Advances in functional neuroanatomy: A review of combined DTI and fMRI studies in healthy younger and older adults

Abstract

Structural connections between brain regions are thought to influence neural processing within those regions. It follows that alterations to the quality of structural connections should influence the magnitude of neural activity. The quality of structural connections may also be expected to differentially influence activity in directly versus indirectly connected brain regions. To test these predictions, we reviewed studies that combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) in younger and older adults. By surveying studies that examined relationships between DTI measures of white matter integrity and fMRI measures of neural activity, we identified variables that accounted for variability in these relationships. Results revealed that relationships between white matter integrity and neural activity varied with (1) aging (i.e., positive and negative DTI-fMRI relationships in younger and older adults, respectively) and (2) spatial proximity of the neural measures (i.e., positive and negative DTI-fMRI relationships when neural measures were extracted from adjacent and non-adjacent brain regions, respectively). Together, the studies reviewed here provided support for both of our predictions.

Brain Connectivity and Visual Attention

“…In a review of recent studies that have taken a multi-modal approach, Bennett and Rypma (2013) have proposed that the relation between structural brain integrity and functional activation may differ qualitatively with age, reflecting neural efficiency in the case of younger adults but neural compensation in the case of older adults (cf. Davis et al, 2012).…”

“…Some degree of decreased connectivity occurs during the course of normal aging, although the pattern associated with aging may not directly mirror the child developmental pattern, and increased connectivity within and between network components, with age, also occurs (Andrews-Hanna et al, 2007;Biswal et al, 2010;Tomasi and Volkow, 2012). Understanding the basis for age-related differences in connectivity of attentional networks will require multi-modal studies that combine behavioral measures of attention with structural and functional indices of brain connectivity (Bennett and Rypma, 2013;Davis et al, 2012;Madden et al, 2012;Salat, 2011).…”

“…We consider the potential contribution of diffusion tensor imaging (DTI) of cerebral white matter, in particular, to define the anatomical properties of the white matter pathways that are relevant for cortical networks of attention. In addition, the concept of disconnection among these network components has long been applied to the interpretation of neurological disorders (Catani and ffytche, 2005;Geschwind, 1965aGeschwind, , 1965b, and, more recently, to the interpretation of developmental differences (Bartzokis, 2004;Bartzokis et al, 2004;Bennett and Rypma, 2013;Buckner et al, 2008;Carmichael and Lockhart, 2012;Madden et al, 2010Madden et al, , 2012Salat, 2011;Stevens et al, 2009b). Thus, we propose that the connectivity of attentional networks may vary systematically, across individuals, in a manner that will be informative for understanding human development and the effects of brain injury and disease.…”

Frontostriatal anatomical connections predict age- and difficulty-related differences in reinforcement learning

“…Although this allowed us to assess stable differences in structural connectivity, future studies should assess the relation between the same frontostriatal functional connections and learning performance (Bennett and Rypma, 2013;Messé et al, 2014). To estimate structural connectivity, we applied probabilistic tractography to diffusion-weighted MRI scans.…”

Real-time measurement and correction of both B0 changes and subject motion in diffusion tensor imaging using a double volumetric navigated (DvNav) sequence

“…Applications of DTI include studies of brain maturation (Hasan et al, 2011; Miller et al, 2003; Mukherjee et al, 2001; Qiu et al, 2008; Schmithorst et al, 2002; Snook et al, 2005), white matter (WM) disorders (Engelbrecht et al, 2002; Noriuchi et al, 2010; Pavuluri et al, 2009), and functional and structural connectivity (Behrens et al, 2003; Bennett and Rypma, 2013; Itahashi et al, 2015; Staempfli et al, 2008). …”