In this study, we sought to test whether three months of reasoning training altered white matter microstructure. While we found no changes in white matter volume, we observed training-related changes in diffusion parameters within white matter. Indeed, our results show that reasoning training led to decreased RD in white matter connecting frontal cortices, and decreased in MD in white matter underlying left frontal and right parietal cortices. These experience-dependent changes fall into tracts that would be predicted by prior work showing that reasoning relies on an interhemispheric frontoparietal network (for review, see Prado et al., 2011
). Our findings are also consistent with the view that reasoning is largely left-hemisphere dominent (e.g., Krawczyk, 2012
), but that homologous cortex in the right hemisphere can be recruited as needed to support complex reasoning. Perhaps learning to reason more efficiently involves recruiting compensatory neural circuitry more consistently.
Relationships between diffusion changes and LSAT changes were not particularly robust, perhaps because neuroplastic changes were driven by experience shared across individuals. We found an unpredicted negative correlation between change in MD and improvement on the LSAT in the retrolenticular part of the right internal capsule (white matter that interconnects posterior cortices and thalamus) as well as corticopontine fibers originating in the right parietal lobe (Nolte, 2009
). Future research with a larger sample size will be needed to determine whether these brain-behavior correlations are replicable, and whether there are any additional statistically significant relationships between diffusion change and reasoning improvement.
The results featured here meet a more conservative criterion than several prior training studies, in that changes in the trained group needed to surpass changes in the control group to be considered significant. The participants in our study were, on average, in their early twenties, and developmental changes in white matter are known to occur during this age range (Lebel et al., 2008
). Additionally, both groups consisted largely of university students, and their academic experiences over the course of 3 months alone could have altered their white matter microstructure. Thus, changes that were significantly greater in the trained group than in a well-matched control group provide strong evidence for experience-dependent plasticity, and not simply maturational changes.
An active control group is often preferable to a passive control group in training studies, because it controls for general factors like beliefs about how much one is learning or improving on a task. For this study, however, selecting an appropriate active control group for this study would have been difficult as most adults would not choose to spend 100 hours over 3 months training on a skill that is not directly relevant to their life goals. Had we administered an artificial active control training program in the lab, differences between groups in neuroanatomical changes could have been confounded by differences in levels of motivation and attention. Alternatively, if our control group had consisted of individuals enrolled in a different professional training course, such as the Medical College Admission Test (MCAT), we might have encountered initial group differences based on differences in interests, coursework, and experiences that would predispose students to seek admission to one professional program over another.
In this paper, we have examined changes in four measures of diffusion. On the one hand, this broad approach introduces a multiple comparison problem that would not exist if we had simply investigated changes in a single measure. On the other hand, if we had only looked at one measure, we would have painted a limited picture of white matter plasticity. Further, we did not have strong reason to believe that one index of white matter microstructure was more important or more likely to change with training than the others.
It is important to recognize that a tract defined by an atlas does not necessarily reflect an individual's anatomical tract. Rather, it reflects where tracts lie on average across individuals. At the current resolution, it is not possible to determine whether any given voxel contains axons connecting, for example, bilateral motor cortices or frontal and parietal cortices. Advances in diffusion imaging, such as diffusion spectral imaging (DSI), may make it possible to better classify the principal direction(s) of each voxel that shows a quantified change in diffusion. However, these sequences have yet to be used in the context of research on neuroplasticity. As the required scan time for advanced diffusion imaging pulse sequences decreases, and as scanners employ stronger gradients, it should become feasible to include more sensitive measures of white matter microstructure in studies of neuroplasticity that involve multiple structural and functional brain scans.
Even with advances in imaging methodology that make it possible to determine the direction of diffusion precisely, the study of white matter plasticity in humans will still be limited by the scale at which we can observe neuroanatomical changes. The cellular basis for training-induced changes in diffusion in humans is and will remain unclear, at least for the foreseeable future, though it is possible to speculate about potential mechanisms based on plasticity observed in animals (see Zatorre et al., 2012
Studies in animals have shown that both decreased RD and increased FA are related to increased myelination (Vorisek and Sykova, 1997
; Zhang et al., 2009
; Blumenfeld-Katzir et al., 2011
). It is possible, then, that the experience-dependent decreases in RD (and increases in FA) that we observed were driven by myelination, especially because they tended to be in highly directional, heavily myelinated tracts. However, it is important to note that while myelin does affect diffusion (Mottershead et al., 2003
; Concha et al., 2010
), unmyelinated axon membranes do as well (Partridge et al., 2004
), and myelin volume and axon counts are very highly correlated (Schmierer et al., 2007
; Concha et al., 2010
). Therefore, the extent to which axonal cell membranes also constrain diffusion is unclear.
Decreased MD, on the other hand, has been related to proliferation and/or growth of astrocytes (Blumenfeld et al., 2006
; Sagi et al., 2012
). A reduction in MD could additionally or alternatively reflect the myelination of axons traveling in multiple directions. It is therefore intriguing that we observed decreased MD near cortex, and also in white matter that was not highly directional and therefore could contain crossing fibers. Hopefully, future research linking changes in cell structure and function to plasticity in large-scale networks will further our understanding of how experience shapes the anatomy of the human brain.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.