Mu suppression and the mirror neurons

A few decades ago, Italian researchers from the University of Parma discovered some neurons in monkey which were active not only when the monkey is performing an action, but also when watching the same action performed by someone else. This kind of neuron, or rather this particular neuronal behavior, had been subsequently identified in humans scattered mainly within the frontal and parietal cortices (front and top of your head) and called the mirror neuron system (MNS). Its role is to understand the intentions of others and thus facilitate learning. Mind you, there are, as it should be in any healthy vigorous scientific endeavor, those who challenge this role and even the existence of MNS.

Hobson & Bishop (2016) do not question the existence of the mirror neurons or their roles, but something else. You see, proper understanding of intentions, actions and emotions of others is severely impaired in autism or some schizophrenias. Correspondingly, there have been reports saying that the MNS function is abnormal in these disorders. So if we can manipulate the neurons that help us understanding others, then we may be able to study the neurons better, and – who knows? – maybe even ‘switch them on’ and ‘off’ when needed (Ha! That’s a scary thought!).

Human EEG waves (from Wikipedia, under CC BY-SA 3.0 license)

Anyway, previous work said that recording a weak Mu frequency in the brain regions with mirror neurons show that these neurons are active. This frequency (between 8-13 Hz) is recorded through electroencephalography (EEG). The assumption is as follows: when resting, neurons fire synchronously; when busy, they fire each to its own, so they desynchronize, which leads to a reduction in the Mu intensity.

All well and good, but there is a problem. There is another frequency that overlaps with the Mu frequency and that is the Alpha band. Alpha activity is highest when a person is awake with eyes closed, but diminishes when the person is drowsy or, importantly, when making a mental effort, like paying great attention to something. So, if I see a weak Mu/Alpha frequency when the subject is watching someone grabbing a pencil, is that because the mirror neurons are active or because he’s sleepy? There are a few gimmicks to disentangle between the two, from the setup of the experiment in such a way that it requires same attention demand over tasks to the careful localization of the origin of the two waves (Mu is said to arise from sensoriomotor regions, whereas Alpha comes from more posterior regions).

But Hobson & Bishop (2016) argue that this disentangling is more difficult than previously thought by carrying out a series of experiments where they varied the baseline, in such a way that some were more attentionally demanding than others. After carefully analyzing various EEG waves and electrodes positions in these conditions, they conclude that “mu suppression can be used to index the human MNS, but the effect is weak and unreliable and easily confounded with alpha suppression“.

87mu - Copy

What makes this paper interesting to me, besides its empirical findings, is the way the experiment was conducted and published. This is a true hypothesis driven study, following the scientific method step by step, a credit to us all scientists. In other words, a rare gem.  A lot of other papers are trying to make a pretty story from crappy data or weave some story about the results as if that’s what they went for all along when in fact they did a bunch of stuff and chose what looked good on paper.

Let me explain. As a consequence of the incredible pressure put on researchers to publish or perish (which, believe me, is more than just a metaphor, your livelihood and career depend on it), there is an alarming increase in bad papers, which means

  • papers with inappropriate statistical analyses (p threshold curse, lack of multiple comparisons corrections, like the one brilliantly exposed here),
  • papers with huge databases in which some correlations are bound to appear by chance alone and are presented as meaningful (p-hacking or data fishing),
  • papers without enough data to make a meaningful conclusion (lack of statistical power),
  • papers that report only good-looking results (only positive results required by journals),
  • papers that seek only to provide data to reinforce previously held beliefs (confirmation bias)
  • and so on.

For these reasons (and more), there is a high rate of rejection of papers submitted to journals (about 90%), which means more than just a lack of publication in a good journal; it means wasted time, money and resources, shattered career prospects for the grad students who did the experiments and threatened job security for everybody involved, not to mention a promotion of distrust of science and a disservice to the scientific endeavor in general. So some journals, like Cortex, are moving toward a system called Registered Report, which asks for the rationale and the plan of the experiment before this is conducted, which should protect against many of the above-mentioned plagues. If the plan is approved, the chances to get the results published in that journal are 90%.

This is one of those Registered Report papers. Good for you, Hobson & Bishop!

Reference: Hobson HM & Bishop DVM (Epub April 2016). Mu suppression – A good measure of the human mirror neuron system?. Cortex, doi: 10.1016/j.cortex.2016.03.019 ARTICLE | FREE FULLTEXT PDF | RAW DATA

By Neuronicus, 14 July 2016