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Ooi LQR, Orban C, Nichols TE, Zhang S, Tan TWK, Kong R, Marek S, Dosenbach NU, Laumann T, Gordon EM, Zhou JH, Bzdok D, Eickhoff SB, Holmes AJ, Yeo BTT. MRI economics: Balancing sample size and scan duration in brain wide association studies. bioRxiv 2024:2024.02.16.580448. [PMID: 38405815 PMCID: PMC10889017 DOI: 10.1101/2024.02.16.580448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
A pervasive dilemma in neuroimaging is whether to prioritize sample size or scan duration given fixed resources. Here, we systematically investigate this trade-off in the context of brain-wide association studies (BWAS) using resting-state functional magnetic resonance imaging (fMRI). We find that total scan duration (sample size × scan duration per participant) robustly explains individual-level phenotypic prediction accuracy via a logarithmic model, suggesting that sample size and scan duration are broadly interchangeable. The returns of scan duration eventually diminish relative to sample size, which we explain with principled theoretical derivations. When accounting for fixed costs associated with each participant (e.g., recruitment, non-imaging measures), we find that prediction accuracy in small-scale BWAS might benefit from much longer scan durations (>50 min) than typically assumed. Most existing large-scale studies might also have benefited from smaller sample sizes with longer scan durations. Both logarithmic and theoretical models of the relationships among sample size, scan duration and prediction accuracy explain well-predicted phenotypes better than poorly-predicted phenotypes. The logarithmic and theoretical models are also undermined by individual differences in brain states. These results replicate across phenotypic domains (e.g., cognition and mental health) from two large-scale datasets with different algorithms and metrics. Overall, our study emphasizes the importance of scan time, which is ignored in standard power calculations. Standard power calculations inevitably maximize sample size at the expense of scan duration. The resulting prediction accuracies are likely lower than would be produced with alternate designs, thus impeding scientific discovery. Our empirically informed reference is available for future study design: WEB_APPLICATION_LINK.
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Affiliation(s)
- Leon Qi Rong Ooi
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
| | - Csaba Orban
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Shaoshi Zhang
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
| | - Trevor Wei Kiat Tan
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
| | - Ru Kong
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University, School of Medicine, USA
| | - Nico U.F. Dosenbach
- Mallinckrodt Institute of Radiology, Washington University, School of Medicine, USA
- Department of Neurology, Washington University, School of Medicine, USA
- Department of Psychiatry, Washington University, School of Medicine, USA
- Deparments of Paediatrics, Biomedical Engineering, and Psychological and Brain Sciences, Washington University, School of Medicine, USA
| | - Timothy Laumann
- Department of Psychiatry, Washington University, School of Medicine, USA
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University, School of Medicine, USA
| | - Juan Helen Zhou
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
| | - Danilo Bzdok
- Department of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute, Canada
- Faculty of Medicine, School of Computer Science, McGill University, Montreal, QC, Canada
- Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Center Jülich, Jülich, Germany
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Avram J Holmes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
| | - B. T. Thomas Yeo
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
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Chauvin RJ, Newbold DJ, Nielsen AN, Miller RL, Krimmel SR, Metoki A, Wang A, Van AN, Montez DF, Marek S, Suljic V, Baden NJ, Ramirez-Perez N, Scheidter KM, Monk JS, Whiting FI, Adeyemo B, Snyder AZ, Kay BP, Raichle ME, Laumann TO, Gordon EM, Dosenbach NU. Disuse-driven plasticity in the human thalamus and putamen. bioRxiv 2024:2023.11.07.566031. [PMID: 37987000 PMCID: PMC10659348 DOI: 10.1101/2023.11.07.566031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.
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Affiliation(s)
- Roselyne J. Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Dillan J. Newbold
- Department of Neurology, New York University Grossman School of Medicine, New York, New York 10016, USA
| | - Ashley N. Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Ryland L. Miller
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain
| | - Samuel R. Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Anxu Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
| | - Andrew N. Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Division of Computation and Data Science, Washington University School of Medicine, St. Louis, MO 63110
| | - David F. Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Vahdeta Suljic
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Noah J. Baden
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | | | - Kristen M. Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Julia S. Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Forrest I. Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P. Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E. Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O. Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M. Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U.F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
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3
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Krimmel SR, Laumann TO, Chauvin RJ, Hershey T, Roland JL, Shimony JS, Willie JT, Norris SA, Marek S, Van AN, Monk J, Scheidter KM, Whiting F, Ramirez-Perez N, Metoki A, Wang A, Kay BP, Nahman-Averbuch H, Fair DA, Lynch CJ, Raichle ME, Gordon EM, Dosenbach NUF. The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action. bioRxiv 2024:2023.12.30.573730. [PMID: 38260662 PMCID: PMC10802246 DOI: 10.1101/2023.12.30.573730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.
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Affiliation(s)
- Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tamara Hershey
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Forrest Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nadeshka Ramirez-Perez
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anxu Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Computation and Data Science, Washington University, St. Louis, Missouri, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Hadas Nahman-Averbuch
- Washington University Pain Center, Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota, USA
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
- Program in Occupational Therapy, Washington University, St. Louis, Missouri, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, USA
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D'Andrea CB, Laumann TO, Newbold DJ, Nelson SM, Nielsen AN, Chauvin R, Marek S, Greene DJ, Dosenbach NUF, Gordon EM. Substructure of the brain's Cingulo-Opercular network. bioRxiv 2023:2023.10.10.561772. [PMID: 37873065 PMCID: PMC10592749 DOI: 10.1101/2023.10.10.561772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.
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Affiliation(s)
- Carolina Badke D'Andrea
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, California 92093, USA
- Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO 63310, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Dillan J Newbold
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA
| | - Ashley N Nielsen
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Roselyne Chauvin
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, California 92093, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
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Rajesh A, Seider NA, Newbold DJ, Adeyemo B, Marek S, Greene DJ, Snyder AZ, Shimony JS, Laumann TO, Dosenbach NUF, Gordon EM. Structure-Function Coupling in Highly Sampled Individual Brains. bioRxiv 2023:2023.10.04.560909. [PMID: 37873167 PMCID: PMC10592963 DOI: 10.1101/2023.10.04.560909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas. SIGNIFICANCE STATEMENT Structural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function.Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships.Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulate's structure-function relationship suggests that its organization may be unique among higher-order cortical regions.
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Badke D’Andrea C, Marek S, Van AN, Miller RL, Earl EA, Stewart SB, Dosenbach NUF, Schlaggar BL, Laumann TO, Fair DA, Gordon EM, Greene DJ. Thalamo-cortical and cerebello-cortical functional connectivity in development. Cereb Cortex 2023; 33:9250-9262. [PMID: 37293735 PMCID: PMC10492576 DOI: 10.1093/cercor/bhad198] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 05/09/2023] [Accepted: 05/17/2023] [Indexed: 06/10/2023] Open
Abstract
The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.
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Affiliation(s)
- Carolina Badke D’Andrea
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Ryland L Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Eric A Earl
- Data Science and Sharing Team, National Institute of Mental Health, NIH, DHHS, Bethesda, MD 20899, United States
| | - Stephanie B Stewart
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO 80045, United States
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Damien A Fair
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455, United States
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55455, United States
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
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7
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Tervo-Clemmens B, Marek S, Barch DM. Tailoring Psychiatric Neuroimaging to Translational Goals. JAMA Psychiatry 2023:2806008. [PMID: 37314757 DOI: 10.1001/jamapsychiatry.2023.1416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- Brenden Tervo-Clemmens
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
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Li ZA, Cai Y, Taylor RL, Eisenstein SA, Barch DM, Marek S, Hershey T. Associations Between Socioeconomic Status, Obesity, Cognition, and White Matter Microstructure in Children. JAMA Netw Open 2023; 6:e2320276. [PMID: 37368403 DOI: 10.1001/jamanetworkopen.2023.20276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Abstract
Importance Lower neighborhood and household socioeconomic status (SES) are associated with negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter and via what mechanisms. Objective To assess whether and how neighborhood and household SES are independently associated with children's white matter microstructure and examine whether obesity and cognitive performance (reflecting environmental cognitive and sensory stimulation) are plausible mediators. Design, Setting, and Participants This cross-sectional study used baseline data from participants in the Adolescent Brain Cognitive Development (ABCD) study. Data were collected at 21 US sites, and school-based recruitment was used to represent the US population. Children aged 9 to 11 years and their parents or caregivers completed assessments between October 1, 2016, and October 31, 2018. After exclusions, 8842 of 11 875 children in the ABCD study were included in the analyses. Data analysis was conducted from July 11 to December 19, 2022. Exposures Neighborhood disadvantage was derived from area deprivation indices at participants' primary residence. Household SES factors were total income and highest parental educational attainment. Main Outcomes and Measures A restriction spectrum imaging (RSI) model was used to quantify restricted normalized directional (RND; reflecting oriented myelin organization) and restricted normalized isotropic (RNI; reflecting glial and neuronal cell bodies) diffusion in 31 major white matter tracts. The RSI measurements were scanner harmonized. Obesity was assessed through body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), age- and sex-adjusted BMI z scores, and waist circumference, and cognition was assessed through the National Institutes of Health Toolbox Cognition Battery. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, mean head motion, and twin or siblingship. Results Among 8842 children, 4543 (51.4%) were boys, and the mean (SD) age was 9.9 (0.7) years. Linear mixed-effects models revealed that greater neighborhood disadvantage was associated with lower RSI-RND in the left superior longitudinal fasciculus (β = -0.055; 95% CI, -0.081 to -0.028) and forceps major (β = -0.040; 95% CI, -0.067 to -0.013). Lower parental educational attainment was associated with lower RSI-RND in the bilateral superior longitudinal fasciculus (eg, right hemisphere: β = 0.053; 95% CI, 0.025-0.080) and bilateral corticospinal or pyramidal tract (eg, right hemisphere: β = 0.042; 95% CI, 0.015-0.069). Structural equation models revealed that lower cognitive performance (eg, lower total cognition score and higher neighborhood disadvantage: β = -0.012; 95% CI, -0.016 to -0.009) and greater obesity (eg, higher BMI and higher neighborhood disadvantage: β = -0.004; 95% CI, -0.006 to -0.001) partially accounted for the associations between SES and RSI-RND. Lower household income was associated with higher RSI-RNI in most tracts (eg, right inferior longitudinal fasciculus: β = -0.042 [95% CI, -0.073 to -0.012]; right anterior thalamic radiations: β = -0.045 [95% CI, -0.075 to -0.014]), and greater neighborhood disadvantage had similar associations in primarily frontolimbic tracts (eg, right fornix: β = 0.046 [95% CI, 0.019-0.074]; right anterior thalamic radiations: β = 0.045 [95% CI, 0.018-0.072]). Lower parental educational attainment was associated with higher RSI-RNI in the forceps major (β = -0.048; 95% CI, -0.077 to -0.020). Greater obesity partially accounted for these SES associations with RSI-RNI (eg, higher BMI and higher neighborhood disadvantage: β = 0.015; 95% CI, 0.011-0.020). Findings were robust in sensitivity analyses and were corroborated using diffusion tensor imaging. Conclusions and Relevance In this cross-sectional study, both neighborhood and household contexts were associated with white matter development in children, and findings suggested that obesity and cognitive performance were possible mediators in these associations. Future research on children's brain health may benefit from considering these factors from multiple socioeconomic perspectives.
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Affiliation(s)
- Zhaolong Adrian Li
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
| | - Yuqi Cai
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
- Now with Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rita L Taylor
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
| | - Sarah A Eisenstein
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Scott Marek
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Tamara Hershey
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University in St Louis School of Medicine, St Louis, Missouri
- Department of Neurology, Washington University in St Louis School of Medicine, St Louis, Missouri
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Sanders AFP, Harms MP, Kandala S, Marek S, Somerville LH, Bookheimer SY, Dapretto M, Thomas KM, Van Essen DC, Yacoub E, Barch DM. Age-related differences in resting-state functional connectivity from childhood to adolescence. Cereb Cortex 2023; 33:6928-6942. [PMID: 36724055 PMCID: PMC10233258 DOI: 10.1093/cercor/bhad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 01/06/2023] [Accepted: 01/07/2023] [Indexed: 02/02/2023] Open
Abstract
The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.
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Affiliation(s)
- Ashley F P Sanders
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Michael P Harms
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63119, USA
| | - Leah H Somerville
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Kathleen M Thomas
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
- Department of Psychological and Brain Sciences, Washington University, St Louis, MO 63130, USA
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10
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Gordon EM, Chauvin RJ, Van AN, Rajesh A, Nielsen A, Newbold DJ, Lynch CJ, Seider NA, Krimmel SR, Scheidter KM, Monk J, Miller RL, Metoki A, Montez DF, Zheng A, Elbau I, Madison T, Nishino T, Myers MJ, Kaplan S, Badke D'Andrea C, Demeter DV, Feigelis M, Ramirez JSB, Xu T, Barch DM, Smyser CD, Rogers CE, Zimmermann J, Botteron KN, Pruett JR, Willie JT, Brunner P, Shimony JS, Kay BP, Marek S, Norris SA, Gratton C, Sylvester CM, Power JD, Liston C, Greene DJ, Roland JL, Petersen SE, Raichle ME, Laumann TO, Fair DA, Dosenbach NUF. A somato-cognitive action network alternates with effector regions in motor cortex. Nature 2023; 617:351-359. [PMID: 37076628 PMCID: PMC10172144 DOI: 10.1038/s41586-023-05964-2] [Citation(s) in RCA: 74] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/16/2023] [Indexed: 04/21/2023]
Abstract
Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.
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Affiliation(s)
- Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
| | - Aishwarya Rajesh
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Ashley Nielsen
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, New York University Langone Medical Center, New York, NY, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Ryland L Miller
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Immanuel Elbau
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Madison
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Michael J Myers
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Carolina Badke D'Andrea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Matthew Feigelis
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Julian S B Ramirez
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Deanna M Barch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Christopher D Smyser
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Kelly N Botteron
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Peter Brunner
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott A Norris
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Caterina Gratton
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Steven E Petersen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Marcus E Raichle
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, 55455, United States
| | - Nico U F Dosenbach
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA.
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA.
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA.
- Program in Occupational Therapy, Washington University in St. Louis, St Louis, MO, USA.
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Montez DF, Van AN, Miller RL, Seider NA, Marek S, Zheng A, Newbold DJ, Scheidter K, Feczko E, Perrone AJ, Miranda-Dominguez O, Earl EA, Kay BP, Jha AK, Sotiras A, Laumann TO, Greene DJ, Gordon EM, Tisdall MD, van der Kouwe A, Fair DA, Dosenbach NUF. Using synthetic MR images for distortion correction. Dev Cogn Neurosci 2023; 60:101234. [PMID: 37023632 PMCID: PMC10106483 DOI: 10.1016/j.dcn.2023.101234] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 03/07/2023] [Accepted: 03/16/2023] [Indexed: 04/07/2023] Open
Abstract
Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.
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Affiliation(s)
- David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America.
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Ryland L Miller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, New York University Langone Medical Center, New York, NY 10016, United States of America
| | - Kristen Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Anders J Perrone
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Psychiatry, Oregon Health and Science University, Portland, OR 97239, United States of America
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Eric A Earl
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Psychiatry, Oregon Health and Science University, Portland, OR 97239, United States of America
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Abhinav K Jha
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Aristeidis Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Institute for Informatics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, La Jolla CA 92093, United States of America
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Andre van der Kouwe
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, United States of America; Department of Radiology, Harvard Medical School, Boston, MA 02115, United States of America
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Institute of Child Development, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
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Tervo-Clemmens B, Marek S, Chauvin RJ, Van AN, Kay BP, Laumann TO, Thompson WK, Nichols TE, Yeo BTT, Barch DM, Luna B, Fair DA, Dosenbach NUF. Reply to: Multivariate BWAS can be replicable with moderate sample sizes. Nature 2023; 615:E8-E12. [PMID: 36890374 PMCID: PMC9995264 DOI: 10.1038/s41586-023-05746-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Affiliation(s)
- Brenden Tervo-Clemmens
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Wesley K Thompson
- Division of Biostatistics, University of California San Diego, La Jolla, CA, USA
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore
- Centre for Translational MR Research, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health, Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, USA
| | - Beatriz Luna
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA.
- Institute of Child Development, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA.
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, USA.
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA.
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA.
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Li ZA, Cai Y, Taylor RL, Eisenstein SA, Barch DM, Marek S, Hershey T. Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition. medRxiv 2023:2023.02.09.23285150. [PMID: 36798149 PMCID: PMC9934783 DOI: 10.1101/2023.02.09.23285150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Importance Both neighborhood and household socioeconomic disadvantage relate to negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter development, and via what mechanisms socioeconomic status (SES) influences the brain. Objective To test independent associations between neighborhood and household SES indicators and white matter microstructure in children, and examine whether body mass index and cognitive function (a proxy of environmental cognitive/sensory stimulation) may plausibly mediate these associations. Design This cross-sectional study used baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing 10-year cohort study tracking child health. Setting School-based recruitment at 21 U.S. sites. Participants Children aged 9 to 11 years and their parents/caregivers completed baseline assessments between October 1 st , 2016 and October 31 st , 2018. Data analysis was conducted from July to December 2022. Exposures Neighborhood disadvantage was derived from area deprivation indices at primary residence. Household SES indicators were total income and the highest parental education attainment. Main Outcomes and Measures Thirty-one major white matter tracts were segmented from diffusion-weighted images. The Restriction Spectrum Imaging (RSI) model was implemented to measure restricted normalized directional (RND; reflecting oriented myelin organization) and isotropic (RNI; reflecting glial/neuronal cell bodies) diffusion in each tract. Obesity-related measures were body mass index (BMI), BMI z -scores, and waist circumference, and cognitive performance was assessed using the NIH Toolbox Cognition Battery. Linear mixed-effects models tested the associations between SES indicators and scanner-harmonized RSI metrics. Structural equation models examined indirect effects of obesity and cognitive performance in the significant associations between SES and white mater microstructure summary principal components. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, and head motion. Results The analytical sample included 8842 children (4299 [48.6%] girls; mean age [SD], 9.9 [0.7] years). Greater neighborhood disadvantage and lower parental education were independently associated with lower RSI-RND in forceps major and corticospinal/pyramidal tracts, and had overlapping associations in the superior longitudinal fasciculus. Lower cognition scores and greater obesity-related measures partially accounted for these SES associations with RSI-RND. Lower household income was related to higher RSI-RNI in almost every tract, and greater neighborhood disadvantage had similar effects in primarily frontolimbic tracts. Lower parental education was uniquely linked to higher RSI-RNI in forceps major. Greater obesity-related measures partially accounted for these SES associations with RSI-RNI. Findings were robust in sensitivity analyses and mostly corroborated using traditional diffusion tensor imaging (DTI). Conclusions and Relevance These cross-sectional results demonstrate that both neighborhood and household contexts are relevant to white matter development in children, and suggest cognitive performance and obesity as possible pathways of influence. Interventions targeting obesity reduction and improving cognition from multiple socioeconomic angles may ameliorate brain health in low-SES children. Key Points Question: Are neighborhood and household socioeconomic levels associated with children’s brain white matter microstructure, and if so, do obesity and cognitive performance (reflecting environmental stimulation) mediate the associations?Findings: In a cohort of 8842 children, higher neighborhood disadvantage, lower household income, and lower parental education had independent and overlapping associations with lower restricted directional diffusion and greater restricted isotropic diffusion in white matter. Greater body mass index and poorer cognitive performance partially mediated these associations.Meaning: Both neighborhood and household poverty may contribute to altered white matter development in children. These effects may be partially explained by obesity incidence and poorer cognitive performance.
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Affiliation(s)
- Zhaolong Adrian Li
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO 63130, USA,Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Yuqi Cai
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Rita L. Taylor
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Sarah A. Eisenstein
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO 63130, USA,Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA
| | - Deanna M. Barch
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO 63130, USA,Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA,Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA,Co-corresponding authors: Scott Marek, PhD, Assistant Professor, Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, MSC 8134-0070-02, Phone: (314)-454-6120, ; Tamara Hershey, PhD, James S. McDonnell Professor of Cognitive Neuroscience, Department of Psychiatry and Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, MSC 8134-0070-02, Phone: (314)-362-5593,
| | - Tamara Hershey
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO 63130, USA,Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA,Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA,Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA,Co-corresponding authors: Scott Marek, PhD, Assistant Professor, Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, MSC 8134-0070-02, Phone: (314)-454-6120, ; Tamara Hershey, PhD, James S. McDonnell Professor of Cognitive Neuroscience, Department of Psychiatry and Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, MSC 8134-0070-02, Phone: (314)-362-5593,
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14
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Hawks ZW, Todorov A, Marrus N, Nishino T, Talovic M, Nebel MB, Girault JB, Davis S, Marek S, Seitzman BA, Eggebrecht AT, Elison J, Dager S, Mosconi MW, Tychsen L, Snyder AZ, Botteron K, Estes A, Evans A, Gerig G, Hazlett HC, McKinstry RC, Pandey J, Schultz RT, Styner M, Wolff JJ, Zwaigenbaum L, Markson L, Petersen SE, Constantino JN, White DA, Piven J, Pruett JR. A Prospective Evaluation of Infant Cerebellar-Cerebral Functional Connectivity in Relation to Behavioral Development in Autism Spectrum Disorder. Biol Psychiatry Glob Open Sci 2023; 3:149-161. [PMID: 36712571 PMCID: PMC9874081 DOI: 10.1016/j.bpsgos.2021.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 12/03/2021] [Accepted: 12/04/2021] [Indexed: 02/01/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection. Methods Data from the Infant Brain Imaging Study (n = 94, 68 male) were used to examine 6-month cerebellar functional connectivity magnetic resonance imaging in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning-based predictive tests examined cerebellar-frontoparietal network (FPN; subserves error signaling in support of EBL) and cerebellar-default mode network (DMN; broadly implicated in ASD) connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven functional connectivity magnetic resonance imaging enrichment examined brain-wide behavioral associations, with post hoc tests of cerebellar connections. Results Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. Functional connectivity magnetic resonance imaging enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post hoc tests did not suggest a role for cerebellar connections. Conclusions We failed to identify cerebellar functional connectivity-based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities.
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Affiliation(s)
- Zoë W. Hawks
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
- Address correspondence to Zoë W. Hawks, Ph.D.
| | - Alexandre Todorov
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Muhamed Talovic
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Mary Beth Nebel
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jessica B. Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Savannah Davis
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Benjamin A. Seitzman
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Adam T. Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Jed Elison
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota
| | - Stephen Dager
- Departments of Radiology, University of Washington, Seattle, Washington
| | - Matthew W. Mosconi
- Life Span Institute and Clinical Child Psychology Program, University of Kansas, Lawrence, Kansas
| | - Lawrence Tychsen
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Kelly Botteron
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Annette Estes
- Speech and Hearing Sciences, University of Washington, Seattle, Washington
| | - Alan Evans
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Guido Gerig
- Department of Computer Science and Engineering, Tandon School of Engineering, New York University, New York, New York
| | - Heather C. Hazlett
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Robert C. McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Juhi Pandey
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Robert T. Schultz
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jason J. Wolff
- Department of Educational Psychology, University of Minnesota, Minneapolis, Minnesota
| | - Lonnie Zwaigenbaum
- Department of Psychiatry, University of Alberta, Edmonton, Alberta, Canada
| | - Lori Markson
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
| | - Steven E. Petersen
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - John N. Constantino
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Desirée A. White
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
| | - Joseph Piven
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - John R. Pruett
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
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15
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Seider NA, Adeyemo B, Miller R, Newbold DJ, Hampton JM, Scheidter KM, Rutlin J, Laumann TO, Roland JL, Montez DF, Van AN, Zheng A, Marek S, Kay BP, Bretthorst GL, Schlaggar BL, Greene DJ, Wang Y, Petersen SE, Barch DM, Gordon EM, Snyder AZ, Shimony JS, Dosenbach NUF. Accuracy and reliability of diffusion imaging models. Neuroimage 2022; 254:119138. [PMID: 35339687 PMCID: PMC9841915 DOI: 10.1016/j.neuroimage.2022.119138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/01/2022] [Accepted: 03/22/2022] [Indexed: 01/19/2023] Open
Abstract
Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.
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Affiliation(s)
- Nicole A Seider
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Ryland Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, New York University Langone Medical Center, New York, NY 10016, United States of America
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Kristen M Scheidter
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Jerrel Rutlin
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Jarod L Roland
- Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO 63110 United States of America
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - G Larry Bretthorst
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Chemistry, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205, United States of America; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States of America; Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States of America
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States of America
| | - Yong Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Steven E Petersen
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO 63110, United States of America
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO 63110, United States of America
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
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16
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Gordon EM, Laumann TO, Marek S, Newbold DJ, Hampton JM, Seider NA, Montez DF, Nielsen AM, Van AN, Zheng A, Miller R, Siegel JS, Kay BP, Snyder AZ, Greene DJ, Schlaggar BL, Petersen SE, Nelson SM, Dosenbach NUF. Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex. Cereb Cortex 2022; 32:2868-2884. [PMID: 34718460 PMCID: PMC9247416 DOI: 10.1093/cercor/bhab387] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 11/14/2022] Open
Abstract
The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.
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Affiliation(s)
- Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ashley M Nielsen
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL 60611, USA
| | - Andrew N Van
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ryland Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joshua S Siegel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Steven E Petersen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Psychological & Brain Sciences, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55454, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
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17
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Chen J, Tam A, Kebets V, Orban C, Ooi LQR, Asplund CL, Marek S, Dosenbach NUF, Eickhoff SB, Bzdok D, Holmes AJ, Yeo BTT. Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study. Nat Commun 2022; 13:2217. [PMID: 35468875 PMCID: PMC9038754 DOI: 10.1038/s41467-022-29766-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 03/18/2022] [Indexed: 12/30/2022] Open
Abstract
How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood.
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Affiliation(s)
- Jianzhong Chen
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | - Angela Tam
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | - Valeria Kebets
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | - Csaba Orban
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | - Leon Qi Rong Ooi
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.,Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - Christopher L Asplund
- Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore.,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore.,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.,Division of Social Sciences, Yale-NUS College, Singapore, Singapore.,Department of Psychology, National University of Singapore, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Simon B Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviours (INM-7), Research Center Jülich, Jülich, Germany
| | - Danilo Bzdok
- Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Mila - Quebec AI Institute, Montreal, QC, Canada
| | - Avram J Holmes
- Yale University, Departments of Psychology and Psychiatry, New Haven, CT, USA
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore. .,Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore. .,Centre for Translational MR Research, National University of Singapore, Singapore, Singapore. .,N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore. .,Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore. .,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
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18
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Kalfoutzos K, Argyriadis A, Joechel E, Kosse J, Jackisch C, Marek S. 285 Clinical management of placenta percreta non-previa with pelvic wall involvement: A case presentation. Eur J Obstet Gynecol Reprod Biol 2022. [DOI: 10.1016/j.ejogrb.2021.11.079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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19
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Marek S, Tervo-Clemmens B, Calabro FJ, Montez DF, Kay BP, Hatoum AS, Donohue MR, Foran W, Miller RL, Hendrickson TJ, Malone SM, Kandala S, Feczko E, Miranda-Dominguez O, Graham AM, Earl EA, Perrone AJ, Cordova M, Doyle O, Moore LA, Conan GM, Uriarte J, Snider K, Lynch BJ, Wilgenbusch JC, Pengo T, Tam A, Chen J, Newbold DJ, Zheng A, Seider NA, Van AN, Metoki A, Chauvin RJ, Laumann TO, Greene DJ, Petersen SE, Garavan H, Thompson WK, Nichols TE, Yeo BTT, Barch DM, Luna B, Fair DA, Dosenbach NUF. Reproducible brain-wide association studies require thousands of individuals. Nature 2022; 603:654-660. [PMID: 35296861 PMCID: PMC8991999 DOI: 10.1038/s41586-022-04492-9] [Citation(s) in RCA: 646] [Impact Index Per Article: 323.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 01/31/2022] [Indexed: 02/01/2023]
Abstract
Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
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Affiliation(s)
- Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
| | - Brenden Tervo-Clemmens
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Alexander S Hatoum
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Meghan Rose Donohue
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryland L Miller
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy J Hendrickson
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Eric A Earl
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Anders J Perrone
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Michaela Cordova
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Gregory M Conan
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Johnny Uriarte
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Kathy Snider
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Benjamin J Lynch
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - James C Wilgenbusch
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Thomas Pengo
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Angela Tam
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore
- Centre for Translational MR Research, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health, Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
| | - Jianzhong Chen
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore
- Centre for Translational MR Research, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health, Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Wesley K Thompson
- Division of Biostatistics, University of California San Diego, La Jolla, CA, USA
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition, National University of Singapore, Singapore, Singapore
- Centre for Translational MR Research, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health, Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, USA
| | - Beatriz Luna
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA.
- Institute of Child Development, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA.
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA.
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA.
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20
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Zheng A, Montez DF, Marek S, Gilmore AW, Newbold DJ, Laumann TO, Kay BP, Seider NA, Van AN, Hampton JM, Alexopoulos D, Schlaggar BL, Sylvester CM, Greene DJ, Shimony JS, Nelson SM, Wig GS, Gratton C, McDermott KB, Raichle ME, Gordon EM, Dosenbach NUF. Parallel hippocampal-parietal circuits for self- and goal-oriented processing. Proc Natl Acad Sci U S A 2021; 118:e2101743118. [PMID: 34404728 PMCID: PMC8403906 DOI: 10.1073/pnas.2101743118] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.
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Affiliation(s)
- Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Adrian W Gilmore
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Jacqueline M Hampton
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, CA 92093
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414
| | - Gagan S Wig
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL 60208
- Department of Neurology, Northwestern University, Evanston, IL 60208
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110
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21
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Abstract
Human functional brain networks can be reliably characterized within individuals using precision functional mapping. This approach entails the collection of large quantities of functional magnetic resonance imaging (fMRI) data from each individual subject. Studies employing precision functional mapping in the cerebral cortex have found that individuals manifest unique representations of functional brain networks around a central tendency described by previous group average approaches. We recently extended precision functional mapping to the subcortex and cerebellum, which has revealed several novel organizational principles within these structures. Here, we detail these principles and provide insights into how precision functional mapping of subcortical structures and the cerebellum may become clinically translatable.
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Affiliation(s)
- Scott Marek
- Department of Psychiatry, Washington University School of Medicine
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego
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22
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Chahal R, Weissman DG, Marek S, Rhoads SA, Hipwell AE, Forbes EE, Keenan K, Guyer AE. Girls' brain structural connectivity in late adolescence relates to history of depression symptoms. J Child Psychol Psychiatry 2020; 61:1224-1233. [PMID: 31879977 PMCID: PMC7316589 DOI: 10.1111/jcpp.13184] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 11/20/2019] [Accepted: 11/22/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Girls' depressive symptoms typically increase in adolescence, with individual differences in course and severity being key risk factors for impaired emotional functioning in young adulthood. Given the continued brain white matter (WM) maturation that occurs in adolescence, the present study tested whether structural connectivity patterns in late adolescence are associated with variation in the course of depression symptom severity throughout adolescence. METHOD Participants were girls (N = 115) enrolled in a multiyear prospective cohort study of risk for depression. Initial depression severity (intercept) at age 10 and change in severity (linear slope) across ages 10-19 were examined in relation to WM tractography collected at age 19. Network-based statistic analyses were used to identify clusters showing variation in structural connectivity in association with depressive symptom intercept, slope, and their interaction. RESULTS Higher initial depressive severity and steeper positive slope (separately) were associated with greater structural connectivity between temporal, subcortical socioaffective, and occipital regions. Intercept showed more connectivity associations than slope. The interaction effect indicated that higher initial symptom severity and a steeper negative slope (i.e., alleviating symptoms) were related to greater connectivity between cognitive control regions. Moderately severe symptoms that worsened over time were followed by greater connectivity between self-referential and cognitive regions (e.g., posterior cingulate and frontal gyrus). CONCLUSIONS Higher depressive symptom severity in early adolescence and increasing symptom severity over time may forecast structural connectivity differences in late adolescence, particularly in pathways involving cognitive and emotion-processing regions. Understanding how clinical course relates to neurobiological correlates may inform new treatment approaches to adolescent depression.
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Affiliation(s)
- Rajpreet Chahal
- Department of Human Ecology, University of California, Davis, Davis, CA 95616
- Center for Mind and Brain, University of California, Davis, Davis, CA 95618
| | | | - Scott Marek
- Department of Psychiatry, Washington University, St. Louis, MO 63110
| | - Shawn A. Rhoads
- Department of Psychology, Georgetown University, Washington, DC 20057
| | - Alison E. Hipwell
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213
| | - Erika E. Forbes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213
| | - Kate Keenan
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637
| | - Amanda E. Guyer
- Department of Human Ecology, University of California, Davis, Davis, CA 95616
- Center for Mind and Brain, University of California, Davis, Davis, CA 95618
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23
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Newbold DJ, Laumann TO, Hoyt CR, Hampton JM, Montez DF, Raut RV, Ortega M, Mitra A, Nielsen AN, Miller DB, Adeyemo B, Nguyen AL, Scheidter KM, Tanenbaum AB, Van AN, Marek S, Schlaggar BL, Carter AR, Greene DJ, Gordon EM, Raichle ME, Petersen SE, Snyder AZ, Dosenbach NUF. Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits. Neuron 2020; 107:580-589.e6. [PMID: 32778224 PMCID: PMC7419711 DOI: 10.1016/j.neuron.2020.05.007] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 04/12/2020] [Accepted: 05/06/2020] [Indexed: 11/16/2022]
Abstract
To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.
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Affiliation(s)
- Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Catherine R Hoyt
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ryan V Raut
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Mario Ortega
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Stanford University, Stanford, CA 94305, USA
| | - Ashley N Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL 60611, USA
| | - Derek B Miller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie L Nguyen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Aaron B Tanenbaum
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Bradley L Schlaggar
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Kennedy Krieger Institute, Baltimore, MD 21205, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Alexandre R Carter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Deanna J Greene
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Evan M Gordon
- VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75080, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA.
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24
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Gordon EM, Laumann TO, Marek S, Raut RV, Gratton C, Newbold DJ, Greene DJ, Coalson RS, Snyder AZ, Schlaggar BL, Petersen SE, Dosenbach NUF, Nelson SM. Default-mode network streams for coupling to language and control systems. Proc Natl Acad Sci U S A 2020; 117:17308-17319. [PMID: 32632019 PMCID: PMC7382234 DOI: 10.1073/pnas.2005238117] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.
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Affiliation(s)
- Evan M Gordon
- Veterans Integrated Service Network 17 Center of Excellence for Research on Returning War Veterans, US Department of Veterans Affairs, Waco, TX 76711;
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychology and Neuroscience, Baylor University, Waco, TX 76789
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Ryan V Raut
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL 60208
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Deanna J Greene
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Rebecca S Coalson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychological & Brain Sciences, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110
| | - Steven M Nelson
- Veterans Integrated Service Network 17 Center of Excellence for Research on Returning War Veterans, US Department of Veterans Affairs, Waco, TX 76711
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychology and Neuroscience, Baylor University, Waco, TX 76789
- Department of Psychiatry and Behavioral Science, Texas A&M Health Science Center, Bryan, TX 77807
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25
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Raut RV, Mitra A, Marek S, Ortega M, Snyder AZ, Tanenbaum A, Laumann TO, Dosenbach NUF, Raichle ME. Organization of Propagated Intrinsic Brain Activity in Individual Humans. Cereb Cortex 2020; 30:1716-1734. [PMID: 31504262 PMCID: PMC7132930 DOI: 10.1093/cercor/bhz198] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 07/09/2019] [Accepted: 08/07/2019] [Indexed: 12/11/2022] Open
Abstract
Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks-altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.
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Affiliation(s)
- Ryan V Raut
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
| | - Scott Marek
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
| | - Mario Ortega
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63110, USA
- Department of Occupational Therapy, Washington University, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
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26
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Greene DJ, Marek S, Gordon EM, Siegel JS, Gratton C, Laumann TO, Gilmore AW, Berg JJ, Nguyen AL, Dierker D, Van AN, Ortega M, Newbold DJ, Hampton JM, Nielsen AN, McDermott KB, Roland JL, Norris SA, Nelson SM, Snyder AZ, Schlaggar BL, Petersen SE, Dosenbach NUF. Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals. Neuron 2020; 105:742-758.e6. [PMID: 31836321 PMCID: PMC7035165 DOI: 10.1016/j.neuron.2019.11.012] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 08/28/2019] [Accepted: 11/07/2019] [Indexed: 10/25/2022]
Abstract
The basal ganglia, thalamus, and cerebral cortex form an interconnected network implicated in many neurological and psychiatric illnesses. A better understanding of cortico-subcortical circuits in individuals will aid in development of personalized treatments. Using precision functional mapping-individual-specific analysis of highly sampled human participants-we investigated individual-specific functional connectivity between subcortical structures and cortical functional networks. This approach revealed distinct subcortical zones of network specificity and multi-network integration. Integration zones were systematic, with convergence of cingulo-opercular control and somatomotor networks in the ventral intermediate thalamus (motor integration zones), dorsal attention and visual networks in the pulvinar, and default mode and multiple control networks in the caudate nucleus. The motor integration zones were present in every individual and correspond to consistently successful sites of deep brain stimulation (DBS; essential tremor). Individually variable subcortical zones correspond to DBS sites with less consistent treatment effects, highlighting the importance of PFM for neurosurgery, neurology, and psychiatry.
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Affiliation(s)
- Deanna J Greene
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Evan M Gordon
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
| | - Joshua S Siegel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA; Department of Neurology, Northwestern University, Evanston, IL, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Adrian W Gilmore
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jeffrey J Berg
- Department of Psychology, New York University, New York, NY, USA
| | - Annie L Nguyen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Mario Ortega
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Ashley N Nielsen
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, USA
| | - Kathleen B McDermott
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, USA
| | - Jarod L Roland
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Steven M Nelson
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Steven E Petersen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University, St. Louis, MO, USA
| | - Nico U F Dosenbach
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University, St. Louis, MO, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA; Program in Occupational Therapy, Washington University, St. Louis, MO, USA.
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27
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Sylvester CM, Yu Q, Srivastava AB, Marek S, Zheng A, Alexopoulos D, Smyser CD, Shimony JS, Ortega M, Dierker DL, Patel GH, Nelson SM, Gilmore AW, McDermott KB, Berg JJ, Drysdale AT, Perino MT, Snyder AZ, Raut RV, Laumann TO, Gordon EM, Barch DM, Rogers CE, Greene DJ, Raichle ME, Dosenbach NUF. Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry. Proc Natl Acad Sci U S A 2020; 117:3808-3818. [PMID: 32015137 PMCID: PMC7035483 DOI: 10.1073/pnas.1910842117] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.
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Affiliation(s)
- Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110;
| | - Qiongru Yu
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - A Benjamin Srivastava
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Psychiatry, Columbia University, New York, NY 10032
- New York State Psychiatric Institute, New York, NY 10032
| | - Scott Marek
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Annie Zheng
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
| | | | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Mario Ortega
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Teva Pharmaceuticals, North Wales, PA 19454
| | - Donna L Dierker
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Gaurav H Patel
- Department of Psychiatry, Columbia University, New York, NY 10032
- New York State Psychiatric Institute, New York, NY 10032
| | - Steven M Nelson
- VISN 17 Center of Excellence for Research on Returning War Veterans, Doris Miller VA Medical Center, Waco, TX 76711
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706
| | - Adrian W Gilmore
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110
| | - Jeffrey J Berg
- Department of Psychology, New York University, New York, NY 10003
| | - Andrew T Drysdale
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Michael T Perino
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Abraham Z Snyder
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Ryan V Raut
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Timothy O Laumann
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Evan M Gordon
- VISN 17 Center of Excellence for Research on Returning War Veterans, Doris Miller VA Medical Center, Waco, TX 76711
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
| | - Deanna J Greene
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Marcus E Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110;
| | - Nico U F Dosenbach
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110
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28
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Seitzman BA, Gratton C, Marek S, Raut RV, Dosenbach NUF, Schlaggar BL, Petersen SE, Greene DJ. A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum. Neuroimage 2020; 206:116290. [PMID: 31634545 PMCID: PMC6981071 DOI: 10.1016/j.neuroimage.2019.116290] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 10/15/2019] [Accepted: 10/16/2019] [Indexed: 12/15/2022] Open
Abstract
An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011, and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.
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Affiliation(s)
- Benjamin A Seitzman
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
| | - Caterina Gratton
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
| | - Scott Marek
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
| | - Ryan V Raut
- Department of Radiology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
| | - Nico U F Dosenbach
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Radiology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Pediatrics, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Occupational Therapy, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis- School of Engineering and Applied Science, One Brookings Dr, St. Louis, MO, 63130, USA.
| | - Bradley L Schlaggar
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Psychiatry, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Radiology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Pediatrics, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Neuroscience, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
| | - Steven E Petersen
- Department of Neurology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, One Brookings Dr, St. Louis, MO, 63130, USA; Department of Radiology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Neuroscience, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis- School of Engineering and Applied Science, One Brookings Dr, St. Louis, MO, 63130, USA.
| | - Deanna J Greene
- Department of Psychiatry, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA; Department of Radiology, Washington University in St. Louis- School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA.
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29
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Lopez KC, Kandala S, Marek S, Barch DM. Development of Network Topology and Functional Connectivity of the Prefrontal Cortex. Cereb Cortex 2019; 30:2489-2505. [DOI: 10.1093/cercor/bhz255] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 01/08/2023] Open
Abstract
Abstract
The prefrontal cortex (PFC) comprises distinct regions and networks that vary in their trajectories across development. Further understanding these diverging trajectories may elucidate the neural mechanisms by which distinct PFC regions contribute to cognitive maturity. In particular, it remains unclear whether PFC regions of distinct network affiliations differ in topology and their relationship to cognition. We examined 615 individuals (8–21 years) to characterize age-related effects in participation coefficient of 28 PFC regions of distinct networks, evaluating connectivity profiles of each region to understand patterns influencing topological maturity. Findings revealed that PFC regions of attention, frontoparietal, and default mode networks (DMN) displayed varying rates of decline in participation coefficient with age, characterized by stronger connectivity with each PFC’s respective network; suggesting that PFC regions largely aid network segregation. Conversely, PFC regions of the cinguloopercular/salience network increased in participation coefficient with age, marked by stronger between-network connections, suggesting that some PFC regions feature a distinctive ability to facilitate network integration. PFC topology of the DMN, in particular, predicted improvements in global cognition, including motor speed and higher order abilities. Together, these findings elucidate systematic differences in topology across PFC regions of different network affiliation, representing important neural signatures of typical brain development.
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Affiliation(s)
- Katherine C Lopez
- Department of Psychological & Brain Sciences, Washington University, St Louis, 63130 MO, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
| | - Scott Marek
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University, St Louis, 63130 MO, USA
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
- Department of Radiology, Washington University, St Louis, 63110 MO, USA
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30
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Marek S, Tervo-Clemmens B, Nielsen AN, Wheelock MD, Miller RL, Laumann TO, Earl E, Foran WW, Cordova M, Doyle O, Perrone A, Miranda-Dominguez O, Feczko E, Sturgeon D, Graham A, Hermosillo R, Snider K, Galassi A, Nagel BJ, Ewing SWF, Eggebrecht AT, Garavan H, Dale AM, Greene DJ, Barch DM, Fair DA, Luna B, Dosenbach NUF. Identifying reproducible individual differences in childhood functional brain networks: An ABCD study. Dev Cogn Neurosci 2019; 40:100706. [PMID: 31614255 PMCID: PMC6927479 DOI: 10.1016/j.dcn.2019.100706] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 08/01/2019] [Accepted: 08/21/2019] [Indexed: 02/08/2023] Open
Abstract
The 21-site Adolescent Brain Cognitive Development (ABCD) study provides an unparalleled opportunity to characterize functional brain development via resting-state functional connectivity (RSFC) and to quantify relationships between RSFC and behavior. This multi-site data set includes potentially confounding sources of variance, such as differences between data collection sites and/or scanner manufacturers, in addition to those inherent to RSFC (e.g., head motion). The ABCD project provides a framework for characterizing and reproducing RSFC and RSFC-behavior associations, while quantifying the extent to which sources of variability bias RSFC estimates. We quantified RSFC and functional network architecture in 2,188 9-10-year old children from the ABCD study, segregated into demographically-matched discovery (N = 1,166) and replication datasets (N = 1,022). We found RSFC and network architecture to be highly reproducible across children. We did not observe strong effects of site; however, scanner manufacturer effects were large, reproducible, and followed a "short-to-long" association with distance between regions. Accounting for potential confounding variables, we replicated that RSFC between several higher-order networks was related to general cognition. In sum, we provide a framework for how to characterize RSFC-behavior relationships in a rigorous and reproducible manner using the ABCD dataset and other large multi-site projects.
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Affiliation(s)
- Scott Marek
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, 63110, USA.
| | | | - Ashley N Nielsen
- Department of Medical Social Sciences, Northwestern University, Chicago, IL 60611, USA
| | - Muriah D Wheelock
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Ryland L Miller
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Eric Earl
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - William W Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 15213, USA
| | - Michaela Cordova
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Olivia Doyle
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Anders Perrone
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Oscar Miranda-Dominguez
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Eric Feczko
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, 97213, USA
| | - Darrick Sturgeon
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Alice Graham
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Robert Hermosillo
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Kathy Snider
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Anthony Galassi
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Bonnie J Nagel
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Sarah W Feldstein Ewing
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Adam T Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington VT 05401, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Deanna J Greene
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, 63110, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, 63110, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Damien A Fair
- Departments of Psychiatry & Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97213, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 15213, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, 63110, USA; Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, 63110, USA; Department of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA
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Kamińska A, Pardyak L, Marek S, Wróbel K, Kotula-Balak M, Bilińska B, Hejmej A. Notch signaling regulates nuclear androgen receptor AR and membrane androgen receptor ZIP9 in mouse Sertoli cells. Andrology 2019; 8:457-472. [PMID: 31468707 DOI: 10.1111/andr.12691] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/24/2019] [Accepted: 07/14/2019] [Indexed: 12/27/2022]
Abstract
BACKGROUND Notch signaling pathway is involved in contact-dependent communication between the cells of seminiferous epithelium, and its proper activity is important for undisturbed spermatogenesis. OBJECTIVES The aim was to assess the effect of Notch pathway inhibition on the expression of nuclear (AR) and membrane (ZIP9) androgen receptors and androgen-regulated genes, claudin-5 and claudin-11, in TM4 mouse Sertoli cell line. MATERIALS AND METHODS DAPT (γ-secretase inhibitor) treatment and recombination signal binding protein silencing were employed to reduce Notch signaling, whereas immobilized ligands were used to activate Notch pathway in TM4 cells. To reveal specific effect of each androgen receptor, AR or ZIP9 silencing was performed. RESULTS Notch pathway inhibition increased the expression of AR and ZIP9 mRNA and proteins (p < 0.01; p < 0.05) in TM4 cells, whereas incubation with Notch ligands, rDLL1 or rJAG1, reduced AR (p < 0.01; p < 0.001) and ZIP9 (p < 0.05; p < 0.01) expressions, respectively. Testosterone enhanced the expression of both receptors (p < 0.05; p < 0.01). Androgen-regulated claudin-5 and claudin-11 (p < 0.01; p < 0.001) and cAMP (p < 0.001) were elevated in Notch-inhibited cells, while activation of Notch signaling by DLL1 or JAG1 reduced claudin-11 or claudin-5 level (p < 0.01; p < 0.001), respectively. DISCUSSION Our findings indicate opposite effect of Notch and androgen signaling on the expression of androgen receptors in TM4 cells. We demonstrated that AR expression is regulated by DLL1-mediated Notch signaling, whereas JAG1 is involved in the regulation of ZIP9. The expression of both claudins and cAMP production is under inhibitory influence of Notch pathway. The effects of Notch signaling on claudin-5 and claudin-11 expression are mediated by ZIP9 and AR, respectively. CONCLUSION Notch signaling may be considered as an important pathway controlling Sertoli cell physiology, and its alterations may contribute to disturbed response of Sertoli cells to androgens.
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Affiliation(s)
- A Kamińska
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
| | - L Pardyak
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
| | - S Marek
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
| | - K Wróbel
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
| | - M Kotula-Balak
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland.,University Centre of Veterinary Medicine, University of Agriculture in Krakow, Krakow, Poland
| | - B Bilińska
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
| | - A Hejmej
- Department of Endocrinology, Faculty of Biology, Institute of Zoology & Biomedical Research, Jagiellonian University, Krakow, Poland
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Abstract
The human brain is organized into specialized functional brain networks. Some networks are dedicated to early sensory processing, and others to generating motor outputs. Yet, the bulk of the human brain's functional networks is actually dedicated to control processes. The two control networks most important for the impressive repertoire of control-related behaviors that humans are able to instantiate and maintain are the frontoparietal and cinguloopercular networks. We provide evidence that these two control networks largely contribute to nonoverlapping domains of control. These networks largely have been studied using fMRI, which is sensitive only to infraslow activity. Complementary electrophysiological techniques have provided evidence that these networks manifest at substantially faster frequencies (delta-alpha band), supporting their role in coordination of whole-brain functional network activity. Both the frontoparietal and cinguloopercular networks demonstrate protracted development, supporting increases in control-related performance. Recent studies from our lab indicate these control networks exhibit measurable individual specificity, highlighting the importance of individualized paradigms in neuroimaging studies to advance our understanding of typical and atypical control network function throughout the life span.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States; Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, United States.
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Abstract
The frontoparietal network is critical for our ability to coordinate behavior in a rapid, accurate, and flexible goal-driven manner. In this review, we outline support for the framing of the frontoparietal network as a distinct control network, in part functioning to flexibly interact with and alter other functional brain networks. This network coordination likely occurs in a 4 Hz to 73 Hz θ/α rhythm, both during resting state and task state. Precision mapping of individual human brains has revealed that the functional topography of the frontoparietal network is variable between individuals, underscoring the notion that group-average studies of the frontoparietal network may be obscuring important typical and atypical features. Many forms of psychopathology implicate the frontoparietal network, such as schizophrenia and attention-deficit/hyperactivity disorder. Given the interindividual variability in frontoparietal network organization, clinical studies will likely benefit greatly from acquiring more individual subject data to accurately characterize resting-state networks compromised in psychopathology.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA; Program in Occupational Therapy, Washington University School of Medicine, St Louis, Missouri, USA; Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, USA
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Marek S, Tervo-Clemmens B, Klein N, Foran W, Ghuman AS, Luna B. Adolescent development of cortical oscillations: Power, phase, and support of cognitive maturation. PLoS Biol 2018; 16:e2004188. [PMID: 30500809 PMCID: PMC6291169 DOI: 10.1371/journal.pbio.2004188] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 12/12/2018] [Accepted: 11/08/2018] [Indexed: 12/11/2022] Open
Abstract
During adolescence, the integration of specialized functional brain networks related to cognitive control continues to increase. Slow frequency oscillations (4-10 Hz) have been shown to support cognitive control processes, especially within prefrontal regions. However, it is unclear how neural oscillations contribute to functional brain network development and improvements in cognitive control during adolescence. To bridge this gap, we employed magnetoencephalography (MEG) to explore changes in oscillatory power and phase coupling across cortical networks in a sample of 68 adolescents and young adults. We found a redistribution of power from lower to higher frequencies throughout adolescence, such that delta band (1-3 Hz) power decreased, whereas beta band power (14-16 and 22-26 Hz) increased. Delta band power decreased with age most strongly in association networks within the frontal lobe and operculum. Conversely, beta band power increased throughout development, most strongly in processing networks and the posterior cingulate cortex, a hub of the default mode (DM) network. In terms of phase, theta band (5-9 Hz) phase-locking robustly decreased with development, following an anterior-to-posterior gradient, with the greatest decoupling occurring between association networks. Additionally, decreased slow frequency phase-locking between frontolimbic regions was related to decreased impulsivity with age. Thus, greater decoupling of slow frequency oscillations may afford functional networks greater flexibility during the resting state to instantiate control when required.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, United States of America
- * E-mail:
| | - Brenden Tervo-Clemmens
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Natalie Klein
- Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Avniel Singh Ghuman
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Beatriz Luna
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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Marek S, Siegel JS, Gordon EM, Raut RV, Gratton C, Newbold DJ, Ortega M, Laumann TO, Adeyemo B, Miller DB, Zheng A, Lopez KC, Berg JJ, Coalson RS, Nguyen AL, Dierker D, Van AN, Hoyt CR, McDermott KB, Norris SA, Shimony JS, Snyder AZ, Nelson SM, Barch DM, Schlaggar BL, Raichle ME, Petersen SE, Greene DJ, Dosenbach NUF. Spatial and Temporal Organization of the Individual Human Cerebellum. Neuron 2018; 100:977-993.e7. [PMID: 30473014 DOI: 10.1016/j.neuron.2018.10.010] [Citation(s) in RCA: 153] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 08/13/2018] [Accepted: 10/05/2018] [Indexed: 12/18/2022]
Abstract
The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit measurable individual specificity. Using the highly sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125-380 ms), supporting the hypothesis that the cerebellum engages in a domain-general function in the adaptive control of all cortical processes.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Joshua S Siegel
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Evan M Gordon
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, USA
| | - Ryan V Raut
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Caterina Gratton
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Mario Ortega
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Derek B Miller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Katherine C Lopez
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jeffrey J Berg
- Department of Psychology, New York University, New York, NY 10003 USA
| | - Rebecca S Coalson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie L Nguyen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Catherine R Hoyt
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven M Nelson
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, USA
| | - Deanna M Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Bradley L Schlaggar
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Deanna J Greene
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
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Marek S. The frontoparietal network: function, electrophysiology, and importance of individual precision mapping. Dialogues Clin Neurosci 2018; 20:133-140. [PMID: 30250390 PMCID: PMC6136121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
The frontoparietal network is critical for our ability to coordinate behavior in a rapid, accurate, and flexible goal-driven manner. In this review, we outline support for the framing of the frontoparietal network as a distinct control network, in part functioning to flexibly interact with and alter other functional brain networks. This network coordination likely occurs in a 4 Hz to 73 Hz θ/α rhythm, both during resting state and task state. Precision mapping of individual human brains has revealed that the functional topography of the frontoparietal network is variable between individuals, underscoring the notion that group-average studies of the frontoparietal network may be obscuring important typical and atypical features. Many forms of psychopathology implicate the frontoparietal network, such as schizophrenia and attention-deficit/hyperactivity disorder. Given the interindividual variability in frontoparietal network organization, clinical studies will likely benefit greatly from acquiring more individual subject data to accurately characterize resting-state networks compromised in psychopathology.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA
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Marek RJ, Coulon SM, Brown JD, Lydecker JA, Marek S, Malcolm R, O'Neil PM. Characteristics of Weight Loss Trajectories in a Comprehensive Lifestyle Intervention. Obesity (Silver Spring) 2017; 25:2062-2067. [PMID: 29086487 DOI: 10.1002/oby.21942] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 06/21/2017] [Accepted: 06/22/2017] [Indexed: 01/18/2023]
Abstract
OBJECTIVE Focusing on average weight loss (WL) from interventions provides useful efficacy data but masks large variability across patients. In this study, parameters of weight loss trajectories were determined that differentiated individuals during a 15-week clinical lifestyle intervention. METHODS Patients (n = 595) were in a fee-for-service WL lifestyle program with a partial meal replacement diet and lifestyle change counseling. Parameters used in latent class analyses were percent WL (%WL), weight nadir, number of weekly weight gains, maximum weekly percent weight gain, standard deviation of weekly weight changes, linear slope values, and change in slope. RESULTS Average %WL was 9.73%. Latent class analyses revealed three groups with considerable overlap in %WL ranges but differing significantly on all trajectory parameters (Ps < 0.001). Group 1 had the most variable and least successful pattern of weight changes. Group 3 had the least variable and most successful pattern of weight changes. Group 2 fell between the others on all parameters. CONCLUSIONS Emphasis on average WL likely obscures considerable variability in individual courses of weight change. Moreover, patients with similar %WL can have different WL trajectories. Identification of behavioral/physiological characteristics associated with different weight loss trajectories may facilitate the development of more tailored interventions, particularly for trajectories associated with less optimal outcomes.
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Affiliation(s)
- Ryan J Marek
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Sandra M Coulon
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Joshua D Brown
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Janet A Lydecker
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Robert Malcolm
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Patrick M O'Neil
- Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
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Abstract
Brains systems undergo unique and specific dynamic changes at the cellular, circuit, and systems level that underlie the transition to adult-level cognitive control. We integrate literature from these different levels of analyses to propose a novel model of the brain basis of the development of cognitive control. The ability to consistently exert cognitive control improves into adulthood as the flexible integration of component processes, including inhibitory control, performance monitoring, and working memory, increases. Unique maturational changes in brain structure, supported by interactions between dopaminergic and GABAergic systems, contribute to enhanced network synchronization and an improved signal-to-noise ratio. In turn, these factors facilitate the specialization and strengthening of connectivity in networks supporting the transition to adult levels of cognitive control. This model provides a novel understanding of the adolescent period as an adaptive period of heightened experience-seeking necessary for the specialization of brain systems supporting cognitive control.
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Moncrief I, Garzon C, Marek S, Stack J, Gamliel A, Garrido P, Proaño F, Gard M, Dehne H, Fletcher J. Development of simple sequence repeat (SSR) markers for discrimination among isolates of Fusarium proliferatum. J Microbiol Methods 2016; 126:12-7. [PMID: 27021663 DOI: 10.1016/j.mimet.2016.03.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 03/11/2016] [Accepted: 03/21/2016] [Indexed: 10/22/2022]
Abstract
The plant pathogen Fusarium proliferatum has a wide host range and occurs worldwide. Many isolates of the fungus produce mycotoxins in plant tissues, which, if ingested, can cause harm to animals and humans. In 2008, an outbreak of salmon blotch of onions, caused by F. proliferatum, was detected in southern Israel. The source and distribution of the fungus in Israel were unknown. Inter-simple sequence repeats (ISSR) were used to identify repetitive motifs present in seven isolates of F. proliferatum from Israel, Germany and Austria. ISSR repeat motifs were, used to develop 17 simple sequence repeat (SSR) loci. Six of these SSR markers were polymorphic in and consistently amplified from ten isolates collected in Israel, Germany, Austria and North America, from cucumber, onion, garlic, maize, and asparagus. These six polymorphic SSR alleles included 5 to 12 copies of di-, tri, and pentanucleotide motifs and yielded six to 9 alleles each. Sixteen of the SSR loci were amplified at least one of the seven Fusarium species, F. verticillioides, F. thapsinum, F. subglutinans, F. andiyazi, F. globosum, F. fujikoroi and F. oxysporum. The data demonstrate that these SSRs can be used for characterization of F. proliferatum isolates from diverse hosts and geographic locations and that they are transferable to other species of Fusarium.
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Affiliation(s)
- I Moncrief
- Oklahoma State University, Stillwater, OK, United States
| | - C Garzon
- Oklahoma State University, Stillwater, OK, United States
| | - S Marek
- Oklahoma State University, Stillwater, OK, United States
| | - J Stack
- Kansas State University, Manhattan, KS, United States
| | - A Gamliel
- Laboratory for Pest management Research, Institute of Agricultural Engineering ARO, The Volcani Center, Bet Dagan, Israel
| | - P Garrido
- Oklahoma State University, Stillwater, OK, United States
| | - F Proaño
- Oklahoma State University, Stillwater, OK, United States
| | - M Gard
- Oklahoma State University, Stillwater, OK, United States
| | | | - J Fletcher
- Oklahoma State University, Stillwater, OK, United States
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Marek S, Hwang K, Foran W, Hallquist MN, Luna B. The Contribution of Network Organization and Integration to the Development of Cognitive Control. PLoS Biol 2015; 13:e1002328. [PMID: 26713863 PMCID: PMC4694653 DOI: 10.1371/journal.pbio.1002328] [Citation(s) in RCA: 194] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Accepted: 11/12/2015] [Indexed: 01/19/2023] Open
Abstract
Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. This study reveals that although the organization of functional brain networks remains stable during adolescence, between-network integration continues to increase, underlying maturation in cognitive control. Adolescence is a unique period of brain development, with major changes occurring across the brain at many different levels of brain functioning. At the macroscopic level, the brain is composed of individual regions that collaborate in networks to perform diverse cognitive functions. Some networks of brain regions perform lower-level sensorimotor processing, while other networks orchestrate more complex functions, such as cognitive control. The affiliation of each region to a network is referred to as network organization. Brain regions not only can communicate with other regions belonging to their own network but also with regions in other networks. Brain regions that communicate with regions belonging to other networks display a high level of integration since they link their network with another network. We found that during adolescence, network organization does not change. However, integration continues to increase, underscoring the notion that brain function becomes more distributed and collaborative during this unique period of development. Furthermore, this increased network integration underlies improvements in cognitive control. Thus, we provide a network-based account for improvements in cognitive functioning during adolescence.
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Affiliation(s)
- Scott Marek
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
| | - Kai Hwang
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, United States of America
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Michael N. Hallquist
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Psychology, The Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Beatriz Luna
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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Kloos M, Marek S, Kuettner EB, Kirchberger J, Schöneberg T, Sträter N. Structural basis of allosteric regulation of eukaryotic phosphofructokinases. Acta Crystallogr A 2011. [DOI: 10.1107/s0108767311093366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Cheung NW, Cinnadaio N, Russo M, Marek S. A pilot randomised controlled trial of resistance exercise bands in the management of sedentary subjects with type 2 diabetes. Diabetes Res Clin Pract 2009; 83:e68-71. [PMID: 19157617 DOI: 10.1016/j.diabres.2008.12.009] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2008] [Revised: 12/09/2008] [Accepted: 12/12/2008] [Indexed: 11/23/2022]
Abstract
We conducted a 4-month randomised controlled trial of home-based resistance training using exercise bands, amongst people with type 2 diabetes and co-morbidities limiting aerobic exercise capacity. The intervention did not improve HbA1c, anthropometric variables or functional capacity. We conclude that short-term use of exercise bands does not improve glycaemic control.
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Affiliation(s)
- N W Cheung
- Centre for Diabetes & Endocrinology Research, Westmead Hospital, Westmead, NSW 2145, Australia.
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Stein W, Marek S, Misselwitz B, Kühnert M, Reitz D, Schmidt S. Maternale und fetale Einflussfaktoren auf den Geburtsmodus von Zwillingen ≥ 34. Schwangerschaftswoche - Eine bevölkerungsbasierte Kohortenanalyse. Geburtshilfe Frauenheilkd 2007. [DOI: 10.1055/s-2007-965049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Marek S, Bock K, Hellmeyer L, Stein W, Schmidt S. Herkunft und Bedeutung von Leptin und Neuropeptid Y (NPY) im Fruchtwasser zwischen der 14. - 18. Schwangerschaftswoche. Z Geburtshilfe Neonatol 2006; 210:208-12. [PMID: 17206555 DOI: 10.1055/s-2006-957074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
INTRODUCTION Leptin and neuropeptide Y (NPY) play important roles in the regulation of food intake, energy expenditure, hematopoesis and reproduction. The biological functions of leptin and NPY in fetal development, and their regulation during pregnancy by fetal and maternal factors remain poorly understood. PATIENTS AND METHODS From 55 women undergoing diagnostic amniocentesis between the 14th and 18th weeks of gestation samples of amniotic fluid were collected. In accord with the circadian rhythm of leptin secretion all amniocenteses were performed between 8.00 and 12.00 a. m. The concentrations of leptin and NPY in amniotic fluid were analysed using commercially available RIA's. RESULTS The amniotic fluid samples of 32 male and 23 female fetuses were determined and demonstrated no gender-dependent differences in leptin and NPY levels. No correlation was found between leptin/NPY and the maternal body mass index. NPY concentrations are lower in advanced gestational age pregnancies. Leptin levels revealed no differences with respect to gestational age. CONCLUSION Leptin and NPY levels were independent of fetal gender and maternal BMI. This provides clues for alternative regulatory mechanisms in leptin and NPY secretion. Compared to the data of adults, our findings show high leptin concentrations in the amniotic fluid in the presence of only minor amounts of white adipose tissues which might include the placenta. Our data including the observation of lower levels of NPY in more advanced gestational age support the idea of specific factors regulating leptin and NPY secretion into the amniotic fluid.
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Affiliation(s)
- S Marek
- Klinik für Geburtshilfe und Perinatalmedizin der Philipps-Universität Marburg, Pilgrimstein 3, 35037 Marburg.
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Marek S, Ermisch S, Stein W, Schmidt S. Polyhydramnnion: Differentialdiagnose bei höhergradigem fetalen vesicoureteralem Reflux. Z Geburtshilfe Neonatol 2005. [DOI: 10.1055/s-2005-923147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Marek S, Tekesin I, Hellmeyer L, Kömhoff M, Seyberth HW, Maier RF, Schmidt S. Differenzialdiagnose des Polyhydramnions beim Hyperprostaglandin-E-Syndrom: Case-Report. Z Geburtshilfe Neonatol 2004; 208:232-5. [PMID: 15647987 DOI: 10.1055/s-2004-835870] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
INTRODUCTION A polyhydramnion is diagnosed in 0.4 to 3.3 % of all pregnancies. The most common causes of increased amniotic fluid include maternal diabetes mellitus, fetal malformations and chromosomal aberrations, twin-to-twin transfusion syndrome, rhesus incompatibility syndrome, and congenital infections. After exclusion of other etiologies for polyhydramnion, the very rare, autosomal-recessive transferred hyperprostaglandin E syndrome (HPS) has to be considered. PATIENTS AND METHODS We report on a 31-year-old women who visited our obstetrical outpatient clinics at 22 + 4 weeks of gestation for prenatal ultrasound scanning and amniocentesis. This, the patient's third pregnancy had been without complications so far. She had delivered two children before, one of them bearing the HPS. The women herself suffered from epilepsy. At 26 + 0 weeks of gestation the pregnancy was complicated by a polyhydramnion requiring serial amniocentesis for reducing amniotic fluid load. Among others, her amniotic fluid was analyzed for chloride concentration and for genetic aberrations regarding HPS. Serological investigations and an oral glucose tolerance test (oGTT) were performed. RESULTS Amniocentesis revealed a normal chromosomal pattern. The oGTT demonstrated values in the normal range. Serological investigations regarding TORCH infections were without pathological findings. The chloride concentration was highly increased in the amniotic fluid, which is suspicious for HPS. Finally, molecular analysis proved an NKCC2-mutation responsible for HPS. A cesarean section was performed at 33 + 3 weeks of gestation. CONCLUSION If HPS is suspected to be the cause of polyhydramnions, the chloride concentrations in the amniotic fluid and molecular analysis for HPS should be performed. Interdisciplinary care, diagnostics and therapy in an experienced perinatal center are essential for an optimal outcome of the pregnancy and the newborn infant.
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Affiliation(s)
- S Marek
- Klinikum der Philipps-Universität Marburg, Klinik für Geburtshilfe und Perinatalmedizin, Marburg.
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Washo-Stultz D, Crowley C, Payne CM, Bernstein C, Marek S, Gerner EW, Bernstein H. Increased susceptibility of cells to inducible apoptosis during growth from early to late log phase: an important caveat for in vitro apoptosis research. Toxicol Lett 2000; 116:199-207. [PMID: 10996481 DOI: 10.1016/s0378-4274(00)00225-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The physiologic mode of cell death known as apoptosis has become a major focus of scientific research due to its biologic importance. Much of this research involves cells grown in culture, where induction of apoptosis is achieved through a variety of agents. We report that cell cultures in late log growth phase exhibit an increased susceptibility to apoptosis compared with cultures in early log growth phase when apoptosis is induced by sodium deoxycholate (NaDOC), anti-Fas antibody and cytosine-b-D-arabino-furanoside (Ara-C), three agents which induce apoptosis through different upstream mechanisms. We show that this phenomenon occurs in Jurkat lymphocytes, HT-29 and HCT-116 colon epithelial cells. We also present evidence that cell density alone does not affect NaDOC-induced apoptosis, but rather that the growth media plays a key role in increased susceptibility of cells in late log growth phase to NaDOC-induced apoptosis. These results indicate that growth phase is a variable that must be controlled in order to obtain reliable apoptosis data.
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Affiliation(s)
- D Washo-Stultz
- Department of Microbiology and Immunology, College of Medicine, University of Arizona, 85724 Tucson, AZ, USA
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Wehrmann T, Marek S, Hanisch E, Lembcke B, Caspary WF. Causes and management of recurrent biliary pain after successful nonoperative gallstone treatment. Am J Gastroenterol 1997; 92:132-8. [PMID: 8995953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To evaluate the frequency and causes of recurrent biliary colic after successful extracorporeal shock wave lithotripsy of gallstones. METHODS Follow-up of 77 patients for 2 yr (median) after complete gallstone clearance by lithotripsy and adjuvant oral litholysis. All patients with recurrent biliary colic were examined thoroughly (laboratory data, ultrasonography, gastroscopy); the examination included gallbladder motility testing. If the patients suffered from additional gastrointestinal complaints, further symptom-guided investigations (pH-metry, lactose absorption study, enteroclysis, colonic transit time, colonoscopy) were performed. Patients without documented gallstone recurrence underwent ERCP and sphincter of Oddi manometry. Cholecystectomy was advised for patients in whom gallstones recurred, and patients with sphincter of Oddi dysfunction underwent endoscopic sphincterotomy. If other gastrointestinal disorders were diagnosed, appropriate treatment was initiated. RESULTS Twenty-seven patients (35%) experienced biliary colic during follow-up. Gallstone recurrence was documented in 17 patients, and 16 of the patients who underwent cholecystectomy became symptom-free again (follow-up: 12 months). Gallbladder hypomotility was revealed in seven of the 17 patients with gallstone recurrence compared to none of the 10 patients without gallstone recurrence (p < 0.05). Microlithiasis was not detected in bile samples from the patients whose gallstones did not recur. Sphincter of Oddi dysfunction was found in four patients, and sphincterotomy cured all of them (follow-up: 9 months). Two of the remaining six patients had functional gastrointestinal disorders (reflux, constipation) and became asymptomatic after specific treatment. CONCLUSIONS Biliary colic often recurs after successful gallstone lithotripsy. Recurrent gallbladder stones are the main cause, but another cause is sphincter of Oddi dysfunction. Neither gallbladder hypomotility nor microlithiasis seems to cause biliary symptoms in patients without recurrence of gallstones.
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Affiliation(s)
- T Wehrmann
- Department of Internal Medicine II, J. W. Goethe University Hospital, Frankfurt, Germany
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Wolf C, Mertz D, Marek S, Thorpe D. What are the keys to retaining administrators in long-term care? Contemp Longterm Care 1992; 15:30, 86, 106. [PMID: 10121936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
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Herzig B, Marek S. [On the question of therapeutic tactics in polytraumatism of small surgical wards (author's transl)]. Acta Chir Orthop Traumatol Cech 1975; 42:180-6. [PMID: 1136660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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