Our results show robust brain-behavior associations in infancy using DTI and a simple assessment of visuospatial working memory. Infants’ performance on this task is predictive of widespread white matter microstructure in major association, projection, and callosal fibers that connect frontal, parietal, and temporal regions of the brain. Better working memory scores were associated with higher FA and lower RD values suggesting that infants with better working memory potentially have more advanced white matter maturation, characterized by increased myelination. This interpretation of the findings is consistent with the developmental stage of the infants in the current study, given that the brain is still undergoing rapid, widespread myelination at 12 months of age. Working memory performance associations were not observed with most control tracts or with global measures of brain volume, which suggests greater specificity of the identified associations between working memory and the selected white matter tracts. Interestingly, white matter microstructural characteristics were rarely associated with infants’ age or other tests of general and specific cognitive ability. The lack of association between these standard measures of infant physical and cognitive development highlights the utility of this working memory assessment, as a predictor of widespread white matter microstructure in infancy.
Multiple neurobiological factors can affect the diffusion of water molecules across a given tract, including axon compaction and diameter, crossing fibers, and, importantly for this study, myelination (Beaulieu, 2002
; Mukherjee and McKinstry, 2006
). Because FA is simply an index of directional diffusion, we are primarily interested in the association between RD and working memory, as RD is more proximal to the neuroanatomical processes. RD represents an index of the diffusion of water molecules perpendicular to the fiber bundle, which is thought to provide an index of myelination (Zhang et al., 2009
; Song et al., 2003
). While it is unclear which neuroanatomical properties drive changes in RD across the life span, at 12-months of age, the brain is still undergoing a rapid phase of myelination (Brody et al., 1987
; Kinney et al., 1988
; Yakovlev and LeCours, 1967
), thus we consider myelin content and the myelination process as one plausible explanation for the strong associations found between infants’ working memory scores and RD values.
Although we found robust relationships between infants’ cognitive function and RD, it is yet to be determined whether early patterns of white matter microstructure are predictive of later myelination or of cognitive function (Fields, 2011
). Recent results from our lab (Geng et al., 2012a
) however suggest that the health and organization of early white matter connections at one-year of age may determine the structural integrity of white matter connections at two-years of age. It is well known that the health and integrity of white matter is critical for functions of both the peripheral and central nervous systems. There is increasing evidence showing the integrity of white matter fibers, as measured with DTI, contributes to behavioral and cognitive functioning across the lifespan. Moreover, the use of DTI in developmental and psychiatric research is rapidly extending our knowledge of the white matter characteristics associated with physical abilities and cognitive functions (Catani et al., 2007
; Liston et al., 2006
; Hu et al., 2011
; Karlsgodt et al., 2008
; Nagy et al., 2004
; Penke et al., 2010
). To date, however there are few studies of infant white matter that have used DTI and deterministic tractography and even fewer studies that have also investigated the resulting microstructural characteristics in association with infant performance or cognition (Dubois et al., 2008
; Niogi et al., 2010
; Wolff et al., 2012
). If early developmental patterns of white matter microstructure can be shown to predict later structural and functional health of the brain, these early brain-behavior associations will be an important step toward identifying weaknesses in neural connections at a time when the brain is potentially more amenable to intervention. Such findings could lead to the development of targeted intervention strategies to strengthen foundational cognitive capacities, such as working memory, since the formation of other cognitive functions critically depends on working memory (Baddeley, 2003
Working memory has been considered the ‘information processing gate-keeper’ and the ‘workbench of cognition’ and thus plays a privileged role in the development of adaptive cognitive functions (D’Esposito, 2007
; Kane and Engle, 2002
). Working memory capacity has a pervasive influence over cognitive and social-cognitive competencies, including decision-making, planning, cognitive flexibility, reasoning, and emotion regulation (Goldman-Rakic, 1995
; Baddeley, 2003
). Moreover, visuospatial working memory capacity has been shown to be more closely related to general fluid intelligence than any of the other early developing cognitive domains (Kane and Engle, 2002
). Future studies will be needed to confirm the reported findings and to identify which other white matter connections are important to working memory and how they function as networks and how this changes from infancy to late childhood. Identifying and understanding the putative neural circuitry associated with working memory has implications for understanding typical and atypical cognitive development.
Considering the experience-dependent plasticity of both white matter and working memory demonstrated in school-age children and adults (Klingberg, 2010
; Olesen et al., 2003
; Scholz et al., 2009
; Takeuchi et al., 2010
; Zatorre et al., 2012
), evidence from the current report suggests intriguing possibilities for identifying developmental periods that are optimal for strengthening children’s working memory capacity. Deficits in working memory are a core feature of ADHD and schizophrenia. Implementing working memory training interventions during optimal periods of developmental plasticity could potentially ameliorate cognitive deficits common to these and other neurodevelopmental and neuropsychiatric disorders (Jaeggi et al., 2008
; Hagmann et al., 2010
; Holtmaat and Svoboda, 2009
). Although additional studies are needed to answer fundamental questions about the nature of the interactions between experience-dependent and experience-expectant developmental processes (Johnson, 2001
), characterizing the underlying white matter microstructure associated with working memory in infancy provides the groundwork for subsequent longitudinal examinations of these relations.
Results from our mixed regression model, controlling for twin-status, showed an unexpected association between working memory scores and a control tract, the left spinothalamic radiation. However, this result largely disappeared when the sample size was reduced and the methodology changed (i.e., removal twin pairs, n = 12) for the correlational analyses. See and section 2.11 in Methods. That this association did not survive the slight perturbation in the dataset and analysis method might suggest that the correlation was spurious to begin with. Although correlations were slightly reduced for the associations between infants’ working memory scores and the putative working memory tracts, the general pattern of results and strength of associations remained significant and stable, despite the loss of one twin from each twin pair. The other control tract associated with working memory was the corpus callosum body. This finding may not be surprising given the number of brain regions connected by the body of the corpus callosum which also shares a high degree of overlap with regions known to support working memory that are represented with our hypothesized tracts. Our interpretation of this finding is that infants’ working memory scores are associated with widespread white matter connections and as such the specificity of these associations will need to be further characterized in future studies.
Consideration should be given to the following study limitations. First, although several white matter tracts were associated with infants’ performance, it is likely that additional white matter tracts support working memory in infancy. Thus, future studies of brain-behavior associations should include tract-based spatial statistics to explore brain-wide relationships with white matter (Smith et al., 2006
). Second, additional properties of white matter microstructure such as crossing fibers, changes in axonal packing, and even partial volume effects could influence the diffusion of water molecules indexed by FA, RD, and AD (Huppi and Dubois, 2006
; Mori and Zhang, 2006
; Hermoye, 2006
; Mori and van Zijl, 2002
; Concha et al., 2010
), and this restricts the interpretation of findings. However, a recent study found that autism is associated with abnormalities of white matter development between the ages of 6 and 24 months (Wolff et al., 2012
), suggesting that trajectories of white matter microstructural characteristics measured with DTI have the potential to predict complex behavioral patterns. Finally, children who completed at least 8 of 12 working memory trials were included in this study. It is therefore possible that the white matter microstructure differs in those infants who were excluded from the study on the basis of incomplete data, although the working memory performance of infants included in this study ranged widely (from 33-100% correct) and appeared normally distributed. Factors mediating the current brain-behavior associations are likely to be multiplicative and result from genetic and environmental influences. We did not investigate mediating factors in the current study; future research will be needed to identify mediating factors of white matter maturation and infant learning. More broadly however, the current study does contribute to ongoing efforts to identify early biomarkers and determinants of long-term health and disease.
In summary, using quantitative tractography, this study found robust relationships between infants’ working memory and microstructural characteristics of widespread white matter. Significant associations were found for white matter tracts that connect brain regions known to support working memory in older children and adults. Better working memory scores were significantly associated with higher FA and lower RD values in these selected white matter tracts. These strong tract-specific brain-behavior relationships accounted for a significant amount of individual variation above and beyond infants’ gestational age and developmental level, as measured with the Mullen Scales of Early Learning.
Future studies will be needed to determine the predictive utility of white matter microstructural characteristics in the infant brain. It is possible that this brain-behavior association resulted from a more rapid developmental trajectory for those infants with better working memory performance and that those infants with poorer performance will catch up over time. Thus, it remains to be seen whether this early brain-behavior association predicts long-term advantages in working memory capacity or other cognitive domains. Our future research will investigate the predictive power of these early brain-behavior relationships as we continue to work with these children that are enrolled in our large longitudinal studies of early brain and behavioral development. Likewise, it will be important to identify genetic and environmental factors that contribute to these individual differences in white matter fiber bundles. We will also address genetic and environmental factors following subsequent assessments of the participants in our large-scale, longitudinal study of brain development in children.