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Damien A Fair - One of the best experts on this subject based on the ideXlab platform.
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image processing and analysis methods for the adolescent brain cognitive development study
NeuroImage, 2019Co-Authors: Donald J Hagler, Sean N Hatton, Carolina Makowski, Daniela M Cornejo, Damien A Fair, Anthony Steven Dick, Matthew T Sutherland, B J Casey, M Deanna, Michael P HarmsAbstract:The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.
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image processing and analysis methods for the adolescent brain cognitive development study
bioRxiv, 2018Co-Authors: Donald J Hagler, Sean N Hatton, Carolina Makowski, Daniela M Cornejo, Damien A Fair, Anthony Steven Dick, Matthew T Sutherland, B J Casey, M Deanna, Michael P HarmsAbstract:The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The ABCD Study is a collaborative effort, including a Coordinating Center, 21 data acquisition sites across the United States, and a Data Analysis and Informatics Center (DAIC). The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data will provide a resource of unprecedented scale and depth for studying typical and atypical development. Here, we describe the baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes. Neuroimaging processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI.
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examining mechanisms of brain control of bladder function with resting state functional connectivity mri
Neurourology and Urodynamics, 2014Co-Authors: Bradley L Schlaggar, Rahel Nardos, William Thomas Gregory, Christine Krisky, Amanda Newell, Binyam Nardos, Damien A FairAbstract:Aims This aim of this study is to identify the brain mechanisms involved in bladder control. Methods We used fMRI to identify brain regions that are activated during bladder filling. We then used resting state connectivity fMRI (rs-fcMRI) to assess functional connectivity of regions identified by fMRI with the rest of the brain as the bladder is filled to capacity. Results Female participants (n = 20) were between ages 40 and 64 with no significant history of symptomatic urinary incontinence. Main effect of time (MET) fMRI analysis resulted in 20 regions of interest (ROIs) that have significant change in BOLD signal (z = 3.25, P <0.05) over the course of subtle bladder filling and emptying regardless of full versus empty bladder state. Bladder-state by time (BST) fMRI analysis resulted in three ROIs that have significant change in BOLD signal (z = 3.25, P <0.05) over the course of bladder runs comparing full versus empty bladder state. Rs-fcMRI fixed effects analysis identified significant changes in connectivity between full and empty bladder states in seven brain regions (z = 4.0) using the three BST ROIs and sixteen brain regions (z = 7) using the twenty MET ROIs. Regions identified include medial frontal gyrus, posterior cingulate (PCC), inferiolateral temporal and post-central gyrus, amygdale, the caudate, inferior parietal lobe as well as anterior and middle cingulate gyrus. Conclusions There is significant and vast changes in the brain's functional connectivity when bladder is filled suggesting that the central process responsible for the increased control during the full bladder state appears to largely rely on the how distributed brain systems are functionally integrated. Neurourol. Urodynam. 33:493–501, 2014. © 2013 Wiley Periodicals, Inc.
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defining functional areas in individual human brains using resting functional connectivity mri
NeuroImage, 2008Co-Authors: Alexander L Cohen, Damien A Fair, Bradley L Schlaggar, Francis M Miezin, Nico U F Dosenbach, Donna L Dierker, David C Van Essen, Steven E PetersenAbstract:The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g., topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.
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a method for using blocked and event related fMRI data to study resting state functional connectivity
NeuroImage, 2007Co-Authors: Damien A Fair, Bradley L Schlaggar, L Alexander B A Cohen, Francis M Miezin, Nico U F Dosenbach, Kristin K Wenger, Abraham Z Snyder, Marcus E Raichle, Steven E PetersenAbstract:Abstract Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large data sets of task-related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of data sets could potentially be modified to emulate resting state data. These data sets include: (1) “interleaved” resting blocks from blocked or mixed blocked/event-related sets, and (2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that, despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of “continuous” resting state data. In contrast, despite being qualitatively similar to “continuous” resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care.
Steven E Petersen - One of the best experts on this subject based on the ideXlab platform.
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Role of the anterior insula in task-level control and focal attention
Brain Structure and Function, 2010Co-Authors: Steven M. Nelson, Bradley L Schlaggar, Nico U F Dosenbach, Alexander L Cohen, Mark E. Wheeler, Steven E PetersenAbstract:In humans, the anterior insula (aI) has been the topic of considerable research and ascribed a vast number of functional properties by way of neuroimaging and lesion studies. Here, we argue that the aI, at least in part, plays a role in domain-general attentional control and highlight studies (Dosenbach et al. 2006 ; Dosenbach et al. 2007 ) supporting this view. Additionally, we discuss a study (Ploran et al. 2007 ) that implicates aI in processes related to the capture of focal attention. Task-level control and focal attention may or may not reflect information processing supported by a single functional area (within the aI). Therefore, we apply a novel technique (Cohen et al. 2008 ) that utilizes resting state functional connectivity MRI (rs-fcMRI) to determine whether separable regions exist within the aI. rs-fcMRI mapping suggests that the ventral portion of the aI is distinguishable from more dorsal/anterior regions, which are themselves distinct from more posterior parts of the aI. When these regions are applied to functional MRI (fMRI) data, the ventral and dorsal/anterior regions support processes potentially related to both task-level control and focal attention, whereas the more posterior aI regions did not. These findings suggest that there exists some functional heterogeneity within aI that may subserve related but distinct types of higher-order cognitive processing.
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defining functional areas in individual human brains using resting functional connectivity mri
NeuroImage, 2008Co-Authors: Alexander L Cohen, Damien A Fair, Bradley L Schlaggar, Francis M Miezin, Nico U F Dosenbach, Donna L Dierker, David C Van Essen, Steven E PetersenAbstract:The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g., topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.
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a method for using blocked and event related fMRI data to study resting state functional connectivity
NeuroImage, 2007Co-Authors: Damien A Fair, Bradley L Schlaggar, L Alexander B A Cohen, Francis M Miezin, Nico U F Dosenbach, Kristin K Wenger, Abraham Z Snyder, Marcus E Raichle, Steven E PetersenAbstract:Abstract Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large data sets of task-related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of data sets could potentially be modified to emulate resting state data. These data sets include: (1) “interleaved” resting blocks from blocked or mixed blocked/event-related sets, and (2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that, despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of “continuous” resting state data. In contrast, despite being qualitatively similar to “continuous” resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care.
Kantaro Nishigori - One of the best experts on this subject based on the ideXlab platform.
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Towards HCP-Style macaque connectomes: 24-Channel 3T multi-array coil, MRI sequences and preprocessing.
NeuroImage, 2020Co-Authors: Joonas A. Autio, Matthew F. Glasser, Takayuki Ose, Chad J. Donahue, Matteo Bastiani, Masahiro Ohno, Yoshihiko Kawabata, Yuta Urushibata, Katsutoshi Murata, Kantaro NishigoriAbstract:Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain.
Kalanit Grillspector - One of the best experts on this subject based on the ideXlab platform.
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white matter fascicles and cortical microstructure predict reading related responses in human ventral temporal cortex
NeuroImage, 2021Co-Authors: Mareike Grotheer, Jason D Yeatman, Kalanit GrillspectorAbstract:Reading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain's fascicles and to map their endpoint densities in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint densities of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. In the remaining participants (N=20, validation set), we show that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual's reading-related responses in lateral VTC.
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corresponding ecog and fMRI category selective signals in human ventral temporal cortex
Neuropsychologia, 2016Co-Authors: Corentin Jacques, Nathan Witthoft, Kevin S Weiner, Brett L Foster, Vinitha Rangarajan, Dora Hermes, Kai J Miller, Josef Parvizi, Kalanit GrillspectorAbstract:Abstract Functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG) research have been influential in revealing the functional characteristics of category-selective responses in human ventral temporal cortex (VTC). One important, but unanswered, question is how these two types of measurements might be related with respect to the VTC. Here we examined which components of the ECoG signal correspond to the fMRI response by using a rare opportunity to measure both fMRI and ECoG responses from the same individuals to images of exemplars of various categories including faces, limbs, cars and houses. Our data reveal three key findings. First, we discovered that the coupling between fMRI and ECoG responses is frequency and time dependent. The strongest and most sustained correlation is observed between fMRI and high frequency broadband (HFB) ECoG responses (30–160 hz). In contrast, the correlation between fMRI and ECoG signals in lower frequency bands is temporally transient, where the correlation is initially positive, but then tapers off or becomes negative. Second, we find that the strong and positive correlation between fMRI and ECoG signals in all frequency bands emerges rapidly around 100 ms after stimulus onset, together with the onset of the first stimulus-driven neural signals in VTC. Third, we find that the spatial topology and representational structure of category-selectivity in VTC reflected in ECoG HFB responses mirrors the topology and structure observed with fMRI. These findings of a strong and rapid coupling between fMRI and HFB responses validate fMRI measurements of functional selectivity with recordings of direct neural activity and suggest that fMRI category-selective signals in VTC are associated with feed-forward neural processing.
Bradley L Schlaggar - One of the best experts on this subject based on the ideXlab platform.
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examining mechanisms of brain control of bladder function with resting state functional connectivity mri
Neurourology and Urodynamics, 2014Co-Authors: Bradley L Schlaggar, Rahel Nardos, William Thomas Gregory, Christine Krisky, Amanda Newell, Binyam Nardos, Damien A FairAbstract:Aims This aim of this study is to identify the brain mechanisms involved in bladder control. Methods We used fMRI to identify brain regions that are activated during bladder filling. We then used resting state connectivity fMRI (rs-fcMRI) to assess functional connectivity of regions identified by fMRI with the rest of the brain as the bladder is filled to capacity. Results Female participants (n = 20) were between ages 40 and 64 with no significant history of symptomatic urinary incontinence. Main effect of time (MET) fMRI analysis resulted in 20 regions of interest (ROIs) that have significant change in BOLD signal (z = 3.25, P <0.05) over the course of subtle bladder filling and emptying regardless of full versus empty bladder state. Bladder-state by time (BST) fMRI analysis resulted in three ROIs that have significant change in BOLD signal (z = 3.25, P <0.05) over the course of bladder runs comparing full versus empty bladder state. Rs-fcMRI fixed effects analysis identified significant changes in connectivity between full and empty bladder states in seven brain regions (z = 4.0) using the three BST ROIs and sixteen brain regions (z = 7) using the twenty MET ROIs. Regions identified include medial frontal gyrus, posterior cingulate (PCC), inferiolateral temporal and post-central gyrus, amygdale, the caudate, inferior parietal lobe as well as anterior and middle cingulate gyrus. Conclusions There is significant and vast changes in the brain's functional connectivity when bladder is filled suggesting that the central process responsible for the increased control during the full bladder state appears to largely rely on the how distributed brain systems are functionally integrated. Neurourol. Urodynam. 33:493–501, 2014. © 2013 Wiley Periodicals, Inc.
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Role of the anterior insula in task-level control and focal attention
Brain Structure and Function, 2010Co-Authors: Steven M. Nelson, Bradley L Schlaggar, Nico U F Dosenbach, Alexander L Cohen, Mark E. Wheeler, Steven E PetersenAbstract:In humans, the anterior insula (aI) has been the topic of considerable research and ascribed a vast number of functional properties by way of neuroimaging and lesion studies. Here, we argue that the aI, at least in part, plays a role in domain-general attentional control and highlight studies (Dosenbach et al. 2006 ; Dosenbach et al. 2007 ) supporting this view. Additionally, we discuss a study (Ploran et al. 2007 ) that implicates aI in processes related to the capture of focal attention. Task-level control and focal attention may or may not reflect information processing supported by a single functional area (within the aI). Therefore, we apply a novel technique (Cohen et al. 2008 ) that utilizes resting state functional connectivity MRI (rs-fcMRI) to determine whether separable regions exist within the aI. rs-fcMRI mapping suggests that the ventral portion of the aI is distinguishable from more dorsal/anterior regions, which are themselves distinct from more posterior parts of the aI. When these regions are applied to functional MRI (fMRI) data, the ventral and dorsal/anterior regions support processes potentially related to both task-level control and focal attention, whereas the more posterior aI regions did not. These findings suggest that there exists some functional heterogeneity within aI that may subserve related but distinct types of higher-order cognitive processing.
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defining functional areas in individual human brains using resting functional connectivity mri
NeuroImage, 2008Co-Authors: Alexander L Cohen, Damien A Fair, Bradley L Schlaggar, Francis M Miezin, Nico U F Dosenbach, Donna L Dierker, David C Van Essen, Steven E PetersenAbstract:The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g., topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.
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a method for using blocked and event related fMRI data to study resting state functional connectivity
NeuroImage, 2007Co-Authors: Damien A Fair, Bradley L Schlaggar, L Alexander B A Cohen, Francis M Miezin, Nico U F Dosenbach, Kristin K Wenger, Abraham Z Snyder, Marcus E Raichle, Steven E PetersenAbstract:Abstract Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large data sets of task-related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of data sets could potentially be modified to emulate resting state data. These data sets include: (1) “interleaved” resting blocks from blocked or mixed blocked/event-related sets, and (2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that, despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of “continuous” resting state data. In contrast, despite being qualitatively similar to “continuous” resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care.
