There is a long-standing interest in the determinants of successful learning in children. “Grit” is an individual trait, reflecting the ability to pursue long-term goals despite temporary setbacks. Although grit is known to be predictive of future success in real-world learning situations, an understanding of the underlying neural basis and mechanisms is still lacking. Here we show that grit in a sample of 6-year-old children ( n = 55) predicts the working memory improvement during 8 weeks of training on working memory tasks ( p = .009). In a separate neuroimaging analysis performed on a partially overlapping sample ( n = 27), we show that interindividual differences in grit were associated with differences in the volume of nucleus accumbens (peak voxel p = .021, x = 12, y = 11, z = −11). This was also confirmed in a leave-one-out analysis of gray matter density in the nucleus accumbens ( p = .018). The results can be related to previous animal research showing the role of the nucleus accumbens to search out rewards regardless of delays or obstacles. The results provide a putative neural basis for grit and could contribute a cross-disciplinary connection of animal neuroscience to child psychology.

Limitations in the performance of working memory (WM) tasks have been characterized in terms of the number of items retained (capacity) and in terms of the precision with which the information is retained. The neural mechanisms behind these limitations are still unclear. Here we used a biological constrained computational model to study the capacity and precision of visuospatial WM. The model consists of two connected networks of spiking neurons. One network is responsible for storage of information. The other provides a nonselective excitatory input to the storage network. Simulations showed that this excitation boost could temporarily increase storage capacity but also predicted that this would be associated with a decrease in precision of the memory. This prediction was subsequently tested in a behavioral (38 participants) and fMRI (22 participants) experiment. The behavioral results confirmed the trade-off effect, and the fMRI results suggest that a frontal region might be engaged in the trial-by-trial control of WM performance. The average effects were small, but individuals differed in the amount of trade-off, and these differences correlated with the frontal activation. These results support a two-module model of WM where performance is determined both by storage capacity and by top–down influence, which can vary on a trial-by-trial basis, affecting both the capacity and precision of WM.

Studying the effects of cognitive training can lead to finding better treatments, but it can also be a tool for investigating factors important for brain plasticity and acquisition of cognitive skills. In this study, we investigated how single-nucleotide polymorphisms (SNPs) and ratings of intrinsic motivation were associated to interindividual differences in improvement during working memory training. The study included 256 children aged 7–19 years who were genotyped for 13 SNPs within or near eight candidate genes previously implicated in learning: COMT , SLC6A3 (DAT1) , DRD4 , DRD2 , PPP1R1B (DARPP32) , MAOA , LMX1A , and BDNF . Ratings on the intrinsic motivation inventory were also available for 156 of these children. All participants performed at least 20 sessions of working memory training, and performance during the training was logged and used as the outcome variable. We found that two SNPs, rs1800497 and rs2283265, located near and within the dopamine receptor 2 ( DRD2 ) gene, respectively, were significantly associated with improvements during training ( p < .003 and p < .0004, respectively). Scores from a questionnaire regarding intrinsic motivation did not correlate with training outcome. However, we observed both the main effect of genotype at those two loci as well as the interaction between genotypes and ratings of intrinsic motivation (perceived competence). Both SNPs have previously been shown to affect DRD2 receptor density primarily in the BG. Our results suggest that genetic variation is accounting for some interindividual differences in how children acquire cognitive skills and that part of this effect is also seen on intrinsic motivation. Moreover, they suggest that dopamine D2 transmission in the BG is a key factor for cognitive plasticity.

The cellular maturational processes behind cognitive development during childhood, including the development of working memory capacity, are still unknown. By using the most standard computational model of visuospatial working memory, we investigated the consequences of cellular maturational processes, including myelination, synaptic strengthening, and synaptic pruning, on working memory-related brain activity and performance. We implemented five structural developmental changes occurring as a result of the cellular maturational processes in the biophysically based computational network model. The developmental changes in memory activity predicted from the simulations of the model were then compared to brain activity measured with functional magnetic resonance imaging in children and adults. We found that networks with stronger fronto-parietal synaptic connectivity between cells coding for similar stimuli, but not those with faster conduction, stronger connectivity within a region, or increased coding specificity, predict measured developmental increases in both working memory-related brain activity and in correlations of activity between regions. Stronger fronto-parietal synaptic connectivity between cells coding for similar stimuli was thus the only developmental process that accounted for the observed changes in brain activity associated with development of working memory during childhood.

In the human brain, myelination of axons continues until early adulthood and is thought to be important for the development of cognitive functions during childhood. We used diffusion tensor MR imaging and calculated fractional anisotropy, an indicator of myelination and axonal thickness, in children aged between 8 and 18 years. Development of working memory capacity was positively correlated with fractional anisotropy in two regions in the left frontal lobe, including a region between the superior frontal and parietal cortices. Reading ability, on the other hand, was only correlated with fractional anisotropy in the left temporal lobe, in the same white matter region where adults with reading disability are known to have lower fractional anisotropy. Both the temporal and the frontal regions were also correlated with age. These results show that maturation of white matter is an important part of brain maturation during childhood, and that maturation of relatively restricted regions of white matter is correlated with development of specific cognitive functions.

The aim of this study was to identify changes in brain activity associated with the increase in working memory (WM) capacity that occurs during childhood and early adulthood. Functional MRI (fMRI) was used to measure brain activity in subjects between 9 and 18 years of age while they performed a visuospatial WM task and a baseline task. During performance of the WM task, the older children showed higher activation of cortex in the superior frontal and intraparietal cortex than the younger children did. A second analysis found that WM capacity was significantly correlated with brain activity in the same regions. These frontal and parietal areas are known to be involved in the control of attention and spatial WM. The development of the functionality in these areas may play an important role in cognitive development during childhood.