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Multimodal imaging of the self-regulating developing brain.

ABSTRACT: Self-regulation refers to the ability to control behavior, cognition, and emotions, and self-regulation failure is related to a range of neuropsychiatric problems. It is poorly understood how structural maturation of the brain brings about the gradual improvement in self-regulation during childhood. In a large-scale multicenter effort, 735 children (4-21 y) underwent structural MRI for quantification of cortical thickness and surface area and diffusion tensor imaging for quantification of the quality of major fiber connections. Brain development was related to a standardized measure of cognitive control (the flanker task from the National Institutes of Health Toolbox), a critical component of self-regulation. Ability to inhibit responses and impose cognitive control increased rapidly during preteen years. Surface area of the anterior cingulate cortex accounted for a significant proportion of the variance in cognitive performance. This finding is intriguing, because characteristics of the anterior cingulum are shown to be related to impulse, attention, and executive problems in neurodevelopmental disorders, indicating a neural foundation for self-regulation abilities along a continuum from normality to pathology. The relationship was strongest in the younger children. Properties of large-fiber connections added to the picture by explaining additional variance in cognitive control. Although cognitive control was related to surface area of the anterior cingulate independently of basic processes of mental speed, the relationship between white matter quality and cognitive control could be fully accounted for by speed. The results underscore the need for integration of different aspects of brain maturation to understand the foundations of cognitive development.

SUBMITTER: Fjell AM

PROVIDER: S-EPMC3511748 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Multimodal imaging of the self-regulating developing brain.

Fjell Anders M AM Walhovd Kristine Beate KB Brown Timothy T TT Kuperman Joshua M JM Chung Yoonho Y Hagler Donald J DJ Venkatraman Vijay V Roddey J Cooper JC Erhart Matthew M McCabe Connor C Akshoomoff Natacha N Amaral David G DG Bloss Cinnamon S CS Libiger Ondrej O Darst Burcu F BF Schork Nicholas J NJ Casey B J BJ Chang Linda L Ernst Thomas M TM Gruen Jeffrey R JR Kaufmann Walter E WE Kenet Tal T Frazier Jean J Murray Sarah S SS Sowell Elizabeth R ER van Zijl Peter P Mostofsky Stewart S Jernigan Terry L TL Dale Anders M AM

Proceedings of the National Academy of Sciences of the United States of America 20121112 48

Self-regulation refers to the ability to control behavior, cognition, and emotions, and self-regulation failure is related to a range of neuropsychiatric problems. It is poorly understood how structural maturation of the brain brings about the gradual improvement in self-regulation during childhood. In a large-scale multicenter effort, 735 children (4-21 y) underwent structural MRI for quantification of cortical thickness and surface area and diffusion tensor imaging for quantification of the qu ...[more]

PMID: 23150548

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Project description:Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19-73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results. It was observed both a high inter-hemispheric symmetry and an intra-hemispheric modularity associated with structural data, whilst functional data presented lower inter-hemispheric symmetry and a high inter-hemispheric modularity. Furthermore, when testing for differences between two subgroups (<40 and >40 years old adults) we observed a significant reduction in the volume and thickness, and an increase in the mean diffusivity of most of the subcortical/cortical regions. Conclusion. While bridging the gap between the high numbers of packages and tools widely available for the neuroimaging community in one toolbox, MIBCA also offers different possibilities for combining, analysing and visualising data in novel ways, enabling a better understanding of the human brain.

Project description:Background and purposeContrast-enhanced noninvasive angiography and perfusion imaging are recommended to identify eligible patients for endovascular therapy (EVT) in extended time windows (>6 hours or wake-up). If eligible, additional intraarterial contrast exposure will occur during EVT. We aimed to study the renal safety in the DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke) population, selected with contrast-enhanced multimodal Imaging and randomized to EVT versus medical management.MethodsIn the randomized DEFUSE 3 trial population, we compared changes in serum creatinine between baseline (before randomization) and 24 hours later. The primary outcome was the relative change in creatinine level between baseline and 24 hours in the EVT versus medical arm. The secondary outcome was a comparison between computed tomography (CT) versus magnetic resonance imaging selection in the EVT arm. The safety outcome was a comparison of the proportion of patients with criteria for contrast-associated kidney injury in the EVT versus medical arm and a comparison between CT versus magnetic resonance imaging selection in the EVT arm.ResultsIn the DEFUSE 3 population (n=182, age 69±13, 51% female), mean creatinine decreased from a baseline of 0.98±0.33 mg/dL to 0.88±0.28 mg/dL at 24 hours (P<0.001). There was no difference in change between treatment groups: relative to baseline, there was a 6.3% reduction in the EVT group versus 9.2% in the medical group, P=0.294. Absolute decrease -0.08±0.18 in EVT versus -0.12±0.18 in medical, P=0.135; Among patients treated with EVT, there was no difference in 24-hour creatinine level changes between patients who were selected with CT angiography/CT perfusion (-0.08±0.18) versus magnetic resonance imaging (-0.07±0.19), P=0.808 or 6.8% reduction versus 4.8%, P=0.696. In the EVT arm, contrast-associated kidney injury was encountered in 4 out of 91 (4.4%) versus 2/90 (2.2%) in the medical arm P=0.682. In the EVT arm, contrast-associated kidney injury was evenly distributed between magnetic resonance imaging (1/22, 4.6%) versus CT 3 out of 69 (4.4%), P=1.0.ConclusionsPerfusion imaging before EVT was not associated with evidence of decline in renal function. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02586415.

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Multimodal imaging of the self-regulating developing brain.

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Multimodal imaging of the self-regulating developing brain.

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