Local brain connectivity and associations with gender and age

ABSTRACTRegional homogeneity measures synchrony of resting-state brain activity in neighboring voxels, or local connectivity. The effects of age and gender on local connectivity in healthy subjects are unknown. We performed regional homogeneity analyses on resting state BOLD time series data acquired from 58 normal, healthy participants, ranging in age from 11 to 35 (mean 18.1±5.0 years, 32 males). Regional homogeneity was found to be highest for gray matter, with brain regions within the default mode network having the highest local connectivity values. There was a general decrease in regional homogeneity with age with the greatest reduction seen in the anterior cingulate and temporal lobe. Greater female local connectivity in the right hippocampus and amygdala was also noted, regardless of age. These findings suggest that local connectivity at the millimeter scale decreases during development as longer connections are formed, and underscores the importance of examining gender differences in imaging studies of healthy and clinical populations

Developmental Maturation of Dynamic Causal Control Signals in Higher-Order Cognition: A Neurocognitive Network Model

Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI) to investigate the maturation of control processes underlying problem solving skills in 7–9 year-old children. Our analysis focused on two key neurocognitive networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience network, anchored in anterior insula (AI), ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal central executive network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We found that, by age 9, the AI node of the salience network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the central executive network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. The quantitative approach developed is likely to be useful in investigating neurodevelopmental disorders, in which control processes are impaired, such as autism and ADHD

Impulse Control and Underlying Functions of the Left DLPFC Mediate Age-Related and Age-Independent Individual Differences in Strategic Social Behavior

SummaryHuman social exchange is often characterized by conflicts of interest requiring strategic behavior for their resolution. To investigate the development of the cognitive and neural mechanisms underlying strategic behavior, we studied children's decisions while they played two types of economic exchange games with differing demands of strategic behavior. We show an increase of strategic behavior with age, which could not be explained by age-related changes in social preferences but instead by developmental differences in impulsivity and associated brain functions of the left dorsolateral prefrontal cortex (DLPFC). Furthermore, observed differences in cortical thickness of lDLPFC were predictive of differences in impulsivity and strategic behavior irrespective of age. We conclude that egoistic behavior in younger children is not caused by a lack of understanding right or wrong, but by the inability to implement behavioral control when tempted to act selfishly; a function relying on brain regions maturing only late in ontogeny

Development of Large-Scale Functional Brain Networks in Children

Large-scale rewiring of brain circuits in children leads to emergence of hierarchical organization in the mature adult brain

MR connectomics: a conceptual framework for studying the developing brain

The combination of advanced neuroimaging techniques and major developments in complex network science, have given birth to a new framework for studying the brain: “connectomics.” This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research

Altersabhängige Veränderungen des EEGs in Kindheit und Adoleszenz

Der vorliegende Mantelteil bildet einen Rahmen für drei empirische Arbeiten, die sich mit altersabhängigen Veränderungen des Elektroenzephalogramms (= EEG) in Kindheit und Adoleszenz beschäftigen. In der Einleitung wird Hirnentwicklung als gemeinsamer Hintergrund der Arbeiten vorgestellt. Im Theorieteil wird das EEG als Methode zur Erfassung von Hirnentwicklung bei Kindern und Jugendlichen dargestellt. Abschließend werden dann frühere Befunde in diesem Bereich skizziert und eigene Hypothesen abgeleitet. Nach einer kurzen Beschreibung des Designs, der Stichprobe und des allgemeinen Vorgehens bei der Erfassung und Auswertung der Daten im Methodenteil werden im Diskussionsteil eigene Befunde zusammengefasst und im Hinblick auf eine mögliche Bedeutung für ein Verständnis normaler und pathologischer Entwicklung erörtert. Ausgangspunkt der vorliegenden Promotion ist ein Artikel zu frequenzspezifischen Veränderungen der hirnelektrischen Ruheaktivität über das Schulalter (Arbeit I), in den Erkenntnisse der Diplomarbeit des Autors wesentlich verfeinert eingingen. Die auf diesem Weg beschriebene hirnelektrische Aktivität wurde dann in einem weiteren Manuskript im Hinblick auf altersabhängige Veränderungen ihrer räumlichen Synchronisierung analysiert (Arbeit II). Daraus ergibt sich eine umfassende Beschreibung des Ruhe-EEGs in Kindheit und Adoleszenz. Über Veränderungen des Ruhe-EEGs hinaus wurden in Arbeit III altersabhängige Veränderungen ereigniskorrelierter Potentiale beschrieben. Das hierfür herangezogene P3-Paradigma wird im Folgenden als neurophysiologisches Korrelat höherer Aufmerksamkeits- und Gedächtnisprozesse betrachtet. Gegenwärtig wird eine Reorganisation des Ruhe-EEGs in Folge von Informationsverarbeitungsprozessen als eine mögliche Grundlage ereigniskorrelierter Potentiale diskutiert. Dieser Zusammenhang unterstreicht die Bedeutung einer gemeinsamen Untersuchung von Ruhe-Aktivität und ereigniskorrelierter Aktivität für ein Verständnis der markanten kognitiven Fortschritte in der Kindheit und Adoleszenz