How High Can You Go?

Validating optogenetic stimulation frequency

For my most recent optogenetics experiment, I did a full validation for the optimal optogenetics stimulation frequency. FYI, I would recommend doing this for any new paradigm.

I took a safe “positive control” measure that I knew would be influenced by my neurones of interest. I then applied a ramped increase in stimulation frequencies: 1, 2, 5, 10 and 20 Hz. This gave me what is essentially a dose response, with increasing food intake up to 5 Hz. But it then plateaued with no further increases at higher frequencies. I was then able to select the 5 Hz frequency as my optimal, as it gave me a maximal response while limiting the amount of light.

This is important, because the light is not only phototoxic at high levels, it can produce neuronal activation in the absence of ChR2. I say this, because I will always see some amount of c-fos at the fibre site, even in control mice. And this is why it is so important to include non-ChR2 mice in your study. You also find that at higher light power and frequencies, that your action potential fidelity drops.

What’s the optimal stimulation frequency?

I digress. And ramble. My point today is to talk about the optimal frequency with which to stimulate your opto mice. I have in the past used 10 Hz, or sometimes even 20 Hz, just as a kind of industry standard, without proper optimisation. This is easy to do, but as I’ve just shown, is often not the optimum for your experiment.

A common stimulation paradigm in the literature is to stimulate at 20 Hz in a pulsed manner – for example flashing for 1 second, then off for 3 seconds in a cycle. The popularity of this method likely stems from its use by Aponte, Atasoy and Betley in their early seminal works1-3.

And these come from the much earlier finding by Van Den Top that AgRP neurones fire in such bursting patterns following activation by ghrelin4. So, for experiments involving AgRP neurones, this stimulation paradigm does make sense, as it closely mimics normal physiological activity in the activated state.

A concerning pattern

However, I have noticed a collaborator who uses a similar stimulation pattern, but at even higher frequencies (30 Hz pulsed 1 second on, 3 seconds off). My problem with this begins with the fact that I have recorded from his neuronal population of interest, and they do not fire in such bursts (I have told him this).

Even more concerning, is the question as to whether those neurones are even capable of firing at 30 Hz. It might seem like I’m being overly dramatic, but this is a genuine concern; some neurones are capable of firing much faster, like 100 Hz, but many are not. And there is an even deeper concern, which is that if you overstimulate a neurone, you can drive it so depolarised that it is incapable of generating an action potential – in essence you silence the neurone.

Optogenetic frequency validation

The potential to optogenetically silence neurones was well shown by Lin et al.5, who compared various opsins including our perennial favourite, ChR2(h134r) (Figure 1). They found that at 25 Hz, ChR2(h134r) only has about 25-50 % fidelity, depending on the light irradiance.

But why is this? You need to take into account the time it takes for the opsin to close after light off, which is 18 ms for ChR2(h134r). And this leaves very little time for the neurone to recover at a high optogenetics stimulation frequency. It should be noted, as well, that Lin et al. used very short stimulation times of 0.5 ms, whereas most people use 10 ms in vivo. This means that if you were to stimulate at 30 Hz with 10 ms on time (as my colleague did), you have 23 ms of light off between each flash.

You then have to take into account an 18 ms delay for the ChR2 to close, and that gives 5 ms for neuronal recovery for the next action potential. My point here is not to bash on my colleague, but rather to stress the importance of optimising your stimulation protocol, and in particular not to overdo the irradiance and high frequency stimulation.

How to determine optimal stimulation protocol

For me, there are three factors to consider when planning your optimal stimulation protocol:

  • How do these neurones normally fire when activated? Trying to mimic as closely as possible the natural firing dynamics of your neurones of interest is, in my opinion, the best way to go. This is probably best done by current clamp patching of identified neurones and then applying something to activate them eg. applying ghrelin to AgRP neurones.
  • How fast can you drive electrical behaviour in these neurones? For this, I would patch clamp your opsin-expressing neurones, and then apply light pulses to the soma. This way you can determine likely irradiance power needed, as well as the electrical responsivity and action potential fidelity. This is particularly important if you intend to drive high frequency firing, as you need to know that your neurones are capable of keeping up.
  • Finally, test a range of firing frequencies (including pulse paradigms if relevant) in vivo against a known behavioural response. For my studies and for AgRP studies, it is simple to measure food intake; this lets you test how your predicted stimulation paradigm works in vivo, as well as confirm your current experiment is working eg. virus transfection and optic fibre placements are good.

Hopefully people will find this useful, if only as a reminder to test your optogenetics stimulation frequency, and not to just go for the brightest and fastest possible stim.

1. Aponte et al., Nature Neurosci 14(3) 351-355 (2011) AGRP neurons are sufficient to orchestrate feeding behavior rapidly and without training.

2. Atasoy et al., Nature 488, 172-177 (2012) Deconstruction of a neural circuit for hunger.

3. Betley et al., Cell 155, 1337-1350 (2013) Parallel, redundant circuit organisation for homeostatic control of feeding behaviour.

4. Van den Top et al., Nat Neurosci 7, 493-494 (2004) Orexigen-sensitive NPY/AgRP pacemaker neurons in the hypothalamic arcuate nucleus.

5. Lin et al., Biophysical J 96, 1803-1814 (2009) Characterization of engineered channelrhodopsin variants with improved properties and kinetics.

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