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. 2013:4:1373.
doi: 10.1038/ncomms2374.

Dimensionality of brain networks linked to life-long individual differences in self-control

Affiliations

Dimensionality of brain networks linked to life-long individual differences in self-control

Marc G Berman et al. Nat Commun. 2013.

Abstract

The ability to delay gratification in childhood has been linked to positive outcomes in adolescence and adulthood. Here we examine a subsample of participants from a seminal longitudinal study of self-control throughout a subject's life span. Self-control, first studied in children at age 4 years, is now re-examined 40 years later, on a task that required control over the contents of working memory. We examine whether patterns of brain activation on this task can reliably distinguish participants with consistently low and high self-control abilities (low versus high delayers). We find that low delayers recruit significantly higher-dimensional neural networks when performing the task compared with high delayers. High delayers are also more homogeneous as a group in their neural patterns compared with low delayers. From these brain patterns, we can predict with 71% accuracy, whether a participant is a high or low delayer. The present results suggest that dimensionality of neural networks is a biological predictor of self-control abilities.

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Conflict of interest statement

The authors have no competing financial interests to report.

Figures

Fig. 1
Fig. 1. Directed-forgetting task and Activations
(A) Schematic of the working memory directed-forgetting task. The task is composed of 3 trial types: lure, yes, and control trials. Of most interest is the comparison of accuracy and RT for lure vs. control trials. (B) Activation Patterns for the lure – control contrast across all participants. Significant activation is seen in the Left Inferior Frontal Gyrus (LiFG), the Right Inferior Frontal Gyrus (RiFG), the Anterior Cingulate Cortex (ACC)/Superior Frontral Gyrus (sFG), the Caudate, the Precuneus and the Left Inferior Parietal Lobule (LiPL). These images are thresholded at p < .005 uncorrected for 10 contiguous voxels.
Fig. 2
Fig. 2. The optimal number of dimensions to maximize classification accuracy
The number of linear discriminant (LD) dimensions/components that were required to achieve maximum classification between lure and control trials for each subject, with the group averaged data to the far right. High-delay group = red; Low-delay group = blue. Error bars represent standard errors of the mean.
Fig. 3
Fig. 3. Averaged first and second PC for each group
(A) Average PC 1 for High delayers (B) Average PC 1 for Low delayers (C) Average PC 2 for High delayers (D) Average PC 2 for Low delayers
Fig. 4
Fig. 4. The Euclidean distances for each individual participant’s LD map from their group mean LD map
High-delay group = red; Low-delay group = blue. Error bars represent standard errors of the mean.
Fig. 5
Fig. 5. MDS results for the first 3 dimensions of the LD map distance matrix
The high (red) delayers are grouped together more closely than the low delayers (blue).
Fig. 6
Fig. 6. QD sensitivity map for classifying high- vs. low-delayers’ LD Maps
Areas in blue represent voxels that are higher in low-delayers’ maps. Areas in orange/yellow represent voxels that are higher in high-delayers’ maps. The left hemisphere is shown.

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