Cristina Cabassi is an honorary research assistant investigating fasciculations in people with MND. In this guest blog she tells us a little about herself and the project she is involved with – SPiQE, which stands for surface potential quantification engine, technology developed to detect activity from a specific type of muscle recording.
I first approached the care of people with MND in 2010 as a student nurse in Italy. I can still recall the face and name of my very first patient today – in fact, the experience was very intense for me. After my degree in nursing my curiosity for the mind and the nervous system led me to continue my studies with a second BSc in Neuroscience at the University of Leeds. During this time, I first used electromyography to study muscle activity in healthy individuals. Towards the end of my MSc in Clinical Neuroscience at King’s College London, I had the opportunity to apply for different research projects. Based on my experiences as a nurse with people with MND, and my previous research utilising electromyography, I applied for a project investigating fasciculations in people with MND with the use of a relatively new electromyographical tool – high-density surface electromyography (HDSEMG). The recordings were analysed with a new analytical pipeline called SPiQE. The project was very encouraging, and I had the opportunity to continue it as honorary research assistant. In the meanwhile, the team utilising SPiQE (the SPiQE team!) has grown further and other fellow young researchers have joined the group and obtained very interesting findings.
This fall in particular has been an incredibly exciting time for the SPiQE team! The first annual meeting took place, virtually, and was a great success. The meeting focused on the brilliant research outputs obtained through the implementations of this new practice. SPiQE is an automated analysis tool that was developed to detect voluntary and spontaneous activity from a specific type of muscle recording known as HDSEMG. In more practical terms, when a recording is taken from a muscle with special sensors (such as HDSEMG ones) the data are transferred to a laptop. From here, the data are analysed with this new tool implemented in MATLAB and it is now possible to automatically differentiate voluntary activity from involuntary activity within the muscle. Involuntary activity includes muscle twitches (also known as fasciculations) which are characteristic of MND. This first meeting gave voice to junior members, and latest additions, of the team and their research efforts in the past year. Here I offer a peek into a couple of fantastic projects that were presented.
Finding differences in normal and abnormal muscle activity
Weng Kit Chan (Kevin) is a fourth-year medical student who last year intercalated with an MSc in Clinical Neuroscience at King’s College London. During his time at King’s, his research focused on finding electrical signatures of damage to upper and lower motor neurons caused by motor neurone disease (MND).
His project has shown that important characteristics of normal muscle activity, recorded by HDSEMG and processed with SPiQE, significantly differ from unintentional muscle activity such as muscle twitches. These characteristics include the firing frequency and the amplitude of the electrical activity recorded. This finding further confirms SPiQE’s ability to differentiate between normal, voluntary activity and potentially abnormal, unintentional muscle activity such as muscle twitches.
Additionally, Kevin manually analysed processed HDSEMG recordings and separated areas of high frequency of discharge in the recordings. Within these areas he looked for electrical signs of disease known to be associated with MND and the damage it causes to lower motor neurons. Interestingly, he was able to identify abnormal spontaneous activities known as fasciculations doublets, triplets and quintuplets (Figure 1). These had never been detected before using SPiQE. This is particularly important because it highlights the potential of adapting SPiQE to find even more abnormal electrophysiological patterns which can be applied in the investigation of a range of other disorders beyond MND.
Finally, this project investigated spasticity of muscles in people affected by MND (as assessed by the Modified Ashworth Scale). Spasticity is stiffness of muscles and results from damage to upper motor neurons. In this study it was found that the muscles that became weak during the study were far more likely to show signs of spasticity compared to muscles that remained strong for the whole length of the study. This finding seems to support the ‘dying-forward hypothesis’ of MND – that is, that the disease originates in the motor cortex of the brain (hence the spasticity first) and then spreads ‘forwards’ due to damage of nerve cells caused by glutamate.
Applying SPiQE to shorter muscle recordings
A second presentation was delivered by Abdi Malik Musa, a fourth-year medical student at the University of Southampton. Abdi also intercalated last year with an MSc in Clinical Neuroscience at King’s College London. His research aimed to look at the effect of shorter recording times on the characteristics of fasciculations such as their frequency and amplitude.
Up until now SPiQE had only been applied to long muscle recordings, usually 30 minutes. These long recordings mean that within a two-hour visit the number of muscles investigated are generally only two.
Abdi’s study tested 5-, 10-, 15-, 20- and 25-minute recording durations and compared these to data derived from the 30-minute recordings. He found that 15-minute recordings were sufficient to obtain fasciculation frequencies that were comparable to 30-minute recordings. Of note, the amplitude of fasciculations was not as accurate in shorter recordings as in the 30-minute recordings. This is probably due to the fact that amplitude is more likely to be affected by electrical interferences.
Interestingly however, the increased interferences were only seen in one of the two muscles studied by Abdi – the bicep – whereas the other muscle seemed not to be affected by this. More specifically, it was noticed that in the bicep, as the recording time increased, the interferences decreased. By contrast, the electrical disturbances in the calf muscle remained similar at every recording time. This might suggest that there are inherent differences in the muscles which need to be considered when evaluating the optimal recording time. For instance, it can be hypothesised it takes more time for people to completely relax the bicep compared to the calf muscle.
Overall, Abdi’s findings are very exciting. In fact, he demonstrated that it is possible to halve the recording time in specific muscles. Shorter recording times are extremely beneficial because they hold the potential of investigating a larger number of muscles at every session. Shorter recording times also expand the usability of this methodology to a wider range of clinical trials and research studies. This means that SPiQE could be considered in the future as a useful methodology to further study MND and it could also be used in clinical trials to determine the effectiveness of new drugs.
All these results, although not comprehensive of all of the findings obtained last year, are extremely fascinating and more studies are needed to further advance SPiQE applications. Next year’s annual meeting will surely be the perfect occasion to catch up on all of the progresses that this new academic year will bring!
We’d like to thank Cristina for sharing her research in this blog post.