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The human brain connectome is characterized by the duality of highly modular structure and efficient integration, supporting information processing. Newborns with congenital heart disease (CHD), prematurity, or spina bifida aperta (SBA) constitute a population at risk for altered brain development and developmental delay (DD). We hypothesize that, independent of etiology, alterations of connectomic organization reflect neural circuitry impairments in cognitive DD.

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A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of connections among the constituent neurons. However, in contrast to the well-established theory for quantifying information encoded by the firing patterns of neural networks, little is known about quantifying information encoded by its synaptic connections. Here, we develop a theoretical framework using continuous Hopfield networks as an exemplar for associative neural networks, and data that follow mixtures of broadly applicable multivariate log-normal distributions.

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Osteocalcin (OCN) is a hormone secreted by osteoblasts and has attracted widespread attention for its role in regulating brain function. Clinical studies indicate a positive correlation between levels of circulating OCN and cognitive performance. Indeed, lower circulating OCN has been detected in various neurodegenerative diseases (NDs), while OCN supplementation under certain conditions may improve cognitive function.

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Remembering events is crucial to intelligent behavior. Flexible memory retrieval requires a cognitive map and is supported by two key brain systems: hippocampal episodic memory (EM) and prefrontal working memory (WM). Although an understanding of EM is emerging, little is understood of WM beyond simple memory retrieval.

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Children who develop diabetes in their first years of life risk being exposed to many decades of hyperglycemia, hence having a high risk of early complications and premature death. An additional age-dependent risk is that dysglycemia, especially hyperglycemia, negatively affects the developing brain. In evaluating the outcome of insulin treatment at an individual and group level, cutoff thresholds for glucose values are needed.

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