Longitudinal DTI Study on Correlation Between Musical Training and Memory Performance
Abstract
This paper aims to explore neural mechanisms of memory, one of the key cognitive abilities, through diffusion tensor imaging (DTI). It posits participants will show different relationship between DTI indices including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and their memory performance, depending on the type of training they received. Accordingly, studying the association between white matter diffusion and memory function will yield insights that could contribute to development of neurobiological indicators of memory enhancement or memory deficits.
Introduction
Effects of musical training on memory performance have been reported in several studies. A meta analysis concluded that musicians performed better than non-musicians on several aspects of memory [1]. In studies of white matter using DTI, musicians and non-musicians showed differences in various brain regions, including the corpus callosum and other related brain regions [2]. However, many brain imaging studies on memory focus on grey matter, with relatively few studies involving white matter, despite of its important role in memory function. DTI technique is a compatible method of investigating white matter changes based on water diffusion within the brain [3]. Thus, I hypothesize that young adults who received musical training for one year, will show higher FA and lower AD and RD in the regions of interest: corpus callosum and fornix, compared to the group of non-music group, as their memory performance increased.
Methods
This research uses data collected from 65 participants (fourty-seven females, mean age: 21.3) who underwent scans at two time points, spaced one year apart. During the intervening year, participants engaged in different types of training programs, such as musical, athletic, and language training. Data was acquired with respect to MR images and memory performance using California Verbal Learning Task (CVLT) and Wechsler Memory Scale (WMS). Data pre-processing has been done utilizing FSL toolbox and statistical analysis using JASP. The analysis will encompass the examination of brain regions of interest that exhibited significant differences in previous studies.
Discussion
Although this research is anticipated to give deeper understanding of the underlying neurological mechanisms of memory function, the current research has several limitations. Firstly, the sample size is relatively small compared to other studies. Furthermore, due to limited time, profound analysis of the given data is difficult. Controlling other potential variables is also challenging, as memory interacts with many cognitive functions. Nevertheless, the study may provide new insights into the effects of music on memory, which has been underrepresented in existing DTI research.
References
[1] A. Criscuolo, V. Pando-Naude, L. Bonetti, P. Vuust, and E. Brattico, “An ALE meta-analytic review of musical expertise,” Sci Rep, vol. 12, no. 1, p. 11726, Jul. 2022, doi: 10.1038/s41598-022-14959-4.
[2] E. Moore, R. Schaefer, M. Bastin, N. Roberts, and K. Overy, “Can Musical Training Influence Brain Connectivity? Evidence from Diffusion Tensor MRI,” Brain Sciences, vol. 4, no. 2, pp. 405–427, Jun. 2014, doi: 10.3390/brainsci4020405.
[3] C. Gaser and G. Schlaug, “Brain Structures Differ between Musicians and Non- Musicians,” J. Neurosci., vol. 23, no. 27, pp. 9240–9245, Oct. 2003, doi: 10.1523/JNEUROSCI.23-27-09240.2003.
