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1.  Gray matter volume is associated with rate of subsequent skill learning after a long term training intervention 
Neuroimage  2014;96(100):158-166.
The ability to predict learning performance from brain imaging data has implications for selecting individuals for training or rehabilitation interventions. Here, we used structural MRI to test whether baseline variations in gray matter (GM) volume correlated with subsequent performance after a long-term training of a complex whole-body task. 44 naïve participants were scanned before undertaking daily juggling practice for 6 weeks, following either a high intensity or a low intensity training regime. To assess performance across the training period participants' practice sessions were filmed. Greater GM volume in medial occipito-parietal areas at baseline correlated with steeper learning slopes. We also tested whether practice time or performance outcomes modulated the degree of structural brain change detected between the baseline scan and additional scans performed immediately after training and following a further 4 weeks without training. Participants with better performance had higher increases in GM volume during the period following training (i.e., between scans 2 and 3) in dorsal parietal cortex and M1. When contrasting brain changes between the practice intensity groups, we did not find any straightforward effects of practice time though practice modulated the relationship between performance and GM volume change in dorsolateral prefrontal cortex. These results suggest that practice time and performance modulate the degree of structural brain change evoked by long-term training regimes.
•Inter-individual differences in brain structure correlate with subsequent performance outcome.•Performance outcome plays an important role in positive structural brain change.•Performance outcome and amount of practice modulate structural brain change.
PMCID: PMC4075341  PMID: 24680712
Structural plasticity; Skill learning; MRI
2.  The Effects of Aerobic Activity on Brain Structure 
Aerobic activity is a powerful stimulus for improving mental health and for generating structural changes in the brain. We review the literature documenting these structural changes and explore exactly where in the brain these changes occur as well as the underlying substrates of the changes including neural, glial, and vasculature components. Aerobic activity has been shown to produce different types of changes in the brain. The presence of novel experiences or learning is an especially important component in how these changes are manifest. We also discuss the distinct time courses of structural brain changes with both aerobic activity and learning as well as how these effects might differ in diseased and elderly groups.
PMCID: PMC3311131  PMID: 22470361
exercise; plasticity; hippocampus; neurogenesis; angiogenesis; learning; environmental enrichment; aging
3.  The Organization of Dorsal Frontal Cortex in Humans and Macaques 
The Journal of Neuroscience  2013;33(30):12255-12274.
The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractography-based parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for “new” regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.
PMCID: PMC3744647  PMID: 23884933
4.  Human Structural Plasticity at Record Speed 
Neuron  2012;73(6):1058-1060.
How rapidly does learning shape our brains? A new study using diffusion magnetic resonance imaging in both humans and rats suggests that just two hours of spatial learning is sufficient to change brain structure.
PMCID: PMC3353540  PMID: 22445333
5.  Functional but not structural changes associated with learning: An exploration of longitudinal Voxel-Based Morphometry (VBM) 
NeuroImage  2009;48(1):117-125.
Voxel-Based Morphometry (VBM) has been used for several years to study differences in brain structure between populations. Recently, a longitudinal version of VBM has been used to show changes in gray matter associated with relatively short periods of training. In the present study we use fMRI and three different standard implementations of longitudinal VBM: SPM2, FSL, and SPM5 to assess functional and structural changes associated with a simple learning task. Behavioral and fMRI data clearly showed a significant learning effect. However, initially positive VBM results were found to be inconsistent across minor perturbations of the analysis technique and ultimately proved to be artifactual. When alignment biases were controlled for and recommended statistical procedures were used, no significant changes in grey matter density were found. This work, initially intended to show structural and functional changes with learning, rather demonstrates some of the potential pitfalls of existing longitudinal VBM methods and prescribes that these tools be applied and interpreted with extreme caution.
PMCID: PMC2981435  PMID: 19520171

Results 1-5 (5)