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. 2006 Nov 15;33(3):980-90.
doi: 10.1016/j.neuroimage.2006.07.028. Epub 2006 Sep 25.

Developmental neural networks in children performing a Categorical N-Back Task

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Developmental neural networks in children performing a Categorical N-Back Task

Kristina T Ciesielski et al. Neuroimage. .

Abstract

The prefrontal and temporal networks subserving object working memory tasks in adults have been reported as immature in young children; yet children are adequately capable of performing such tasks. We investigated the basis of this apparent contradiction using a complex object working memory task, a Categorical n-back (CN-BT). We examined whether the neural networks engaged by the CN-BT in children consist of the same brain regions as those in adults, but with a different magnitude of activation, or whether the networks are qualitatively different. Event-related fMRI was used to study differences in brain activation between healthy children ages 6 and 10 years, and young adults (20-28 years). Performance accuracy and RTs in 10-year-olds and adults were comparable, but the performance in 6-year-olds was lower. In adults, the CN-BT was highly effective in engaging the bilateral (L>R) ventral prefrontal cortex, the bilateral fusiform gyrus, posterior cingulate and precuneus, thus suggesting an involvement of the ventral visual stream, with related feature extraction and semantic labeling strategies. In children, the brain networks were distinctly different. They involved the premotor and parietal cortex, anterior insula, caudate/putamen, and the cerebellum, thus suggesting a predominant involvement of the visual dorsal and sensory-motor pathways, with related visual-spatial and action cognitive strategies. The findings indicate engagement of developmental networks in children reflecting task-effective brain activation. The age-related pattern of fMRI activation suggests a working hypothesis of a developmental shift from reliance on the dorsal visual stream and premotor/striatal/cerebellar networks in young children to reliance on the ventral prefrontal and inferior temporal networks in adults.

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