•Manual tracing of locus coeruleus increased specificity of seed time series•Manual tracing of locus coeruleus increased specificity of intrinsic connectivity•Multi-echo fMRI increased temporal ...signal-to-noise ratio compared to single-echo fMRI•Connectivity maps across methodologies overlapped only moderately•Measurement of LC function benefits from multi-echo fMRI and tracing ROIs
The locus coeruleus (LC) plays a central role in regulating human cognition, arousal, and autonomic states. Efforts to characterize the LC's function in humans using functional magnetic resonance imaging have been hampered by its small size and location near a large source of noise, the fourth ventricle. We tested whether the ability to characterize LC function is improved by employing neuromelanin-T1 weighted images (nmT1) for LC localization and multi-echo functional magnetic resonance imaging (ME-fMRI) for estimating intrinsic functional connectivity (iFC). Analyses indicated that, relative to a probabilistic atlas, utilizing nmT1 images to individually localize the LC increases the specificity of seed time series and clusters in the iFC maps. When combined with independent components analysis (ME-ICA), ME-fMRI data provided significant improvements in the temporal signal to noise ratio and DVARS relative to denoised single echo data (1E-fMRI). The effects of acquiring nmT1 images and ME-fMRI data did not appear to only reflect increases in power: iFC maps for each approach overlapped only moderately. This is consistent with findings that ME-fMRI offers substantial advantages over 1E-fMRI acquisition and denoising. It also suggests that individually identifying LC with nmT1 scans is likely to reduce the influence of other nearby brainstem regions on estimates of LC function.
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Abstract Regional manual volumetry is the gold standard of in vivo neuroanatomy, but is labor-intensive, can be imperfectly reliable, and allows for measuring limited number of regions. Voxel-based ...morphometry (VBM) has perfect repeatability and assesses local structure across the whole brain. However, its anatomic validity is unclear, and with its increasing popularity, a systematic comparison of VBM to manual volumetry is necessary. The few existing comparison studies are limited by small samples, qualitative comparisons, and limited selection and modest reliability of manual measures. Our goal was to overcome those limitations by quantitatively comparing optimized VBM findings with highly reliable multiple regional measures in a large sample ( N = 200) across a wide agespan (18–81). We report a complex pattern of similarities and differences. Peak values of VBM volume estimates (modulated density) produced stronger age differences and a different spatial distribution from manual measures. However, when we aggregated VBM-derived information across voxels contained in specific anatomically defined regions (masks), the patterns of age differences became more similar, although important discrepancies emerged. Notably, VBM revealed stronger age differences in the regions bordering CSF and white matter areas prone to leukoaraiosis, and VBM was more likely to report nonlinearities in age–volume relationships. In the white matter regions, manual measures showed stronger negative associations with age than the corresponding VBM-based masks. We conclude that VBM provides realistic estimates of age differences in the regional gray matter only when applied to anatomically defined regions, but overestimates effects when individual peaks are interpreted. It may be beneficial to use VBM as a first-pass strategy, followed by manual measurement of anatomically defined regions.
The authors assessed individual differences in cortical recruitment, brain morphology, and inhibitory task performance. Similar to previous studies, older adults tended toward bilateral activity ...during task performance more than younger adults. However, better performing older adults showed less bilateral activity than poorer performers, contrary to the idea that additional activity is universally compensatory. A review of the results and of extant literature suggests that compensatory activity in prefrontal cortex may only be effective if the additional cortical processors brought to bear on the task can play a complementary role in task performance. Morphological analyses revealed that frontal white matter tracts differed as a function of performance in older adults, suggesting that hemispheric connectivity might impact both patterns of recruitment and cognitive performance.
In the first century, ce, the Roman satirist Juneval famously observed Orandum est, ut sit mens sana in corpore sano, or "A sound mind in a sound body is something to be prayed for." This implicit ...link between mental and physical health, also paralleled by Eastern philosophies and practices such as tai chi, has survived the millennia since Juneval and his contemporaries. More recently, controlled examinations of the effects of physical fitness on cognitive performance have shown that improving cardiovascular fitness (CVF) can help to reduce the deleterious effects of age on cognition and brain structure. Thus, as we age, it may well be the case that a sound mind is a natural concomitant of a sound body. Numerous cross-sectional and longitudinal studies have examined the effects of aerobic exercise on cognitive performance in aging humans since earlier studies, which found that physically fit older adults performed better on simple cognitive tasks than their less-fit counterparts. This base of knowledge recently has been furthered through examinations of cortical structure (Colcombe et al., 2003) and neurocognitive function in aging humans via functional and structural magnetic resonance imaging techniques. In this manuscript, we will briefly review some of our recent research on the effects of CVF on brain function, structure, and behavior in older adults. We will then outline some of our current and future directions in this area.
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed ...a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
Building on opportunities in open science, the PRIME-DRE non-human primate neuroimaging community at a Global Collaboration Workshop generated a collaboration-based strategic plan presented in this meeting report that is broadly cross-species and data integrative to guide neuroscientific innovation and discovery.
Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of ...barriers deter most researchers from implementing it in practice. To justify the significant effort required for sharing data, funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a case study that provides direct evidence of the impact of open sharing on brain imaging data use and resulting peer-reviewed publications. We demonstrate that openly shared data can increase the scale of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings dispel the myth that scientific findings using shared data cannot be published in high-impact journals, suggest the transformative power of data sharing for accelerating science, and underscore the need for implementing data sharing universally.
Toward discovery science of human brain function Biswal, Bharat B; Mennes, Maarten; Zuo, Xi-Nian ...
Proceedings of the National Academy of Sciences - PNAS,
03/2010, Volume:
107, Issue:
10
Journal Article
Peer reviewed
Open access
Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common ...paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines ...that ensure the reproducible and generalizable processing of ASL MRI data.
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