Research Spotlight #2 Moore, E., Schaefer, R., Bastin, M., Roberts, N., & Overy, K. (2017). Diffusion tensor MRI tractography reveals increased fractional anisotropy (FA) in arcuate fasciculus following music-cued motor training. Brain and Cognition, 116, 40-46.
A couple of weeks ago my mum emailed me a link to a BBC news article which she rightly knew would be of interest to me. It reported on a study by researchers mainly from the University of Edinburgh, and the title of the BBC article was: “Learning with music can change brain structure, says study“. This of course grabbed my attention, as I thought it could provide a neuroscientific counterpart to my PhD student John Dyer’s recent work, which had found that triggering a melody with one’s movements helped in learning and recalling a complex bimanual coordination task (tracing a diamond with one hand and a triangle with the other to create a 4:3 rhythm). The study by Moore et al. on which the BBC article was based is indeed interesting, but probably creates more questions than it answers. It also ties in neatly with an ongoing issue in neuroscience – trying to draw conclusions from neural measures when the behavioural framework within which they should fit is incomplete.
The study involved people learning different patterns of finger movements on their left (non-dominant hand), e.g. index-ring-middle-pinkie-ring-index-ring-middle. You can try yourself and see that it is not that easy – hence room for some learning to happen. Everyone in the study learned the task with a kind of Guitar Hero style video to show them which order the fingers had to be pressed. Importantly, one group practiced with just the video (‘control group’), while the other additionally heard musical pitches (presumably like keys on a piano) to indicate the finger order of the sequence to press. This was the key difference between the groups – one had a ‘musical’ version of the task while the other didn’t. They learned the sequences at home, and the task sped up as they got more confident at producing the sequences. They were tested at performing the rehearsed sequences as well as some sequences that they hadn’t rehearsed at three stages: before training, midway through training and after training. MRI scans of their brains were also recorded before and after training. These were used to measure changes in the organisation of fibres which connects neural cells between the auditory and motor regions of the right-hemisphere of the brain (i.e. the side of the brain which would be responsible for sending muscle signals to the left hand). The hypothesis was that learning with the musical sounds may entail greater auditory-motor linkages in the brain hemisphere involved in coordinating the task-to-be-learned.
The results of the study showed that both groups got better at the task, that is, they completed a greater number of correct sequences as a result of training. However, there were no differences in how much the music and control groups improved, that is both groups were getting pretty much the same number of correct sequences by the end of training. This is rightly taken to show that the musical tones did not influence learning (at least in terms of correct sequences). There was also evidence of a training-dependent change in the organisational structure of the axons connecting auditory and motor regions of the brain for the musical group in the right hemisphere, but not in the left hemisphere or at all in the control group. It could be noted that the changes in neural organisation were small (4% change in the main measure, all measures hovering around the 0.05 p-value), but for such a ‘light’ intervention, this may be all the more compelling – if just adding a little music to the task can change the brain, imagine what you could do if you really went to town with musical movement training!
As I said earlier, these results are certainly interesting. The lack of difference in the learning measure between the group, when one might expect the sound to be helpful, points to a need to understand better if and how sound could lead to enhanced learning of the task (e.g. through movement sonification rather than just as a guide). Also, the apparent change in neural fibres in the music group, although small, may represent a fairly surprising amount of neural plasticity in such a short space of time, more than would be expected (although I cannot comment on whether a 4% difference is that surprising or not as I am not up on what counts as small/large changes in neuroplasticity measures).
In spite of these interesting aspects, there are some limitations on what can be taken from this paper and a number of further questions raised. Firstly, it is a shame that the performance of the task was only examined using correct sequences performed. While it is always a good idea to have a primary learning measure, other measures like timing accuracy or movement kinematics may have revealed group differences which would help with understanding what the neural changes correspond to. If the neural changes are not functional for the movements involved, but rather underpin some audio-motor mapping or association which is simultaneously being acquired by the learners, then this might have been examined by looking for disruptions in performance for the music group when an incongruous finger-tone mapping is introduced following training. It is also possible that using movement sonification (fingers trigger the sounds), rather than sounds as mere cues, may have led to enhanced learning for the music group. Each of these additional measures or experimental conditions might have led to observable behavioural effects, through which the neural changes could be interpreted. As it is, however, it cannot be determined yet whether the observed changes in brain have some functional significance, or are merely an artifact, comparable to an indentation in one’s middle finger following a period of intensive handwriting.
To be fair, the authors do acknowledge that the lack of measured learning differences between the two groups limits the conclusions that can be made with regard to the neural data. Nevertheless, they do propose that the study may be valuable for clinical practice, e.g. for movement rehabilitation in Stroke survivors. The mismatch between the excitement over the seeming neural transformation (less in the paper itself but more in its media coverage) and the lack of corresponding behavioural differences between the learning conditions is telling. Recently, a group of pretty eminent neuroscientists published an excellent critique of a trend in the neurosciences to focus disproportionately on the activity and structures of individual neural cells, or networks of cells, without giving due attention to the situated task and behaviour of the organism that such neural activity is supposed to subserve. Studying the properties of stomach acid molecules is supposed to help us understand digestion; studying the brain should help us understand behaviour.
One might ask – if the researchers had carried out the study as a purely behavioural experiment, would they have then been motivated to repeat it with MRI analysis? My guess is that the behavioural component would need to have been more convincing, in which case the cart may be in front of the horse on this one.