of their response to whether they were responsive during the cue or after it (they show “pre-responsive” neurones, but in a world without midi-chlorians, I don’t think we should put too much stock in neurones that predict when a cue is going to happen).

So anyway, what we’re interested in is the subpopulations of neurones that respond differently between the CS+ and CS– stimuli, which for LHVGAT is the post-lick reward-responsive neurones (Figure 3G), but for LHLEPR is both the cue-responsive and reward-responsive neurones (Figure 3J/K). This is quantified in Figure 3L-O, where they show that LHLEPR neurones are strongly and significantly predictive of reward from cues. This means that in addition to the general LH drive for reward, the LHLEPR neurones are the ones that can distinguish cues and therefore may be important for the behavioural discrimination of food cues.

There are a couple more figures that go into further detail to show the importance of the LHLEPR projections to the VTA for mediating appetitive learning, and then show that the LHLEPR neurones are not relevant for cocaine preference. But, I’ve shown here the results that I found most interesting, and how they inform us on the control of feeding behaviour. In particular, I want to highlight the use of miniscopes to pick out subpopulations of neurones based on behavioural responses.

1. Siemian et al. Cell Reports 36, 109615 (2021) Lateral hypothalamic LEPR neurons drive appetitive but no consummatory behaviors

2. Jennings et al. Cell 160, 516-527 (2015) Visualizing hypothalamic network dynamics for appetitive and consummatory behaviors.

Miniscopes et al.

I have written about the use of fibre photometry to record Ca2+ activity in vivo, and today I’ll be exploring a more advanced (and far more complex) version of that. Namely, the use of a head-mounted miniscope to record videos of individual neurones.

I first learned about head-mounted miniscopes at the same time as photometry – in 2015 when Chen and Betley showed how AgRP neurones really work1,2. Nobody could read the Betley paper with their beautiful head-mounted miniscope data, and not be excited by that data and want to do it for themselves.

But, one must also recognise that it is clearly an exceptionally complex technique, and that you should only use it when you absolutely need to, ie. don’t do the super-difficult version when you can get just as good an answer with fibre photometry. And having said that, I don’t know if miniscopes were necessary for Betley’s paper – Chen found many similar results without them.

Anyway, my point here is to reiterate what I always say, which is to make your experiments as simple as possible, to give you the strongest and cleanest answer. So in that vein, I will investigate a paper that used miniscopes to find a response that wouldn’t have been possible using photometry, a 2018 paper by Chen et al.3

This paper combines head-mounted miniscope recordings of Galanin-expressing neurones (Gal-cre) of the dorsomedial hypothalamus (DMH) and telemetry-based EEG recordings of brain activity (Figure 1A). They combine the data to allow them to correlate the EEG activity showing different phases of sleep/wake and GCaMP signal from individual neurones (Figure 1C). What’s really interesting is that they show two distinct subpopulations of Galanin neurones, with opposite behaviour during REM and non-REM sleep.

So they performed a series of exhaustive tracing studies (which I won’t go into here), that showed strong and mutually exclusive projections from the DMH galanin neurones to the preoptic area (POA) and the raphe pallidus (RPa). To show these correlated with the REM and non-REM sleep patterns, they redid their miniscope experiments on the DMH, but this time they used a retro-transported AAV-GCaMP to label specifically the differently projecting subpopulations (Figure 2A/E). This elegant experiment showed that the POA-projecting subpopulation was active during non-REM sleep (Figure 2C/D), but the RPa-projecting population was active during REM sleep (Figure 2 G/H).

The authors then go on to perform another exhaustive series of experiments, this time using optogenetics to show that the different DMH projection sites don’t just correlate to REM or non-REM sleep, they can also drive changes between those sleep states.

Lastly, I’m just going to briefly go into my interest in doing these experiments myself. A year or so ago, I enquired with Inscopix (who make the benchmark miniscopes, and I think were spun out from the lab that originally developed them) about purchasing one from them4. The quote came to £60k, which was far too much for us, so I forgot about them for a while to focus on other things.

And then recently, while exploring options related to developing fibre photometry, I came across the open source head-mounted miniscope project from UCLA5. I had seen this before but the sheer complexity put me off. Essentially, they have developed their own miniscope, and have made the designs freely available online. The problem is that this is such a complex technique, I wouldn’t be happy having to build the microscope myself as well as learning and optimising the system; I could just see it being a massive waste of time to get it working well.

Anyway, when I revisited the UCLA miniscope site recently, I found that they have not only released a new lightweight and more advanced version of their miniscope, they also have started selling them fully assembled on the open ephys website6. And their price? £1,940 (including the acquisition box). So, needless to say, I will be requesting from my supervisor that we buy one. Or five. The price is reasonable enough that I think the only reason he’ll say no is if he considers it a waste of my time. Or more to the point, that playing around with one of these will distract me from my -real- work.

There is major challenge with getting a miniscope from anyone that isn’t Inscopix, and that comes down to the GRIN lenses that you need to do the imaging in the brain (for any that don’t know, the GRIN lens is like a fibre optic that has a precise structure that means you keep the image in focus). Anyway, it turns out that the only company in the world that makes GRIN lenses longer than about 4 mm of a type that you can use for in vivo imaging is called GrinTech, and they have an exclusivity deal with Inscopix. Which means that they won’t sell them to you, you need to go to Inscopix, which means spending £60k.

So, for any “real” neuroscientists that work on structures such as the hippocampus or cortex near the brain surface, you should be fine to get the cheap miniscope and get shorter GRIN lenses from places such as Edmund optics. I, on the other hand, and anyone else who works on more interesting and deeper brain regions, will have to keep searching.

1. Chen et al., Cell 160, 829-841 (2015) Sensory detection of food rapidly modulates arcuate feeding circuits.

2. Betley et al., Nature 521, 180-185 (2015) Neurons for hunger and thirst transmit a negative-valence teaching signal.

3. Chen et al., Neuron 97, 1168-1176 (2018) A hypothalamic switch for REM and non-REM sleep.

4. https://www.inscopix.com

5. www.miniscope.org

6. https://open-ephys.org/miniscope-v4