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Fortunato JE, Laurienti PJ, Wagoner AL, Shaltout HA, Diz DI, Silfer JL, Burdette JH. Children with chronic nausea and orthostatic intolerance have unique brain network organization: A case-control trial. Neurogastroenterol Motil 2022; 34:e14271. [PMID: 34606665 DOI: 10.1111/nmo.14271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 08/19/2021] [Accepted: 08/31/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND Determine whether subjects with chronic nausea and orthostatic intolerance share common alterations in key brain networks associated with central autonomic control: default mode, salience, and central executive networks, and the insula, a key component of the salience network. METHODS Ten subjects (ages 12-18 years; 8 females, 2 males) with nausea predominant dyspepsia, orthostatic intolerance, and abnormal head-upright tilt test were consecutively recruited from pediatric gastroenterology clinic. These subjects were compared with healthy controls (n = 8) without GI symptoms or orthostatic intolerance. Resting-state fMRI and brain network modularity analyses were performed. Differences in the default mode, salience, and central executive networks, and insular connectivity were measured. KEY RESULTS The community structure of the default mode network and salience network was significantly different between tilt-abnormal children and controls (p = 0.034 and 0.012, respectively), whereas, no group difference was observed in the central executive network (p = 0.48). The default mode network was more consistently "intact," and the consistency of the community structure in the salience network was reduced in tilt-abnormal children, especially in the insula. CONCLUSIONS AND INFERENCES Children with chronic nausea and orthostatic intolerance have altered connectivity in the default mode network and salience network/insula, which supports over-monitoring of their body and altered processing of bodily states resulting in interoceptive hyper self-awareness. The connectivity of the salience network would not support optimal regulation of appropriate attention to internal and external stimuli, and the hyper-connected default mode network may result in a persistent self-referential state with feelings of emotion, pain, and anxiety.
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Affiliation(s)
- John E Fortunato
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.,Section of Pediatric Gastroenterology, Hepatology and Nutrition, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, USA.,Hypertension and Vascular Research Center, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Paul J Laurienti
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Ashley L Wagoner
- Hypertension and Vascular Research Center, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Hossam A Shaltout
- Hypertension and Vascular Research Center, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Debra I Diz
- Hypertension and Vascular Research Center, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jessy L Silfer
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jonathan H Burdette
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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2
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Geib BR, Stanley ML, Wing EA, Laurienti PJ, Cabeza R. Hippocampal Contributions to the Large-Scale Episodic Memory Network Predict Vivid Visual Memories. Cereb Cortex 2018; 27:680-693. [PMID: 26523034 DOI: 10.1093/cercor/bhv272] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A common approach in memory research is to isolate the function(s) of individual brain regions, such as the hippocampus, without addressing how those regions interact with the larger network. To investigate the properties of the hippocampus embedded within large-scale networks, we used functional magnetic resonance imaging and graph theory to characterize complex hippocampal interactions during the active retrieval of vivid versus dim visual memories. The study yielded 4 main findings. First, the right hippocampus displayed greater communication efficiency with the network (shorter path length) and became a more convergent structure for information integration (higher centrality measures) for vivid than dim memories. Second, vivid minus dim differences in our graph theory measures of interest were greater in magnitude for the right hippocampus than for any other region in the 90-region network. Moreover, the right hippocampus significantly reorganized its set of direct connections from dim to vivid memory retrieval. Finally, beyond the hippocampus, communication throughout the whole-brain network was more efficient (shorter global path length) for vivid than dim memories. In sum, our findings illustrate how multivariate network analyses can be used to investigate the roles of specific regions within the large-scale network, while also accounting for global network changes.
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Affiliation(s)
- Benjamin R Geib
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Matthew L Stanley
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Erik A Wing
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Paul J Laurienti
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Roberto Cabeza
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
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3
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Geib BR, Stanley ML, Dennis NA, Woldorff MG, Cabeza R. From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval. Hum Brain Mapp 2017; 38:2242-2259. [PMID: 28112460 PMCID: PMC5460662 DOI: 10.1002/hbm.23518] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Revised: 12/19/2016] [Accepted: 01/04/2017] [Indexed: 01/21/2023] Open
Abstract
Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Benjamin R. Geib
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth Carolina
| | - Matthew L. Stanley
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth Carolina
| | - Nancy A. Dennis
- Department of PsychologyPennsylvania State UniversityUniversity ParkPennsylvania
| | - Marty G. Woldorff
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth Carolina
| | - Roberto Cabeza
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth Carolina
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4
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Bolt T, Nomi JS, Rubinov M, Uddin LQ. Correspondence between evoked and intrinsic functional brain network configurations. Hum Brain Mapp 2017; 38:1992-2007. [PMID: 28052450 DOI: 10.1002/hbm.23500] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 12/14/2016] [Accepted: 12/14/2016] [Indexed: 02/01/2023] Open
Abstract
Much of the literature exploring differences between intrinsic and task-evoked brain architectures has examined changes in functional connectivity patterns between specific brain regions. While informative, this approach overlooks important overall functional changes in hub organization and network topology that may provide insights about differences in integration between intrinsic and task-evoked states. Examination of changes in overall network organization, such as a change in the concentration of hub nodes or a quantitative change in network organization, is important for understanding the underlying processes that differ between intrinsic and task-evoked brain architectures. The present study used graph-theoretical techniques applied to publicly available neuroimaging data collected from a large sample of individuals (N = 202), and a within-subject design where resting-state and several task scans were collected from each participant as part of the Human Connectome Project. We demonstrate that differences between intrinsic and task-evoked brain networks are characterized by a task-general shift in high-connectivity hubs from primarily sensorimotor/auditory processing areas during the intrinsic state to executive control/salience network areas during task performance. In addition, we demonstrate that differences between intrinsic and task-evoked architectures are associated with changes in overall network organization, such as increases in network clustering, global efficiency and integration between modules. These findings offer a new perspective on the principles guiding functional brain organization by identifying unique and divergent properties of overall network organization between the resting-state and task performance. Hum Brain Mapp 38:1992-2007, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Taylor Bolt
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Mikail Rubinov
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, Florida
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5
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Abstract
Neural reuse allegedly stands in stark contrast against a modular view of the brain. However, the development of unique modularity algorithms in network science has provided the means to identify functionally cooperating, specialized subsystems in a way that remains consistent with the neural reuse view and offers a set of rigorous tools to fully engage in Anderson's (2014) research program.
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6
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Mayhugh RE, Moussa MN, Simpson SL, Lyday RG, Burdette JH, Porrino LJ, Laurienti PJ. Moderate-Heavy Alcohol Consumption Lifestyle in Older Adults Is Associated with Altered Central Executive Network Community Structure during Cognitive Task. PLoS One 2016; 11:e0160214. [PMID: 27494180 PMCID: PMC4975417 DOI: 10.1371/journal.pone.0160214] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 07/16/2016] [Indexed: 01/21/2023] Open
Abstract
Older adults today consume more alcohol than previous generations, the majority being social drinkers. The effects of heavy alcohol use on brain functioning closely resemble age-related changes, but it is not known if moderate-heavy alcohol consumption intensifies brain aging. Whether a lifestyle of moderate-heavy alcohol use in older adults increased age-related brain changes was examined. Forty-one older adults (65–80 years) that consumed light (< 2 drinks/week and ≥ 1 drink/month, n = 20) or moderate-heavy (7–21 drinks/week, non-bingers, n = 21) amounts of alcohol were enrolled. Twenty-two young adults (24–35 years) were also enrolled (light, n = 11 and moderate-heavy, n = 11). Functional brain networks based on magnetic resonance imaging data were generated for resting state and during a working memory task. Whole-brain, Central Executive Network (CEN), and Default Mode Network (DMN) connectivity were assessed in light and moderate-heavy alcohol consuming older adults with comparisons to young adults. The older adults had significantly lower whole brain connectivity (global efficiency) and lower regional connectivity (community structure) in the CEN during task and in the DMN at rest. Moderate-heavy older drinkers did not exhibit whole brain connectivity differences compared to the low drinkers. However, decreased CEN connectivity was observed during the task. There were no differences in the DMN connectivity between drinking groups. Taken together, a lifestyle including moderate-heavy alcohol consumption may be associated with further decreases in brain network connectivity within task-related networks in older adults. Further research is required to determine if this decrease is compensatory or an early sign of decline.
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Affiliation(s)
- Rhiannon E. Mayhugh
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Neuroscience Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Malaak N. Moussa
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Neuroscience Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Sean L. Simpson
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Robert G. Lyday
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jonathan H. Burdette
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Linda J. Porrino
- Department of Physiology and Pharmacology, Wake Forest School Medicine, Winston-Salem, North Carolina, United States of America
| | - Paul J. Laurienti
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail:
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7
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Changes in brain network efficiency and working memory performance in aging. PLoS One 2015; 10:e0123950. [PMID: 25875001 PMCID: PMC4395305 DOI: 10.1371/journal.pone.0123950] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2014] [Accepted: 03/09/2015] [Indexed: 01/25/2023] Open
Abstract
Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.
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8
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Stanley ML, Dagenbach D, Lyday RG, Burdette JH, Laurienti PJ. Changes in global and regional modularity associated with increasing working memory load. Front Hum Neurosci 2014; 8:954. [PMID: 25520639 PMCID: PMC4249452 DOI: 10.3389/fnhum.2014.00954] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Accepted: 11/10/2014] [Indexed: 11/13/2022] Open
Abstract
Using graph theory measures common to complex network analyses of neuroimaging data, the objective of this study was to explore the effects of increasing working memory processing load on functional brain network topology in a cohort of young adults. Measures of modularity in complex brain networks quantify how well a network is organized into densely interconnected communities. We investigated changes in both the large-scale modular organization of the functional brain network as a whole and regional changes in modular organization as demands on working memory increased from n = 1 to n = 2 on the standard n-back task. We further investigated the relationship between modular properties across working memory load conditions and behavioral performance. Our results showed that regional modular organization within the default mode and working memory circuits significantly changed from 1-back to 2-back task conditions. However, the regional modular organization was not associated with behavioral performance. Global measures of modular organization did not change with working memory load but were associated with individual variability in behavioral performance. These findings indicate that regional and global network properties are modulated by different aspects of working memory under increasing load conditions. These findings highlight the importance of assessing multiple features of functional brain network topology at both global and regional scales rather than focusing on a single network property.
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Affiliation(s)
- Matthew L Stanley
- Laboratory for Complex Brain Networks, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - Dale Dagenbach
- Laboratory for Complex Brain Networks, Wake Forest University School of Medicine Winston-Salem, NC, USA ; Department of Psychology, Wake Forest University Winston-Salem, NC, USA
| | - Robert G Lyday
- Laboratory for Complex Brain Networks, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - Jonathan H Burdette
- Laboratory for Complex Brain Networks, Wake Forest University School of Medicine Winston-Salem, NC, USA ; Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - Paul J Laurienti
- Laboratory for Complex Brain Networks, Wake Forest University School of Medicine Winston-Salem, NC, USA ; Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA
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