In this issue, I discuss three recent papers on axons. The first one is a review on recent findings about the molecular organization of the axon, in particular its periodic organization observed thanks to super-resolution microscopy. The second one examines spike conduction in axons using a high-density electrode array, which seems to be a very interesting source of data. The third one is a new paper on plasticity of the axon initial segment. This time it is the blocking of a Kv channel that triggers the displacement of the AIS, accompanied (but in my view not caused) by homeostatic change in excitability.
The fourth paper is epistemological, and argues that we should abandon statistical significance in favor of more informative measures, rather than try to fix it with lower p-values.
This is a very interesting review on recent discoveries about the axonal cytoskeleton, which have been made possible in particular by super-resolution microscopy. One of these discoveries is the actin rings that are periodically spaced along the axon. The roles of these rings are not entirely clear, but probably mechanical robustness is one of them. As channels attach to the cytoskeleton, one also wonders whether these periodic rings might also be involved in the regulation of channel density.
2. Radivojevic M, Franke F, Altermatt M, Müller J, Hierlemann A, Bakkum DJ (2017). Tracking individual action potentials throughout mammalian axonal arbors. (Comment on Pubpeer)
This study uses a high-density multielectrode array (MEA) to analyze the propagation of an action potential in the axon of cultured neurons. The device has 11011 electrodes, and can record 126 simultaneously. The authors trigger a spike extracellularly, then record the spike-triggered response many times with different electrode configurations to get the entire response of the MEA, which makes it a very interesting set of data. Normally a single electrode signal is not sufficient to record axonal spikes in a single trial, but the trick is to increase the signal-to-noise ratio by using several electrodes to detect spikes (the SNR increases as the square root of the number of electrodes). This is done using template matching. This allows the authors to measure propagation velocity and jitter not just between two points, as was previously done, but all along the axon. Although it’s not commented, it is interesting to see for example that velocity is apparently not constant, it looks as if there are sorts of jumps (plateaus in Fig. 4f). As expected, the jitter in spike time increases with distance from initiation site. A simple model, used by the authors, predicts indeed that variance increases linearly with distance (by assuming that each axonal compartment introduces an independent noise). However, it is hard to say whether the data follow this model, because no alternative model is tested. Here is one: as the authors later show, conduction velocity depends on previous history (slowing down at high firing rate); if there is jitter in conduction velocity, then variance should grow quadratically with distance. By the way there is a small error in the reporting of jitter: it should be in s/m^(1/2) (because variance is in s^2/m, according to the authors’ model), not s/m. Finally, the authors show that spikes slow down at high rate; something which was known before but not with this level of detail. The authors mention a few possible mechanisms; I would add inactivation of Nav channels.
3. Lezmy J, Lipinsky M, Khrapunsky Y, Patrich E, Shalom L, Peretz A, Fleidervish IA, Attali B (2017). M-current inhibition rapidly induces a unique CK2-dependent plasticity of the axon initial segment. (Comment on PubPeer)
Recent studies have shown that the axon initial segment (AIS) can move, extend or shrink in response to various treatments. Here the authors show that inhibiting the M-current (a hyperpolarizing K+ current) induces a distal shift of the AIS together with changes in excitability. There are several interesting findings in this study. First, blocking the current immediately depolarizes the neuron and increases the input resistance, which logically reduces the rheobase (threshold current). But then these parameters go back to their initial values over an hour or so, although the M-current is still blocked, so some compensation occurred. Concurrently, the AIS shifts distally (first the Nav and Kv channels together, then the ankyrin-G); the initiation site shifts accordingly. Finally they show that the relocation is blocked by inhibiting CK2. The authors use a model to support their interpretation that the distal shift of the AIS causes the compensatory reduction in excitability. The model shows two effects that I showed theoretically in my 2013 paper (Brette (2013) Sharpness of spike initiation in neurons explained by compartmentalization): 1) if only Nav channels are considered, moving the AIS distally actually increases excitability (lowers threshold); 2) if there is hyperpolarizing current in the AIS, the opposite effect is seen (this is in my supplementary methods). Thus the authors propose that (2) is happening. However, in my view the data in Fig. 5C support a different interpretation. What is seen there is quite surprising: when the M-current is blocked, the spike threshold does not change at all, and then after a couple of hours the spike threshold lowers. This explicitly supports (1) and contradicts (2). If the threshold doesn’t change when the M-current is blocked, then that means that this current doesn’t actually hyperpolarize the AIS relative to the soma. If the effect that the authors propose underlied the reduction in excitability, then the spike threshold should increase, not decrease. Thus it seems that the distal movement of the AIS actually increases excitability, but something else (expression/phosphorylation of another channel?) reduces it.
Recently, there has a been a lot of discussion about issues of reproducibility in the biomedical and psychological literature. Some people argue that the threshold for statistical signifance should be lowered, say p = 0.01 instead of 0.05. This paper argues, and in my opinion rightly so, that the use of statistical signifance should be abandoned. One of the main arguments, which I also defended in a blog post, is that the null hypothesis is not credible. When any manipulation on a living being is performed, it is unrealistic to hypothesize that the effect will be exactly 0. It might be small, yes, but not exactly zero. And if it’s not zero, then with a sufficient number of observations there is 100% probability that you find a statistically significant effect, whatever threshold you use. The term “significance” is misleading; a ridiculously small effect would still be statistically significant, provided enough observations. It doesn’t prove much, apart from the fact that you are ready to sacrifice hundreds of animals just to get published by glamour journals. Conversely, finding that something is not significant means literally nothing: it could be that you just haven’t repeated the experiment a sufficient number of times – in fact it must be this interpretation, given that the null hypothesis is not realistic. So, I agree with the authors that statistical significance should be abandoned, in favor of more meaningful statistical measures (for example effect size).