Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

Savalia, Neil K.; Agres, Phillip F.; Chan, Micaela Y.; Feczko, Eric; Kennedy, James L.; Wig, Gagan S.

doi:10.1002/hbm.23397

Cited by 164 publications

(193 citation statements)

References 109 publications

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“…Recently, a number of studies have pointed out effects of participant motion on the quality of structural MRI scans, including on estimates of regional morphological measures such as cortical thickness (Reuter et al 2015; Alexander-Bloch et al 2016; Savalia et al 2017). While we have carried out stringent quality control of our structural scans and FreeSurfer reconstructions of cortical thickness (details in Supplementary Information), we cannot completely rule out potential artefactual effects of motion on our results.…”

Section: Discussionmentioning

confidence: 99%

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

et al. 2017

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Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14–24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.

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Section: Discussionmentioning

confidence: 99%

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

et al. 2017

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“…Strong artifacts due to motion, in addition to their relevance for fMRI, have been noted in diffusion weighted imaging (Roalf et al, 2016; Yendiki et al, 2014) and cortical thickness measurements (Reuter et al, 2015; Savalia et al, 2017). Motion artifacts appear to be tightly related to clinical factors (Fair et al, 2012b) and a whole host of behavioral phenotypes and metrics (Siegel et al, 2016).…”

Section: Methodsological Challenges and Recommendationsmentioning

confidence: 99%

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

2017

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The development of human cognition results from the emergence of coordinated brain activity betweeen distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain’s functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to 1) better characterize normative developmental trajectories, 2) link these trajectories to biologic mechanistic events, as well as component behaviors and 3) better understand the clinical implications and pathophysiological basis of aberrant network development.

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“…Manual editing and rechecking were completed as needed to account for the inaccuracies in the automated outputs (Savalia et al, 2017). …”

Section: Methodsmentioning

confidence: 99%

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span

et al. 2017

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Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20–89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system (“non-connector” nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems (“connector” nodes). This “activation selectivity” was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the “dedifferentiation” in brain activity observed in aging.SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20–89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance.

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Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

Cited by 164 publications

References 109 publications

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span

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