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Han H, Jiang J, Gu L, Gan JQ, Wang H. Brain connectivity patterns derived from aging-related alterations in dynamic brain functional networks and their potential as features for brain age classification. J Neural Eng 2024; 21:026015. [PMID: 38479020 DOI: 10.1088/1741-2552/ad33b1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 03/13/2024] [Indexed: 03/26/2024]
Abstract
Objective.Recent studies have demonstrated that the analysis of brain functional networks (BFNs) is a powerful tool for exploring brain aging and age-related neurodegenerative diseases. However, investigating the mechanism of brain aging associated with dynamic BFN is still limited. The purpose of this study is to develop a novel scheme to explore brain aging patterns by constructing dynamic BFN using resting-state functional magnetic resonance imaging data.Approach.A dynamic sliding-windowed non-negative block-diagonal representation (dNBDR) method is proposed for constructing dynamic BFN, based on which a collection of dynamic BFN measures are suggested for examining age-related differences at the group level and used as features for brain age classification at the individual level.Results.The experimental results reveal that the dNBDR method is superior to the sliding time window with Pearson correlation method in terms of dynamic network structure quality. Additionally, significant alterations in dynamic BFN structures exist across the human lifespan. Specifically, average node flexibility and integration coefficient increase with age, while the recruitment coefficient shows a decreased trend. The proposed feature extraction scheme based on dynamic BFN achieved the highest accuracy of 78.7% in classifying three brain age groups.Significance. These findings suggest that dynamic BFN measures, dynamic community structure metrics in particular, play an important role in quantitatively assessing brain aging.
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Affiliation(s)
- Hongfang Han
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, People's Republic of China
| | - Jiuchuan Jiang
- School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210003, Jiangsu, People's Republic of China
| | - Lingyun Gu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, People's Republic of China
| | - John Q Gan
- School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, United Kingdom
| | - Haixian Wang
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, People's Republic of China
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Greenwood PB, DeSerisy M, Koe E, Rodriguez E, Salas L, Perera FP, Herbstman J, Pagliaccio D, Margolis AE. Combined and sequential exposure to prenatal second hand smoke and postnatal maternal distress is associated with cingulo-opercular global efficiency and attention problems in school-age children. Neurotoxicol Teratol 2024; 102:107338. [PMID: 38431065 DOI: 10.1016/j.ntt.2024.107338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 02/27/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND Prenatal exposure to secondhand (environmental) tobacco smoke (SHS) is associated with adverse neurodevelopmental outcomes, including altered functional activation of cognitive control brain circuitry and increased attention problems in children. Exposure to SHS is more common among Black youth who are also disproportionately exposed to socioeconomic disadvantage and concomitant maternal distress. We examine the combined effects of exposure to prenatal SHS and postnatal maternal distress on the global efficiency (GE) of the brain's cingulo-opercular (CO) and fronto-parietal control (FP) networks in childhood, as well as associated attention problems. METHODS Thirty-two children of non-smoking mothers followed in a prospective longitudinal birth cohort at the Columbia Center for Children's Environmental Health (CCCEH) completed magnetic resonance imaging (MRI) at ages 7-9 years old. GE scores were extracted from general connectivity data collected while children completed the Simon Spatial Incompatibility functional magnetic resonance imaging (fMRI) task. Prenatal SHS was measured using maternal urinary cotinine from the third trimester; postnatal maternal distress was assessed at child age 5 using the Psychiatric Epidemiology Research Interview (PERI-D). The Child Behavior Checklist (CBCL) measured Attention and Attention Deficit Hyperactivity Disorder (ADHD) problems at ages 7-9. Linear regressions examined the interaction between prenatal SHS and postnatal maternal distress on the GE of the CO or FP networks, as well as associations between exposure-related network alterations and attention problems. All models controlled for age, sex, maternal education at prenatal visit, race/ethnicity, global brain correlation, and mean head motion. RESULTS The prenatal SHS by postnatal maternal distress interaction term associated with the GE of the CO network (β = 0.673, Bu = 0.042, t(22) = 2.427, p = .024, D = 1.42, 95% CI [0.006, 0.079], but not the FP network (β = 0.138, Bu = 0.006, t(22) = 0.434, p = .668, 95% CI [-0.022, 0.033]). Higher GE of the CO network was associated with more attention problems (β = 0.472, Bu = 43.076, t(23) = 2.780, p = .011, D = 1.74, n = 31, 95% CI [11.024, 75.128], n = 31) and ADHD risk (β = 0.436, Bu = 21.961, t(29) = 2.567, p = .018, D = 1.81, 95% CI [4.219, 39.703], n = 30). CONCLUSIONS These preliminary findings suggest that sequential prenatal SHS exposure and postnatal maternal distress could alter the efficiency of the CO network and increase risk for downstream attention problems and ADHD. These findings are consistent with prior studies showing that prenatal SHS exposure is associated with altered function of brain regions that support cognitive control and with ADHD problems. Our model also identifies postnatal maternal distress as a significant moderator of this association. These data highlight the combined neurotoxic effects of exposure to prenatal SHS and postnatal maternal distress. Critically, such exposures are disproportionately distributed among youth from minoritized groups, pointing to potential pathways to known mental health disparities.
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Affiliation(s)
- Paige B Greenwood
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Mariah DeSerisy
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Emily Koe
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Elizabeth Rodriguez
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Leilani Salas
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Frederica P Perera
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Julie Herbstman
- Department of Environmental Health Sciences and Columbia Center for Children's Environmental Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - David Pagliaccio
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Amy E Margolis
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA.
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3
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Lima Santos JP, Hayes R, Franzen PL, Goldstein TR, Hasler BP, Buysse DJ, Siegle GJ, Dahl RE, Forbes EE, Ladouceur CD, McMakin DL, Ryan ND, Silk JS, Jalbrzikowski M, Soehner AM. The association between cortical gyrification and sleep in adolescents and young adults. Sleep 2024; 47:zsad282. [PMID: 37935899 PMCID: PMC10782503 DOI: 10.1093/sleep/zsad282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/06/2023] [Indexed: 11/09/2023] Open
Abstract
STUDY OBJECTIVES Healthy sleep is important for adolescent neurodevelopment, and relationships between brain structure and sleep can vary in strength over this maturational window. Although cortical gyrification is increasingly considered a useful index for understanding cognitive and emotional outcomes in adolescence, and sleep is also a strong predictor of such outcomes, we know relatively little about associations between cortical gyrification and sleep. We aimed to identify developmentally invariant (stable across age) or developmentally specific (observed only during discrete age intervals) gyrification-sleep relationships in young people. METHODS A total of 252 Neuroimaging and Pediatric Sleep Databank participants (9-26 years; 58.3% female) completed wrist actigraphy and a structural MRI scan. Local gyrification index (lGI) was estimated for 34 bilateral brain regions. Naturalistic sleep characteristics (duration, timing, continuity, and regularity) were estimated from wrist actigraphy. Regularized regression for feature selection was used to examine gyrification-sleep relationships. RESULTS For most brain regions, greater lGI was associated with longer sleep duration, earlier sleep timing, lower variability in sleep regularity, and shorter time awake after sleep onset. lGI in frontoparietal network regions showed associations with sleep patterns that were stable across age. However, in default mode network regions, lGI was only associated with sleep patterns from late childhood through early-to-mid adolescence, a period of vulnerability for mental health disorders. CONCLUSIONS We detected both developmentally invariant and developmentally specific ties between local gyrification and naturalistic sleep patterns. Default mode network regions may be particularly susceptible to interventions promoting more optimal sleep during childhood and adolescence.
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Affiliation(s)
| | - Rebecca Hayes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peter L Franzen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tina R Goldstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Greg J Siegle
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ronald E Dahl
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Erika E Forbes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Dana L McMakin
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Neal D Ryan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jennifer S Silk
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Adriane M Soehner
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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4
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Santos JPL, Hayes R, Franzen PL, Goldstein TR, Hasler BP, Buysse DJ, Siegle GJ, Dahl RE, Forbes EE, Ladouceur CD, McMakin DL, Ryan ND, Silk JS, Jalbrzikowski M, Soehner AM. The association between cortical gyrification and sleep in adolescents and young adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.15.557966. [PMID: 37745609 PMCID: PMC10516006 DOI: 10.1101/2023.09.15.557966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Study objectives Healthy sleep is important for adolescent neurodevelopment, and relationships between brain structure and sleep can vary in strength over this maturational window. Although cortical gyrification is increasingly considered a useful index for understanding cognitive and emotional outcomes in adolescence, and sleep is also a strong predictor of such outcomes, we know relatively little about associations between cortical gyrification and sleep. Methods Using Local gyrification index (lGI) of 34 bilateral brain regions and regularized regression for feature selection, we examined gyrification-sleep relationships in the Neuroimaging and Pediatric Sleep databank (252 participants; 9-26 years; 58.3% female) and identified developmentally invariant (stable across age) or developmentally specific (observed only during discrete age intervals) brain-sleep associations. Naturalistic sleep characteristics (duration, timing, continuity, and regularity) were estimated from wrist actigraphy. Results For most brain regions, greater lGI was associated with longer sleep duration, earlier sleep timing, lower variability in sleep regularity, and shorter time awake after sleep onset. lGI in frontoparietal network regions showed associations with sleep patterns that were stable across age. However, in default mode network regions, lGI was only associated with sleep patterns from late childhood through early-to-mid adolescence, a period of vulnerability for mental health disorders. Conclusions We detected both developmentally invariant and developmentally specific ties between local gyrification and naturalistic sleep patterns. Default mode network regions may be particularly susceptible to interventions promoting more optimal sleep during childhood and adolescence.
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Affiliation(s)
| | - Rebecca Hayes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peter L Franzen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tina R Goldstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Greg J Siegle
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ronald E Dahl
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Erika E Forbes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Dana L McMakin
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Neal D Ryan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jennifer S Silk
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Adriane M Soehner
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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Hormovas J, Dadario NB, Tang SJ, Nicholas P, Dhanaraj V, Young I, Doyen S, Sughrue ME. Parcellation-Based Connectivity Model of the Judgement Core. J Pers Med 2023; 13:1384. [PMID: 37763153 PMCID: PMC10532823 DOI: 10.3390/jpm13091384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation.
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Affiliation(s)
- Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St., New Brunswick, NJ 08901, USA;
| | - Si Jie Tang
- School of Medicine, 21772 University of California Davis Medical Center, 2315 Stockton Blvd., Sacramento, CA 95817, USA
| | - Peter Nicholas
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Vukshitha Dhanaraj
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
| | - Isabella Young
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Stephane Doyen
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
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6
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Son JJ, Schantell M, Picci G, Wang YP, Stephen JM, Calhoun VD, Doucet GE, Taylor BK, Wilson TW. Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms. Dev Cogn Neurosci 2023; 60:101216. [PMID: 36857850 PMCID: PMC9986502 DOI: 10.1016/j.dcn.2023.101216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/08/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
The default mode network (DMN) plays a crucial role in internal self-processing, rumination, and social functions. Disruptions to DMN connectivity have been linked with early adversity and the emergence of psychopathology in adolescence and early adulthood. Herein, we investigate how subclinical psychiatric symptoms can impact DMN functional connectivity during the pubertal transition. Resting-state fMRI data were collected annually from 190 typically-developing youth (9-15 years-old) at three timepoints and within-network DMN connectivity was computed. We used latent growth curve modeling to determine how self-reported depressive and posttraumatic stress symptoms predicted rates of change in DMN connectivity over the three-year period. In the baseline model without predictors, we found no systematic changes in DMN connectivity over time. However, significant modulation emerged after adding psychopathology predictors; greater depressive symptomatology was associated with significant decreases in connectivity over time, whereas posttraumatic stress symptoms were associated with significant increases in connectivity over time. Follow-up analyses revealed that these effects were driven by connectivity changes involving the dorsal medial prefrontal cortex subnetwork. In conclusion, these data suggest that subclinical depressive and posttraumatic symptoms alter the trajectory of DMN connectivity, which may indicate that this network is a nexus of clinical significance in mental health disorders.
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Affiliation(s)
- Jake J Son
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of technology, and Emory University, Atlanta, GA, USA
| | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA.
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7
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Tarchi L, Damiani S, Vittori PLT, Frick A, Castellini G, Politi P, Fusar-Poli P, Ricca V. Progressive Voxel-Wise Homotopic Connectivity from childhood to adulthood: Age-related functional asymmetry in resting-state functional magnetic resonance imaging. Dev Psychobiol 2023; 65:e22366. [PMID: 36811370 DOI: 10.1002/dev.22366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 10/11/2022] [Accepted: 09/21/2022] [Indexed: 01/12/2023]
Abstract
Homotopic connectivity during resting state has been proposed as a risk marker for neurologic and psychiatric conditions, but a precise characterization of its trajectory through development is currently lacking. Voxel-Mirrored Homotopic Connectivity (VMHC) was evaluated in a sample of 85 neurotypical individuals aged 7-18 years. VMHC associations with age, handedness, sex, and motion were explored at the voxel-wise level. VMHC correlates were also explored within 14 functional networks. Primary and secondary outcomes were repeated in a sample of 107 adults aged 21-50 years. In adults, VMHC was negatively correlated with age only in the posterior insula (false discovery rate p < .05, >30-voxel clusters), while a distributed effect among the medial axis was observed in minors. Four out of 14 considered networks showed significant negative correlations between VMHC and age in minors (basal ganglia r = -.280, p = .010; anterior salience r = -.245, p = .024; language r = -.222, p = .041; primary visual r = -.257, p = .017), but not adults. In minors, a positive effect of motion on VMHC was observed only in the putamen. Sex did not significantly influence age effects on VMHC. The current study showed a specific decrease in VMHC for minors as a function of age, but not adults, supporting the notion that interhemispheric interactions can shape late neurodevelopment.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy
| | - Stefano Damiani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | | | - Andreas Frick
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy
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8
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Davis K, Hirsch E, Gee D, Andover M, Roy AK. Mediating role of the default mode network on parental acceptance/warmth and psychopathology in youth. Brain Imaging Behav 2022; 16:2229-2238. [PMID: 35648269 DOI: 10.1007/s11682-022-00692-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2022] [Indexed: 11/25/2022]
Abstract
Humans are reliant on their caregivers for an extended period of time, offering numerous opportunities for environmental factors, such as parental attitudes and behaviors, to impact brain development. The default mode network is a neural system encompassing the medial prefrontal cortex, posterior cingulate cortex, precuneus, and temporo-parietal junction, which is implicated in aspects of cognition and psychopathology. Delayed default mode network maturation in children and adolescents has been associated with greater general dimensional psychopathology, and positive parenting behaviors have been suggested to serve as protective mechanisms against atypical default mode network development. The current study aimed to extend the existing research by examining whether within- default mode network resting-state functional connectivity would mediate the relation between parental acceptance/warmth and youth psychopathology. Data from the Adolescent Brain and Cognitive Development study, which included a community sample of 9,366 children ages 8.9-10.9 years, were analyzed to test this prediction. Results demonstrated a significant mediation, where greater parental acceptance/warmth predicted greater within- default mode network resting-state functional connectivity, which in turn predicted lower externalizing, but not internalizing symptoms, at baseline and 1-year later. Our study provides preliminary support for the notion that positive parenting behaviors may reduce the risk for psychopathology in youth through their influence on the default mode network.
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9
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Gombos F, Bódizs R, Pótári A, Bocskai G, Berencsi A, Szakács H, Kovács I. Topographical relocation of adolescent sleep spindles reveals a new maturational pattern in the human brain. Sci Rep 2022; 12:7023. [PMID: 35487959 PMCID: PMC9054798 DOI: 10.1038/s41598-022-11098-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 04/18/2022] [Indexed: 11/23/2022] Open
Abstract
Current theories of human neural development emphasize the posterior-to-anterior pattern of brain maturation. However, this scenario leaves out significant brain areas not directly involved with sensory input and behavioral control. Suggesting the relevance of cortical activity unrelated to sensory stimulation, such as sleep, we investigated adolescent transformations in the topography of sleep spindles. Sleep spindles are known to be involved in neural plasticity and in adults have a bimodal topography: slow spindles are frontally dominant, while fast spindles have a parietal/precuneal origin. The late functional segregation of the precuneus from the frontoparietal network during adolescence suggests that spindle topography might approach the adult state relatively late in development, and it may not be a result of the posterior-to-anterior maturational pattern. We analyzed the topographical distribution of spindle parameters in HD-EEG polysomnographic sleep recordings of adolescents and found that slow spindle duration maxima traveled from central to anterior brain regions, while fast spindle density, amplitude and frequency peaks traveled from central to more posterior brain regions. These results provide evidence for the gradual posteriorization of the anatomical localization of fast sleep spindles during adolescence and indicate the existence of an anterior-to-posterior pattern of human brain maturation.
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Affiliation(s)
- Ferenc Gombos
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Kálmán Sq., Budapest, 1088, Hungary.,Adolescent Development Research Group, Hungarian Academy of Sciences - Pázmány Péter Catholic University, Budapest, 1088, Hungary
| | - Róbert Bódizs
- Institute of Behavioural Sciences, Semmelweis University, Budapest, 1089, Hungary.,National Institute of Clinical Neurosciences, Budapest, 1145, Hungary
| | - Adrián Pótári
- Adolescent Development Research Group, Hungarian Academy of Sciences - Pázmány Péter Catholic University, Budapest, 1088, Hungary
| | - Gábor Bocskai
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Kálmán Sq., Budapest, 1088, Hungary.,Doctoral School of Mental Health Sciences, Semmelweis University, Üllői st. 26, Budapest, 1085, Hungary
| | - Andrea Berencsi
- Adolescent Development Research Group, Hungarian Academy of Sciences - Pázmány Péter Catholic University, Budapest, 1088, Hungary.,Institute for the Methodology of Special Needs Education and Rehabilitation, Bárczi Gusztáv Faculty of Special Needs Education, Eötvös Loránd University, Budapest, 1097, Hungary
| | - Hanna Szakács
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Kálmán Sq., Budapest, 1088, Hungary.,Doctoral School of Mental Health Sciences, Semmelweis University, Üllői st. 26, Budapest, 1085, Hungary
| | - Ilona Kovács
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Kálmán Sq., Budapest, 1088, Hungary. .,Adolescent Development Research Group, Hungarian Academy of Sciences - Pázmány Péter Catholic University, Budapest, 1088, Hungary. .,Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, 1117, Hungary.
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10
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Zeev-Wolf M, Dor-Ziderman Y, Pratt M, Goldstein A, Feldman R. Investigating default mode network connectivity disruption in children of mothers with depression. Br J Psychiatry 2022; 220:130-139. [PMID: 35049492 DOI: 10.1192/bjp.2021.164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Exposure to maternal major depressive disorder (MDD) bears long-term negative consequences for children's well-being; to date, no research has examined how exposure at different stages of development differentially affects brain functioning. AIMS Utilising a unique cohort followed from birth to preadolescence, we examined the effects of early versus later maternal MDD on default mode network (DMN) connectivity. METHOD Maternal depression was assessed at birth and ages 6 months, 9 months, 6 years and 10 years, to form three groups: children of mothers with consistent depression from birth to 6 years of age, which resolved by 10 years of age; children of mothers without depression; and children of mothers who were diagnosed with MDD in late childhood. In preadolescence, we used magnetoencephalography and focused on theta rhythms, which characterise the developing brain. RESULTS Maternal MDD was associated with disrupted DMN connectivity in an exposure-specific manner. Early maternal MDD decreased child connectivity, presenting a profile typical of early trauma or chronic adversity. In contrast, later maternal MDD was linked with tighter connectivity, a pattern characteristic of adult depression. Aberrant DMN connectivity was predicted by intrusive mothering in infancy and lower mother-child reciprocity and child empathy in late childhood, highlighting the role of deficient caregiving and compromised socio-emotional competencies in DMN dysfunction. CONCLUSIONS The findings pinpoint the distinct effects of early versus later maternal MDD on the DMN, a core network sustaining self-related processes. Results emphasise that research on the influence of early adversity on the developing brain should consider the developmental stage in which the adversity occured.
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Affiliation(s)
- Maor Zeev-Wolf
- Baruch Ivcher School of Psychology, Interdisciplinary Center Herzliya, Israel; and Department of Education and Zlotowski Center for Neuroscience, Ben Gurion University of the Negev, Israel
| | - Yair Dor-Ziderman
- Baruch Ivcher School of Psychology, Interdisciplinary Center Herzliya, Israel; and Edmond J. Safra Brain Research Center, University of Haifa, Israel
| | - Maayan Pratt
- Department of Education and Zlotowski Center for Neuroscience, Ben Gurion University of the Negev, Israel; and Department of Psychology and Gonda Brain Science Center, Bar-Ilan University, Israel
| | - Abraham Goldstein
- Department of Psychology and Gonda Brain Science Center, Bar-Ilan University, Israel
| | - Ruth Feldman
- Baruch Ivcher School of Psychology, Interdisciplinary Center Herzliya, Israel; and Child Study Center, Yale University, Connecticut, USA
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11
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Sato JR, Biazoli CE, Zugman A, Pan PM, Bueno APA, Moura LM, Gadelha A, Picon FA, Amaro E, Salum GA, Miguel EC, Rohde LA, Bressan RA, Jackowski AP. Long-term stability of the cortical volumetric profile and the functional human connectome throughout childhood and adolescence. Eur J Neurosci 2021; 54:6187-6201. [PMID: 34460993 DOI: 10.1111/ejn.15435] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 08/18/2021] [Accepted: 08/28/2021] [Indexed: 11/26/2022]
Abstract
There is compelling evidence showing that between-subject variability in several functional and structural brain features is sufficient for unique identification in adults. However, individuation of brain functional connectomes depends on the stabilization of neurodevelopmental processes during childhood and adolescence. Here, we aimed to (1) evaluate the intra-subject functional connectome stability over time for the whole brain and for large scale functional networks and (2) determine the long-term identification accuracy or 'fingerprinting' for the cortical volumetric profile and the functional connectome. For these purposes, we analysed a longitudinal cohort of 239 children and adolescents scanned in two sessions with an interval of approximately 3 years (age range 6-15 years at baseline and 9-18 years at follow-up). Corroborating previous results using short between-scan intervals in children and adolescents, we observed a moderate identification accuracy (38%) for the whole functional profile. In contrast, identification accuracy using cortical volumetric profile was 95%. Among the large-scale networks, the default-mode (26.8%), the frontoparietal (23.4%) and the dorsal-attention (27.6%) networks were the most discriminative. Our results provide further evidence for a protracted development of specific individual structural and functional connectivity profiles.
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Affiliation(s)
- João Ricardo Sato
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil.,Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Claudinei Eduardo Biazoli
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil.,Department of Biological and Experimental Psychology, Queen Mary University of London, London, UK
| | - André Zugman
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Pedro Mario Pan
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Ana Paula Arantes Bueno
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Luciana Monteiro Moura
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil.,Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Ary Gadelha
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Felipe Almeida Picon
- National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.,ADHD Outpatient Program & Developmental Psychiatry Program, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Edson Amaro
- National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.,Department of Radiology, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Giovanni Abrahão Salum
- National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.,ADHD Outpatient Program & Developmental Psychiatry Program, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Euripedes Constantino Miguel
- National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.,Department of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Luis Augusto Rohde
- National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.,ADHD Outpatient Program & Developmental Psychiatry Program, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Rodrigo Affonseca Bressan
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Andrea Parolin Jackowski
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
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12
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Lei T, Liao X, Chen X, Zhao T, Xu Y, Xia M, Zhang J, Xia Y, Sun X, Wei Y, Men W, Wang Y, Hu M, Zhao G, Du B, Peng S, Chen M, Wu Q, Tan S, Gao JH, Qin S, Tao S, Dong Q, He Y. Progressive Stabilization of Brain Network Dynamics during Childhood and Adolescence. Cereb Cortex 2021; 32:1024-1039. [PMID: 34378030 DOI: 10.1093/cercor/bhab263] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/14/2022] Open
Abstract
Functional brain networks require dynamic reconfiguration to support flexible cognitive function. However, the developmental principles shaping brain network dynamics remain poorly understood. Here, we report the longitudinal development of large-scale brain network dynamics during childhood and adolescence, and its connection with gene expression profiles. Using a multilayer network model, we show the temporally varying modular architecture of child brain networks, with higher network switching primarily in the association cortex and lower switching in the primary regions. This topographical profile exhibits progressive maturation, which manifests as reduced modular dynamics, particularly in the transmodal (e.g., default-mode and frontoparietal) and sensorimotor regions. These developmental refinements mediate age-related enhancements of global network segregation and are linked with the expression profiles of genes associated with the enrichment of ion transport and nucleobase-containing compound transport. These results highlight a progressive stabilization of brain dynamics, which expand our understanding of the neural mechanisms that underlie cognitive development.
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Affiliation(s)
- Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Xiaodan Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yunman Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xiaochen Sun
- Department of Linguistics, Beijing Language and Culture University, Beijing 100083, China
| | - Yongbin Wei
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Mingming Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Bin Du
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Siya Peng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Menglu Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.,Chinese Institute for Brain Research, Beijing 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.,Chinese Institute for Brain Research, Beijing 102206, China
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13
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Geng F, Xu W, Riggins T. Interactions between the hippocampus and fronto-parietal regions during memory encoding in early childhood. Hippocampus 2021; 32:108-120. [PMID: 34329507 DOI: 10.1002/hipo.23380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 05/18/2021] [Accepted: 07/19/2021] [Indexed: 11/06/2022]
Abstract
The neural mechanisms underlying memory encoding have received much attention in the literature. Research in adults and school-age children suggest that the hippocampus and cortical regions in both frontal and parietal areas are involved in successful formation of memories. Overall, the hippocampus has been shown to interact with fronto-parietal regions to collaboratively support successful memory encoding for both individual items as well as item details (such as the source or color in which the item was originally encountered). To date, only one study has investigated neural regions engaged during memory encoding in children younger than 8 years of age, which is unfortunate since early childhood is a period of dramatic improvement in memory. This previous study indicated that both the hippocampus and cortical regions are involved during the encoding of subsequently remembered item details (i.e., sources). However, this study reported few interactions between these regions, and it did not explore item memory at a more general level. To fill these gaps, this article reanalyzed data from the previous report, aiming to examine the neural correlates of item memory during encoding in early childhood (4-8 years) and interactions between the hippocampus and fronto-parietal regions during encoding. Consistent with research in older individuals, both the hippocampus and fronto-parietal regions were found to participate in item memory encoding. Additionally, functional connectivity between hippocampus and fronto-parietal regions was significantly related to both subsequent item memory and subsequent source memory. Taken together, these findings suggest that not only the activation of individual brain regions (hippocampus and fronto-parietal regions) but also the functional connections between these regions are important for memory encoding. These data add to the growing literature providing insight into how the hippocampus and cortical regions interact to support memory during development.
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Affiliation(s)
- Fengji Geng
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, People's Republic of China.,Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, People's Republic of China
| | - Wenwen Xu
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, People's Republic of China
| | - Tracy Riggins
- Department of Psychology, University of Maryland, College Park, Maryland, USA
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14
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Neuroimaging Studies of Nonsuicidal Self-Injury in Youth: A Systematic Review. Life (Basel) 2021; 11:life11080729. [PMID: 34440473 PMCID: PMC8399885 DOI: 10.3390/life11080729] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/16/2021] [Accepted: 07/19/2021] [Indexed: 01/14/2023] Open
Abstract
Nonsuicidal self-injury (NSSI) is prevalent and affects mainly the youth population. It is prospectively associated with suicide attempts, making it a target for suicide prevention. Recently, several studies have investigated neural pathways of NSSI using neuroimaging. However, there is a lack of systematized appraisal of these findings. This systematic review aims to identify and summarize the main neuroimaging findings of NSSI in youth. We followed PRISMA statement guidelines and searched MEDLINE, APA PsycInfo, and Google Scholar databases for neuroimaging studies, irrespective of imaging modality, specifically investigating NSSI in samples with a mean age of up to 25 years old. Quality assessment was made using the Newcastle–Ottawa and Joanna Briggs Institute scales. The initial search retrieved 3030 articles; 21 met inclusion criteria, with a total of 938 subjects. Eighteen studies employed functional neuroimaging techniques such as resting-state and task-based fMRI (emotional, interpersonal exposure/social exclusion, pain, reward, and cognitive processing paradigms). Three studies reported on structural MRI. An association of NSSI behavior and altered emotional processing in cortico-limbic neurocircuitry was commonly reported. Additionally, alterations in potential circuits involving pain, reward, interpersonal, self-processing, and executive function control processes were identified. NSSI has complex and diverse neural underpinnings. Future longitudinal studies are needed to understand its developmental aspects better.
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15
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Stein A, Iyer KK, Khetani AM, Barlow KM. Changes in working memory-related cortical responses following pediatric mild traumatic brain injury: A longitudinal fMRI study. JOURNAL OF CONCUSSION 2021. [DOI: 10.1177/20597002211006541] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Persistent post-concussion symptoms (PPCS) lasting longer than 4 weeks affect 25% of children with mild traumatic brain injury (mTBI) or concussion. Working memory (WM) problems are a common complaint in children with PPCS. Despite normal function on traditional neuropsychological tests, these children exhibit aberrant cortical responses within the dorsolateral prefrontal cortex (dlPFC) and default mode network (DMN) regions – both of which are implicated in WM. Using a prospective, longitudinal cohort study design, we investigated changes in cortical fMRI responses within the dlPFC and DMN during an nback WM task at two timepoints: one and two months post-injury. Across these timepoints, the primary outcome was change in cortical activations (increase in BOLD) and deactivations (decrease in BOLD) of both dlPFC and DMN. Twenty-nine children (mean age 15.49 ± 2.15; 48.3% male) with fMRI scans at both timepoints were included, following data quality control. Student’s t-tests were used to examine cortical activations across time and task difficulty. ANCOVA F-tests examined cortical responses after removal of baseline across time, task difficulty and recovery. Volumes of interest (5 mm sphere) were placed in peak voxel regions of the DMN and dlPFC to compare cortical responses between recovered and unrecovered participants over time (one-way ANOVA). Between one and two months post-injury, we found significant increases in dlPFC activations and significant activations and deactivations in the DMN with increasing task difficulty, alongside improved task performance. Cortical responses of the DMN and bilateral dlPFC displayed increased intensity in recovered participants, together with improved attention and behavioural symptoms. Overall, our findings suggest evidence of neural compensation and ongoing cognitive recovery from pediatric TBI over time between one and two months post injury in children with PPCS. These results highlight the wider and persisting implications of mTBI in children, whose maturing brains are particularly vulnerable to TBI.
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Affiliation(s)
- Athena Stein
- Acquired Brain Injury in Children Research Program, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Kartik K Iyer
- Acquired Brain Injury in Children Research Program, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Aneesh M Khetani
- Department of Pediatrics, University of Calgary, Calgary, Canada
| | - Karen M Barlow
- Acquired Brain Injury in Children Research Program, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- Department of Pediatrics, University of Calgary, Calgary, Canada
- Queensland Pediatric Rehabilitation Service, Queensland Children's Hospital, Brisbane, Australia
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16
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The NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty: Protocol and rationale for methods and measures. Neuroimage 2021; 234:117970. [PMID: 33771694 DOI: 10.1016/j.neuroimage.2021.117970] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 02/14/2021] [Accepted: 03/10/2021] [Indexed: 02/06/2023] Open
Abstract
Delineating the relationship between human neurodevelopment and the maturation of the hypothalamic-pituitary-gonadal (HPG) axis during puberty is critical for investigating the increase in vulnerability to neuropsychiatric disorders that is well documented during this period. Preclinical research demonstrates a clear association between gonadal production of sex steroids and neurodevelopment; however, identifying similar associations in humans has been complicated by confounding variables (such as age) and the coactivation of two additional endocrine systems (the adrenal androgenic system and the somatotropic growth axis) and requires further elucidation. In this paper, we present the design of, and preliminary observations from, the ongoing NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty. The aim of this study is to directly examine how the increase in sex steroid hormone production following activation of the HPG-axis (i.e., gonadarche) impacts neurodevelopment, and, additionally, to determine how gonadal development and maturation is associated with longitudinal changes in brain structure and function in boys and girls. To disentangle the effects of sex steroids from those of age and other endocrine events on brain development, our study design includes 1) selection criteria that establish a well-characterized baseline cohort of healthy 8-year-old children prior to the onset of puberty (e.g., prior to puberty-related sex steroid hormone production); 2) temporally dense longitudinal, repeated-measures sampling of typically developing children at 8-10 month intervals over a 10-year period between the ages of eight and 18; 3) contemporaneous collection of endocrine and other measures of gonadal, adrenal, and growth axis function at each timepoint; and 4) collection of multimodal neuroimaging measures at these same timepoints, including brain structure (gray and white matter volume, cortical thickness and area, white matter integrity, myelination) and function (reward processing, emotional processing, inhibition/impulsivity, working memory, resting-state network connectivity, regional cerebral blood flow). This report of our ongoing longitudinal study 1) provides a comprehensive review of the endocrine events of puberty; 2) details our overall study design; 3) presents our selection criteria for study entry (e.g., well-characterized prepubertal baseline) along with the endocrinological considerations and guiding principles that underlie these criteria; 4) describes our longitudinal outcome measures and how they specifically relate to investigating the effects of gonadal development on brain development; and 5) documents patterns of fMRI activation and resting-state networks from an early, representative subsample of our cohort of prepubertal 8-year-old children.
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17
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Ilzarbe D, Baeza I, de la Serna E, Fortea A, Valli I, Puig O, Masias M, Borras R, Pariente JC, Dolz M, Castro-Fornieles J, Sugranyes G. Theory of mind performance and prefrontal connectivity in adolescents at clinical high risk for psychosis. Dev Cogn Neurosci 2021; 48:100940. [PMID: 33721828 PMCID: PMC7970321 DOI: 10.1016/j.dcn.2021.100940] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 03/03/2021] [Accepted: 03/03/2021] [Indexed: 11/28/2022] Open
Abstract
Onset of psychosis was linked to a lack of age-related improvement in theory of mind. Reduced prefrontal connectivity preceded onset of psychosis in high risk youth. High risk youth with lower prefrontal connectivity were at greatest risk of psychosis.
Theory of mind(ToM) impairment is a key feature of psychotic disorders and has been documented in individuals at clinical high-risk for psychosis (CHR), suggesting that it may predate illness onset. However, no study to date has examined brain functional correlates of ToM in individuals at CHR during adolescence. The “Reading-the-Mind-in-the-Eyes” test was used to measure ToM performance in 50 CHR youth, 15 of whom transitioned to psychosis (CHR-t) at follow-up (12 ± 6 months) and 36 healthy volunteers. Resting-state functional MRI was acquired to evaluate functional connectivity within the default mode network. Group by age interaction revealed an age-positive association in ToM performance in healthy volunteers, which was not present in adolescents at CHR-t. Intrinsic functional connectivity in the medial prefrontal cortex was reduced in adolescents at CHR-t relative to those who did not transition and to healthy volunteers. Survival analyses revealed that participants at CHR with lower medial prefrontal cortex connectivity were at greatest risk of developing psychosis at follow-up. We demonstrate that lack of age-related maturation of ToM and reduced medial prefrontal cortex connectivity both precede the onset of psychosis during adolescence. Medial prefrontal cortex connectivity holds potential as a brain-based marker for the early identification of transition to psychosis.
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Affiliation(s)
- Daniel Ilzarbe
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Elena de la Serna
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Isabel Valli
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Olga Puig
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Mireia Masias
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Roger Borras
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain
| | - Jose C Pariente
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Montserrat Dolz
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry and Psychology, Hospital Sant Joan de Deu, Esplugues de Llobregat, Spain
| | - Josefina Castro-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain.
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18
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Xiao Q, Wu Z, Jiao Q, Zhong Y, Zhang Y, Lu G. Children with euthymic bipolar disorder during an emotional go/nogo task: Insights into the neural circuits of cognitive-emotional regulation. J Affect Disord 2021; 282:669-676. [PMID: 33445090 DOI: 10.1016/j.jad.2020.12.157] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 10/30/2020] [Accepted: 12/23/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND Pediatric bipolar disorder (PBD), manifested by alternating episodes of depression and mania, is more likely to relapse than adult BD and develop into chronic BD. Although it can be asymptomatic during the remission of PBD, subtle changes in the brain neural response can still exist. Abnormal activities in the neural circuits of cognitive-emotional regulation have been found in adult BD patients using fMRI. However, few fMRI studies focus on emotional regulation on cognitive function in euthymic PBD, especially during an emotional go/nogo task. Therefore, this study aims to compare differences in the activities of both emotional and cognitive circuits between euthymic BD children and healthy controls. METHODS 18 euthymic PBD and 17 healthy subjects from 12 to 17 years of age were enrolled in our study. Simultaneous neural activity was recorded during the overall task and the effect of emotional factors on task performances was assessed. RESULTS There were no significant differences in behavioral performances between the PBD group and the control group. During a task with emotional versus neutral distractors, euthymic PBD patients showed increased activities in the DLPFC, inferior parietal lobule, superior/middle frontal gyrus, superior/middle temporal gyrus, insula, posterior cingulate gyrus and posterior cerebellum lobe relative to healthy controls. The insula and DLPFC activities in response to emotional versus neutral distractors were positively associated with the differences in false response errors. CONCLUSIONS This study confirms the enhanced neural activities in euthymic PBD during a task with emotional versus control distractors. These brain regions supporting the cognitive and emotional dysregulation of PBD mainly coincide with the salience and executive control networks. As neural responses are more sensitive than behavioral manifestations in euthymic PBD, our findings will inspire more clinical studies to unveil the characteristic neuromechanism of PBD.
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Affiliation(s)
- Qian Xiao
- Mental Health Centre of Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
| | - Zhou Wu
- School of Psychology, Nanjing Normal University, Nanjing 210097, China
| | - Qing Jiao
- Department of Radiology, Taishan Medical University, Taian 271016, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing 210097, China.
| | - Yun Zhang
- Medical Department, Northwest Minzu University, Lanzhou 730030, China.
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, China
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19
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Fan F, Liao X, Lei T, Zhao T, Xia M, Men W, Wang Y, Hu M, Liu J, Qin S, Tan S, Gao JH, Dong Q, Tao S, He Y. Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study. Neuroimage 2020; 226:117581. [PMID: 33221440 DOI: 10.1016/j.neuroimage.2020.117581] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 11/04/2020] [Accepted: 11/12/2020] [Indexed: 01/10/2023] Open
Abstract
The default-mode network (DMN) is a set of functionally connected regions that play crucial roles in internal cognitive processing. Previous resting-state fMRI studies have demonstrated that the intrinsic functional organization of the DMN undergoes remarkable reconfigurations during childhood and adolescence. However, these studies have mainly focused on cross-sectional designs with small sample sizes, limiting the consistency and interpretations of the findings. Here, we used a large sample of longitudinal resting-state fMRI data comprising 305 typically developing children (6-12 years of age at baseline, 491 scans in total) and graph theoretical approaches to delineate the developmental trajectories of the functional architecture of the DMN. For each child, the DMN was constructed according to a prior parcellation with 32 brain nodes. We showed that the overall connectivity increased in strength from childhood to adolescence and became spatially similar to that in the young adult group (N = 61, 18-28 years of age). These increases were primarily located in the midline structures. Global and local network efficiency in the DMN also increased with age, indicating an enhanced capability in parallel information communication within the brain system. Based on the divergent developmental rates of nodal centrality, we identified three subclusters within the DMN, with the fastest rates in the cluster mainly comprising the anterior medial prefrontal cortex and posterior cingulate cortex. Together, our findings highlight the developmental patterns of the functional architecture in the DMN from childhood to adolescence, which has implications for the understanding of network mechanisms underlying the cognitive development of individuals.
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Affiliation(s)
- Fengmei Fan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing 100875, China.
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Mingming Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Jie Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China.
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20
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Novel imaging technology and procedures for studying brain function in preadolescent awake marmosets. J Neurosci Methods 2020; 343:108823. [PMID: 32580061 DOI: 10.1016/j.jneumeth.2020.108823] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 06/06/2020] [Accepted: 06/18/2020] [Indexed: 01/07/2023]
Abstract
BACKGROUND Novel imaging technology and procedures were developed to study brain function in preadolescent awake marmosets never exposed to anesthesia. METHODS A radiofrequency transmit and receive, head only volume coil was designed and integrated into a holding system. An acclimation procedure was developed without the use of anesthesia or sedation that allowed for awake imaging. Preadolescent 8-month old male and female marmosets were imaged for resting state BOLD functional connectivity to assess the status of the default mode network. Levels of reactivity during acclimation sessions and behavioral stress following imaging were assessed. RESULTS Data on functional coupling in the default mode network suggest the organization of connectivity to the prefrontal cortex is not fully developed at 8 months of age. The stress associated with the imaging procedure is comparable to that observed when marmosets are removed from their home cage and temporarily isolated from the family. COMPARISON TO OTHER METHODS The design of the radiofrequency coil provides B1 homogeneity across the entire brain without signal drop off. The unique design of the head cradle obviates the need for any stabilizing surgery, ear bars or bite bar and could be adapted to any size marmoset. The acclimation requires no anesthesia or sedation at any time in the early life of the developing marmoset, a condition that better reflects the human experience. CONCLUSION A method is provided for imaging functional activity in the brain of fully awake preadolescent marmosets without any history of anesthesia or sedation.
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21
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Faghiri A, Stephen JM, Wang YP, Wilson TW, Calhoun VD. Brain Development Includes Linear and Multiple Nonlinear Trajectories: A Cross-Sectional Resting-State Functional Magnetic Resonance Imaging Study. Brain Connect 2020; 9:777-788. [PMID: 31744324 DOI: 10.1089/brain.2018.0641] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Studies of brain structure have shown that the cortex matures in both a linear and nonlinear manner depending on the time window and specific region studied. In addition, it has been shown that socioeconomic status can impact brain development throughout childhood. However, very few studies have evaluated these patterns using functional measures. To this end, in this study we used cross-sectional resting-state functional magnetic resonance imaging data of 368 subjects, age 3-21 years, to examine the linear and nonlinear development of brain connectivity. We employed a clustering approach to characterize these developmental patterns into different linear and nonlinear groups. Our results showed that functional brain development exhibits multiple types of linear and nonlinear patterns, and assuming that brain connectivity values reach a stable state after a specific age might be misleading.
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Affiliation(s)
- Ashkan Faghiri
- The Mind Research Network, Albuquerque, New Mexico.,Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
| | | | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana.,Center for Genomics and Bioinformatics, Tulane University, New Orleans, Louisiana
| | - Tony W Wilson
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska.,Center for Magnetoencephalography, University of Nebraska Medical Center, Omaha, Nebraska
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, New Mexico.,Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
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22
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Cornblath EJ, Ashourvan A, Kim JZ, Betzel RF, Ciric R, Adebimpe A, Baum GL, He X, Ruparel K, Moore TM, Gur RC, Gur RE, Shinohara RT, Roalf DR, Satterthwaite TD, Bassett DS. Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands. Commun Biol 2020; 3:261. [PMID: 32444827 PMCID: PMC7244753 DOI: 10.1038/s42003-020-0961-x] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 04/02/2020] [Indexed: 01/01/2023] Open
Abstract
A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of brain activity are modulated by cognitive load, associated with age, and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we apply tools from network control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest, while stimulus-driven visual inputs explain the sequences observed during the n-back task. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.
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Affiliation(s)
- Eli J Cornblath
- Department of Neuroscience, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
| | - Arian Ashourvan
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
| | - Jason Z Kim
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
| | - Richard F Betzel
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
| | - Rastko Ciric
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Graham L Baum
- Department of Neuroscience, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Xiaosong He
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA
| | - Kosha Ruparel
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, & Informatics, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | | | - Danielle S Bassett
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Department of Physics & Astronomy, College of Arts & Sciences, Philadelphia, PA, 19104, USA.
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Department of Electrical & Systems Engineering, School of Engineering & Applied Science, Philadelphia, PA, 19104, USA.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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23
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Zeev-Wolf M, Levy J, Ebstein RP, Feldman R. Cumulative Risk on Oxytocin-Pathway Genes Impairs Default Mode Network Connectivity in Trauma-Exposed Youth. Front Endocrinol (Lausanne) 2020; 11:335. [PMID: 32528417 PMCID: PMC7256187 DOI: 10.3389/fendo.2020.00335] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 04/29/2020] [Indexed: 01/08/2023] Open
Abstract
Background: Although the default mode network (DMN) is a core network essential for brain functioning, little is known about its developmental trajectory, particularly on factors associated with its coherence into a functional network. In light of adult studies indicating DMN's susceptibility to stress-related conditions, we examined links between variability on oxytocin-pathway genes and DMN connectivity in youth exposed to chronic war-related trauma Methods: Following a cohort of war-exposed children from early childhood, we imaged the brains of 74 preadolescents (age 11-13 years; 39 war-exposed) during rest using magnetoencephalography (MEG). A cumulative risk index on oxytocin-pathway genes was constructed by combining single nucleotide polymorphisms on five genes previously linked with social deficits and psychopathology; OXTR rs1042778, OXTR rs2254298, OXTRrs53576, CD38 rs3796863, and AVPR1A RS3. Avoidant response to trauma reminders in early childhood and anxiety disorders in late childhood were assessed as predictors of disruptions to DMN theta connectivity. Results: Higher vulnerability on oxytocin-pathway genes predicted greater disruptions to DMN theta connectivity. Avoidant symptoms in early childhood and generalized anxiety disorder in later childhood were related to impaired DMN connectivity. In combination, stress exposure, oxytocin-pathway genes, and stress-related symptoms explained 24.6% of the variance in DMN connectivity, highlighting the significant effect of stress on the maturing brain. Conclusions: Findings are the first to link the oxytocin system and maturation of the DMN, a core system sustaining autobiographical memories, alteration of intrinsic and extrinsic attention, mentalization, and sense of self. Results suggest that oxytocin may buffer the effects of chronic early stress on the DMN, particularly theta rhythms that typify the developing brain.
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Affiliation(s)
- Maor Zeev-Wolf
- Department of Education, Zlotowski Center for Neuroscience, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Jonathan Levy
- Interdiscilinary Center Herzliya, Baruch Ivcher School of Psychology, Herzliya, Israel
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Richard P. Ebstein
- Department of Psychology, National University of Singapore, Singapore, Singapore
| | - Ruth Feldman
- Interdiscilinary Center Herzliya, Baruch Ivcher School of Psychology, Herzliya, Israel
- Child Study Center, Yale University, New Haven, CT, United States
- *Correspondence: Ruth Feldman
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24
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Hidalgo-Lopez E, Mueller K, Harris T, Aichhorn M, Sacher J, Pletzer B. Human menstrual cycle variation in subcortical functional brain connectivity: a multimodal analysis approach. Brain Struct Funct 2020; 225:591-605. [PMID: 31894405 PMCID: PMC7046575 DOI: 10.1007/s00429-019-02019-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Accepted: 12/18/2019] [Indexed: 12/18/2022]
Abstract
Increasing evidence suggests that endogenous sex steroid changes affect human brain functional connectivity, which could be obtained by resting-state fMRI (RS-fMRI). Nevertheless, RS studies on the menstrual cycle (MC) are underrepresented and yield inconsistent results. We attribute these inconsistencies to the use of various methods in exploratory approaches and small sample sizes. Hormonal fluctuations along the MC likely elicit subtle changes that, however, may still have profound impact on network dynamics when affecting key brain nodes. To address these issues, we propose a ROI-based multimodal analysis approach focusing on areas of high functional relevance to adequately capture these changes. To that end, sixty naturally cycling women underwent RS-fMRI in three different cycle phases and we performed the following analyses: (1) group-independent component analyses to identify intrinsic connectivity networks, (2) eigenvector centrality (EC) as a measure of centrality in the global connectivity hierarchy, (3) amplitude of low-frequency fluctuations (ALFF) as a measure of oscillatory activity and (4) seed-based analyses to investigate functional connectivity from the ROIs. For (2)–(4), we applied a hypothesis-driven ROI approach in the hippocampus, caudate and putamen. In the luteal phase, we found (1) decreased intrinsic connectivity of the right angular gyrus with the default mode network, (2) heightened EC for the hippocampus, and (3) increased ALFF for the caudate. Furthermore, we observed (4) stronger putamen–thalamic connectivity during the luteal phase and stronger fronto-striatal connectivity during the pre-ovulatory phase. This hormonal modulation of connectivity dynamics may underlie behavioural, emotional and sensorimotor changes along the MC.
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Affiliation(s)
- Esmeralda Hidalgo-Lopez
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria.
| | - Karsten Mueller
- Methods and Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany
| | - TiAnni Harris
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria
| | - Markus Aichhorn
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria
| | - Julia Sacher
- Research Group EGG (Emotions and neuroimaGinG)-Laboratory, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany.,Clinic for Cognitive Neurology, University Hospital Leipzig, Liebigstrasse 16, 04103, Leipzig, Germany
| | - Belinda Pletzer
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria.
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25
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Ilzarbe D, de la Serna E, Baeza I, Rosa M, Puig O, Calvo A, Masias M, Borras R, Pariente JC, Castro-Fornieles J, Sugranyes G. The relationship between performance in a theory of mind task and intrinsic functional connectivity in youth with early onset psychosis. Dev Cogn Neurosci 2019; 40:100726. [PMID: 31791005 PMCID: PMC6974903 DOI: 10.1016/j.dcn.2019.100726] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 09/06/2019] [Accepted: 11/03/2019] [Indexed: 12/15/2022] Open
Abstract
Psychotic disorders are characterized by theory of mind (ToM) impairment. Although ToM undergoes maturational changes throughout adolescence, there is a lack of studies examining ToM performance and its brain functional correlates in individuals with an early onset of psychosis (EOP; onset prior to age 18), and its relationship with age. Twenty-seven individuals with EOP were compared with 41 healthy volunteers using the "Reading-the-Mind-in-the-Eyes" Test, as a measure of ToM performance. A resting-state functional MRI scan was also acquired, in which the default mode network was used to identify areas relevant to ToM processing employing independent component analysis. Group effects revealed worse ToM performance and less intrinsic functional connectivity in the medial prefrontal cortex in EOP relative to healthy volunteers. Group by age interaction revealed age-positive associations in ToM task performance and in intrinsic connectivity in the medial prefrontal cortex in healthy volunteers, which were not present in EOP. Differences in ToM performance were partially mediated by intrinsic functional connectivity in the medial prefrontal cortex. Poorer ToM performance in EOP, coupled with less medial prefrontal cortex connectivity, could be associated with the impact of psychosis during a critical period of development of the social brain, limiting normative age-related maturation.
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Affiliation(s)
- Daniel Ilzarbe
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry and Neuroscience, King's College London, London, United Kingdom
| | - Elena de la Serna
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Inmaculada Baeza
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Mireia Rosa
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain
| | - Olga Puig
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Anna Calvo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Mireia Masias
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Roger Borras
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain
| | - Jose C Pariente
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Josefina Castro-Fornieles
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Gisela Sugranyes
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, Barcelona, Spain; Department of Medicine, Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain.
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26
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Association between spontaneous activity of the default mode network hubs and leukocyte telomere length in late childhood and early adolescence. J Psychosom Res 2019; 127:109864. [PMID: 31706071 DOI: 10.1016/j.jpsychores.2019.109864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 10/25/2019] [Accepted: 10/25/2019] [Indexed: 12/11/2022]
Abstract
The impact of early life stress on mental health and telomere length shortening have been reported. Changes in brain default mode network (DMN) were found to be related to a myriad of psychiatric conditions in which stress may play a role. In this context, family environment and adverse childhood experiences (ACEs) are potential causes of stress. This is a hypothesis-driven study focused on testing two hypotheses: (i) there is an association between telomere length and the function of two main hubs of DMN: the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC); (ii) this association is modulated by family environment and/or ACEs. To the best of our knowledge, this is the first study investigating these hypotheses. Resting-state functional magnetic resonance imaging data and blood sample were collected from 389 subjects (6-15 age range). We assessed DMN fractional amplitude of low-frequency fluctuations (fALFF) and leukocyte telomere length (LTL). We fitted general linear models to test the main effects of LTL on DMN hubs and the interaction effects with Family Environment Scale (FES) and ACEs. The results did not survive a strict Bonferroni correction. However, uncorrected p-values suggest that LTL was positively correlated with fALFF in PCC and a FES interaction between FES and LTL at mPFC. Although marginal, our results encourage further research on the interaction between DMN hubs, telomere length and family environment, which may play a role on the biological embedding of stress.
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27
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Cognitive and affective Theory of Mind in adolescence: developmental aspects and associated neuropsychological variables. PSYCHOLOGICAL RESEARCH 2019; 85:533-553. [PMID: 31701225 PMCID: PMC7900042 DOI: 10.1007/s00426-019-01263-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 10/25/2019] [Indexed: 12/19/2022]
Abstract
Theory of Mind (ToM) is the ability to represent and attribute mental states to oneself and others. So far, research regarding ToM processing across adolescence is scarce. Existing studies either yield inconsistent results or did not or not thoroughly investigate aspects like higher order ToM and associated neuropsychological variables which the current study tried to address. 643 typically developing early, middle, and late adolescents (age groups 13-14; 15-16; 17-18) performed cognitive and affective ToM tasks as well as neuropsychological tasks tapping the cognitive or affective domain. Regarding both ToM types, 15- to 16-year-olds and 17- to 18-year-olds outperformed 13- to 14-year-olds, whereas females were superior regarding cognitive ToM. Across adolescence, cognitive and affective ToM correlated with attention and affective intelligence, whereas working memory, language comprehension, and figural intelligence additionally correlated with cognitive ToM. In early adolescence, attention correlated with both ToM types, whereas cognitive ToM further correlated with language comprehension and affective ToM with verbal intelligence, verbal fluency, and verbal flexibility. In middle and late adolescence, affective intelligence correlated with both ToM types, whereas cognitive ToM additionally correlated with working memory, language comprehension, and figural intelligence. The current study shows a developmental step regarding cognitive and affective ToM in middle adolescence as well as gender differences in cognitive ToM processing. Associations between neuropsychological variables and ToM processing were shown across adolescence and within age groups. Results give new insights into social cognition in adolescence and are well supported by neuroscientific and neurobiological studies regarding ToM and the integration of cognitive and affective processes.
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28
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Sato JR, Biazoli CE, Salum GA, Gadelha A, Crossley N, Vieira G, Zugman A, Picon FA, Pan PM, Hoexter MQ, Amaro E, Anés M, Moura LM, Del'Aquilla MAG, Mcguire P, Rohde LA, Miguel EC, Bressan RA, Jackowski AP. Associations between children's family environment, spontaneous brain oscillations, and emotional and behavioral problems. Eur Child Adolesc Psychiatry 2019; 28:835-845. [PMID: 30392120 DOI: 10.1007/s00787-018-1240-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 10/20/2018] [Indexed: 12/31/2022]
Abstract
The family environment in childhood has a strong effect on mental health outcomes throughout life. This effect is thought to depend at least in part on modifications of neurodevelopment trajectories. In this exploratory study, we sought to investigate whether a feasible resting-state fMRI metric of local spontaneous oscillatory neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), is associated with the levels of children's family coherence and conflict. Moreover, we sought to further explore whether spontaneous activity in the brain areas influenced by family environment would also be associated with a mental health outcome, namely the incidence of behavioral and emotional problems. Resting-state fMRI data from 655 children and adolescents (6-15 years old) were examined. The quality of the family environment was found to be positively correlated with fALFF in the left temporal pole and negatively correlated with fALFF in the right orbitofrontal cortex. Remarkably, increased fALFF in the temporal pole was associated with a lower incidence of behavioral and emotional problems, whereas increased fALFF in the orbitofrontal cortex was correlated with a higher incidence.
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Affiliation(s)
- João Ricardo Sato
- Center of Mathematics, Computation, and Cognition, Universidade Federal do ABC, Av. dos Estados, 5001, Bairro Bangu, Santo André, SP, CEP 09210-580, Brazil. .,Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil. .,Department of Radiology, School of Medicine, University of Sao Paulo, São Paulo, Brazil. .,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil. .,Institute of Radiology (InRad), School of Medicine, University of Sao Paulo, São Paulo, Brazil.
| | - Claudinei Eduardo Biazoli
- Center of Mathematics, Computation, and Cognition, Universidade Federal do ABC, Av. dos Estados, 5001, Bairro Bangu, Santo André, SP, CEP 09210-580, Brazil.,Department of Radiology, School of Medicine, University of Sao Paulo, São Paulo, Brazil
| | - Giovanni Abrahão Salum
- Hospital de Clinicas de Porto Alegre and Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Ary Gadelha
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | | | - Gilson Vieira
- Bioinformatics Program, Institute of Mathematics and Statistics, University of Sao Paulo, São Paulo, Brazil.,Department of Radiology, School of Medicine, University of Sao Paulo, São Paulo, Brazil
| | - André Zugman
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Felipe Almeida Picon
- Hospital de Clinicas de Porto Alegre and Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Pedro Mario Pan
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Marcelo Queiroz Hoexter
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,Department of Psychiatry, School of Medicine, University of Sao Paulo, São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Edson Amaro
- Institute of Radiology (InRad), School of Medicine, University of Sao Paulo, São Paulo, Brazil
| | - Mauricio Anés
- Hospital de Clinicas de Porto Alegre and Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Luciana Monteiro Moura
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Marco Antonio Gomes Del'Aquilla
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Philip Mcguire
- Institute of Psychiatry, King's College London, London, UK
| | - Luis Augusto Rohde
- Hospital de Clinicas de Porto Alegre and Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Euripedes Constantino Miguel
- Department of Psychiatry, School of Medicine, University of Sao Paulo, São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Rodrigo Affonseca Bressan
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
| | - Andrea Parolin Jackowski
- Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), São Paulo, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil
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29
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Hinz R, Peeters LM, Shah D, Missault S, Belloy M, Vanreusel V, Malekzadeh M, Verhoye M, Van der Linden A, Keliris GA. Bottom-up sensory processing can induce negative BOLD responses and reduce functional connectivity in nodes of the default mode-like network in rats. Neuroimage 2019; 197:167-176. [PMID: 31029872 DOI: 10.1016/j.neuroimage.2019.04.065] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 04/23/2019] [Accepted: 04/24/2019] [Indexed: 11/26/2022] Open
Abstract
The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode-like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that the BOLD response in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in sedated rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN.
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Affiliation(s)
- Rukun Hinz
- Bio-Imaging Lab, University of Antwerp, Belgium.
| | | | - Disha Shah
- Bio-Imaging Lab, University of Antwerp, Belgium
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30
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Oldham S, Fornito A. The development of brain network hubs. Dev Cogn Neurosci 2019; 36:100607. [PMID: 30579789 PMCID: PMC6969262 DOI: 10.1016/j.dcn.2018.12.005] [Citation(s) in RCA: 106] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 10/24/2018] [Accepted: 12/11/2018] [Indexed: 01/31/2023] Open
Abstract
Some brain regions have a central role in supporting integrated brain function, marking them as network hubs. Given the functional importance of hubs, it is natural to ask how they emerge during development and to consider how they shape the function of the maturing brain. Here, we review evidence examining how brain network hubs, both in structural and functional connectivity networks, develop over the prenatal, neonate, childhood, and adolescent periods. The available evidence suggests that structural hubs of the brain arise in the prenatal period and show a consistent spatial topography through development, but undergo a protracted period of consolidation that extends into late adolescence. In contrast, the hubs of brain functional networks show a more variable topography, being predominantly located in primary cortical areas in early development, before moving to association areas by late childhood. These findings suggest that while the basic anatomical infrastructure of hubs may be established early, the functional viability and integrative capacity of these areas undergoes extensive postnatal maturation. Not all findings are consistent with this view however. We consider methodological factors that might drive these inconsistencies, and which should be addressed to promote a more rigorous investigation of brain network development.
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Affiliation(s)
- Stuart Oldham
- Brain and Mental Health Research Hub, School of Psychological Sciences and the Monash Institute of Cognitive and Clinical Neurosciences (MICCN), Monash University, Australia.
| | - Alex Fornito
- Brain and Mental Health Research Hub, School of Psychological Sciences and the Monash Institute of Cognitive and Clinical Neurosciences (MICCN), Monash University, Australia
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31
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Hunt BAE, Wong SM, Vandewouw MM, Brookes MJ, Dunkley BT, Taylor MJ. Spatial and spectral trajectories in typical neurodevelopment from childhood to middle age. Netw Neurosci 2019; 3:497-520. [PMID: 30984904 PMCID: PMC6444935 DOI: 10.1162/netn_a_00077] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 12/24/2018] [Indexed: 11/21/2022] Open
Abstract
Detailed characterization of typical human neurodevelopment is key if we are to understand the nature of mental and neurological pathology. While research on the cellular processes of neurodevelopment has made great advances, in vivo human imaging is crucial to understand our uniquely human capabilities, as well as the pathologies that affect them. Using magnetoencephalography data in the largest normative sample currently available (324 participants aged 6-45 years), we assess the developmental trajectory of resting-state oscillatory power and functional connectivity from childhood to middle age. The maturational course of power, indicative of local processing, was found to both increase and decrease in a spectrally dependent fashion. Using the strength of phase-synchrony between parcellated regions, we found significant linear and nonlinear (quadratic and logarithmic) trajectories to be characterized in a spatially heterogeneous frequency-specific manner, such as a superior frontal region with linear and nonlinear trajectories in theta and gamma band respectively. Assessment of global efficiency revealed similar significant nonlinear trajectories across all frequency bands. Our results link with the development of human cognitive abilities; they also highlight the complexity of neurodevelopment and provide quantitative parameters for replication and a robust footing from which clinical research may map pathological deviations from these typical trajectories.
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Affiliation(s)
- Benjamin A. E. Hunt
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
- Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
| | - Simeon M. Wong
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
- Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
| | - Marlee M. Vandewouw
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
- Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
| | - Matthew J. Brookes
- The Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Benjamin T. Dunkley
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
- Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Margot J. Taylor
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
- Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
- Department of Psychology, University of Toronto, Toronto, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Canada
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32
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Rubia K, Criaud M, Wulff M, Alegria A, Brinson H, Barker G, Stahl D, Giampietro V. Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD. Neuroimage 2018; 188:43-58. [PMID: 30513395 PMCID: PMC6414400 DOI: 10.1016/j.neuroimage.2018.11.055] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 11/28/2018] [Accepted: 11/29/2018] [Indexed: 11/21/2022] Open
Abstract
Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self-control, underpinned by inferior fronto-striatal deficits. We showed previously that 18 ADHD adolescents over 11 runs of 8.5 min of real-time functional magnetic resonance neurofeedback of the right inferior frontal cortex (rIFC) progressively increased activation in 2 regions of the rIFC which was associated with clinical symptom improvement. In this study, we used functional connectivity analyses to investigate whether fMRI-Neurofeedback of rIFC resulted in dynamic functional connectivity changes in underlying neural networks. Whole-brain seed-based functional connectivity analyses were conducted using the two clusters showing progressively increased activation in rIFC as seed regions to test for changes in functional connectivity before and after 11 fMRI-Neurofeedback runs. Furthermore, we tested whether the resulting functional connectivity changes were associated with clinical symptom improvements and whether they were specific to fMRI-Neurofeedback of rIFC when compared to a control group who had to self-regulate another region. rIFC showed increased positive functional connectivity after relative to before fMRI-Neurofeedback with dorsal caudate and anterior cingulate and increased negative functional connectivity with regions of the default mode network (DMN) such as posterior cingulate and precuneus. Furthermore, the functional connectivity changes were correlated with clinical improvements and the functional connectivity and correlation findings were specific to the rIFC-Neurofeedback group. The findings show for the first time that fMRI-Neurofeedback of a typically dysfunctional frontal region in ADHD adolescents leads to strengthening within fronto-cingulo-striatal networks and to weakening of functional connectivity with posterior DMN regions and that this may be underlying clinical improvement.
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Affiliation(s)
- K Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - M Criaud
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - M Wulff
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - A Alegria
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - H Brinson
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - G Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - D Stahl
- Department of Biostatistics & Health Informatics, King's College London, UK
| | - V Giampietro
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
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33
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Rebello K, Moura LM, Pinaya WHL, Rohde LA, Sato JR. Default Mode Network Maturation and Environmental Adversities During Childhood. ACTA ACUST UNITED AC 2018; 2:2470547018808295. [PMID: 32440587 PMCID: PMC7219900 DOI: 10.1177/2470547018808295] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 09/28/2018] [Indexed: 12/14/2022]
Abstract
Default mode network (DMN) plays a central role in cognition and brain disorders.
It has been shown that adverse environmental conditions impact neurodevelopment,
but how these conditions impact in DMN maturation is still poorly understood.
This article reviews representative neuroimaging functional studies addressing
the interactions between DMN development and environmental factors, focusing on
early life adversities, a critical period for brain changes. Studies focused on
this period of life offer a special challenge: to disentangle the
neurodevelopmental connectivity changes from those related to environmental
conditions. We first summarized the literature on DMN maturation, providing an
overview of both typical and atypical development patterns in childhood and
early adolescence. Afterward, we focused on DMN changes associated with chronic
exposure to environmental adversities during childhood. This summary suggests
that changes in DMN development could be a potential allostatic neural feature
associated with an embodiment of environmental circumstances. Finally, we
discuss about some key methodological issues that should be considered in
paradigms addressing environmental adversities and open questions for future
investigations.
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Affiliation(s)
- Keila Rebello
- Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Brazil
| | - Luciana M Moura
- Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Brazil
| | - Walter H L Pinaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Luis A Rohde
- Department of Psychiatry, Federal University of Rio Grande do Sul, Brazil
| | - João R Sato
- Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Brazil
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34
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Bozhilova NS, Michelini G, Kuntsi J, Asherson P. Mind wandering perspective on attention-deficit/hyperactivity disorder. Neurosci Biobehav Rev 2018; 92:464-476. [PMID: 30036553 PMCID: PMC6525148 DOI: 10.1016/j.neubiorev.2018.07.010] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 06/19/2018] [Accepted: 07/19/2018] [Indexed: 11/29/2022]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder associated with a range of mental health, neurocognitive and functional problems. Although the diagnosis is based on descriptions of behaviour, individuals with ADHD characteristically describe excessive spontaneous mind wandering (MW). MW in individuals with ADHD reflects constant mental activity which lacks topic stability and content consistency. Based on this review of the neural correlates of ADHD and MW, we outline a new perspective on ADHD: the MW hypothesis. We propose that altered deactivation of the default mode network, and dysfunctional interaction with the executive control network, leads to excessive and spontaneous MW, which underpins symptoms and impairments of ADHD. We highlight that processes linked to the normal neural regulation of MW (context regulation, sensory decoupling, salience thresholds) are deficient in ADHD. MW-related measures could serve as markers of the disease process, as MW can be experimentally manipulated, as well as measured using rating scales, and experience sampling during both cognitive tasks and daily life. MW may therefore be a potential endophenotype.
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Affiliation(s)
- Natali S Bozhilova
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Denmark Hill, De Crespigny Park, SE5 8AF, United Kingdom.
| | - Giorgia Michelini
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Denmark Hill, De Crespigny Park, SE5 8AF, United Kingdom
| | - Jonna Kuntsi
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Denmark Hill, De Crespigny Park, SE5 8AF, United Kingdom
| | - Philip Asherson
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Denmark Hill, De Crespigny Park, SE5 8AF, United Kingdom.
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35
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Identification of alterations associated with age in the clustering structure of functional brain networks. PLoS One 2018; 13:e0195906. [PMID: 29795565 PMCID: PMC5967704 DOI: 10.1371/journal.pone.0195906] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Accepted: 04/02/2018] [Indexed: 12/21/2022] Open
Abstract
Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals’ functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.
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36
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Rubia K. Cognitive Neuroscience of Attention Deficit Hyperactivity Disorder (ADHD) and Its Clinical Translation. Front Hum Neurosci 2018; 12:100. [PMID: 29651240 PMCID: PMC5884954 DOI: 10.3389/fnhum.2018.00100] [Citation(s) in RCA: 174] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 03/05/2018] [Indexed: 01/01/2023] Open
Abstract
This review focuses on the cognitive neuroscience of Attention Deficit Hyperactivity Disorder (ADHD) based on functional magnetic resonance imaging (fMRI) studies and on recent clinically relevant applications such as fMRI-based diagnostic classification or neuromodulation therapies targeting fMRI deficits with neurofeedback (NF) or brain stimulation. Meta-analyses of fMRI studies of executive functions (EFs) show that ADHD patients have cognitive-domain dissociated complex multisystem impairments in several right and left hemispheric dorsal, ventral and medial fronto-cingulo-striato-thalamic and fronto-parieto-cerebellar networks that mediate cognitive control, attention, timing and working memory (WM). There is furthermore emerging evidence for abnormalities in orbital and ventromedial prefrontal and limbic areas that mediate motivation and emotion control. In addition, poor deactivation of the default mode network (DMN) suggests an abnormal interrelationship between hypo-engaged task-positive and poorly "switched off" hyper-engaged task-negative networks, both of which are related to impaired cognition. Translational cognitive neuroscience in ADHD is still in its infancy. Pattern recognition analyses have attempted to provide diagnostic classification of ADHD using fMRI data with respectable classification accuracies of over 80%. Necessary replication studies, however, are still outstanding. Brain stimulation has been tested in heterogeneously designed, small numbered proof of concept studies targeting key frontal functional impairments in ADHD. Transcranial direct current stimulation (tDCS) appears to be promising to improve ADHD symptoms and cognitive functions based on some studies, but larger clinical trials of repeated stimulation with and without cognitive training are needed to test clinical efficacy and potential costs on non-targeted functions. Only three studies have piloted NF of fMRI-based frontal dysfunctions in ADHD using fMRI or near-infrared spectroscopy, with the two larger ones finding some improvements in cognition and symptoms, which, however, were not superior to the active control conditions, suggesting potential placebo effects. Neurotherapeutics seems attractive for ADHD due to their safety and potential longer-term neuroplastic effects, which drugs cannot offer. However, they need to be thoroughly tested for short- and longer-term clinical and cognitive efficacy and their potential for individualized treatment.
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Affiliation(s)
- Katya Rubia
- Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, London, United Kingdom
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37
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Sato JR, Biazoli CE, Salum GA, Gadelha A, Crossley N, Vieira G, Zugman A, Picon FA, Pan PM, Hoexter MQ, Amaro E, Anés M, Moura LM, Del'Aquilla MAG, Mcguire P, Rohde LA, Miguel EC, Jackowski AP, Bressan RA. Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning. World J Biol Psychiatry 2018. [PMID: 28635541 DOI: 10.1080/15622975.2016.1274050] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
OBJECTIVES One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM). METHODS We applied this approach to resting-state fMRI data from 622 children and adolescents. Eigenvector centrality (EVC) of nodes from positive- and negative-task networks were extracted from each subject and used as input to an OC-SVM to label individual brain networks as typical or atypical. We hypothesised that classification of these subjects regarding the pattern of brain connectivity would predict the level of psychopathology. RESULTS Subjects with atypical brain network organisation had higher levels of psychopathology (p < 0.001). There was a greater EVC in the typical group at the bilateral posterior cingulate and bilateral posterior temporal cortices; and significant decreases in EVC at left temporal pole. CONCLUSIONS The combination of graph theory methods and an OC-SVM is a promising method to characterise neurodevelopment, and may be useful to understand the deviations leading to mental disorders.
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Affiliation(s)
- João Ricardo Sato
- a Center of Mathematics, Computation and Cognition, Universidade Federal do ABC , Santo André , Brazil.,b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,c Department of Radiology , School of Medicine, University of Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Claudinei Eduardo Biazoli
- a Center of Mathematics, Computation and Cognition, Universidade Federal do ABC , Santo André , Brazil.,c Department of Radiology , School of Medicine, University of Sao Paulo , Brazil
| | - Giovanni Abrahão Salum
- d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,e Hospital de Clinicas de Porto Alegre and Department of Psychiatry , Federal University of Rio Grande do Sul , Porto Alegre , Brazil
| | - Ary Gadelha
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Nicolas Crossley
- f Department of Psychosis Studies, Institute of Psychiatry, King's College London , United Kingdom
| | - Gilson Vieira
- c Department of Radiology , School of Medicine, University of Sao Paulo , Brazil.,g Bioinformatics Program , Institute of Mathematics and Statistics, University of Sao Paulo , Brazil
| | - André Zugman
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Felipe Almeida Picon
- d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,e Hospital de Clinicas de Porto Alegre and Department of Psychiatry , Federal University of Rio Grande do Sul , Porto Alegre , Brazil
| | - Pedro Mario Pan
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Marcelo Queiroz Hoexter
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,h Department of Psychiatry , School of Medicine, University of Sao Paulo , Brazil
| | - Edson Amaro
- i Institute of Radiology (InRad), Faculdade de Medicina , Universidade de Sao Paulo , Brazil
| | - Mauricio Anés
- d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,e Hospital de Clinicas de Porto Alegre and Department of Psychiatry , Federal University of Rio Grande do Sul , Porto Alegre , Brazil
| | - Luciana Monteiro Moura
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Marco Antonio Gomes Del'Aquilla
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Philip Mcguire
- f Department of Psychosis Studies, Institute of Psychiatry, King's College London , United Kingdom
| | - Luis Augusto Rohde
- d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,e Hospital de Clinicas de Porto Alegre and Department of Psychiatry , Federal University of Rio Grande do Sul , Porto Alegre , Brazil
| | - Euripedes Constantino Miguel
- d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil.,h Department of Psychiatry , School of Medicine, University of Sao Paulo , Brazil
| | - Andrea Parolin Jackowski
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
| | - Rodrigo Affonseca Bressan
- b Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC) , Universidade Federal de Sao Paulo (UNIFESP) , Sao Paulo , Brazil.,d National Institute of Developmental Psychiatry for Children and Adolescents , CNPq , Brazil
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Khan S, Hashmi JA, Mamashli F, Michmizos K, Kitzbichler MG, Bharadwaj H, Bekhti Y, Ganesan S, Garel KLA, Whitfield-Gabrieli S, Gollub RL, Kong J, Vaina LM, Rana KD, Stufflebeam SM, Hämäläinen MS, Kenet T. Maturation trajectories of cortical resting-state networks depend on the mediating frequency band. Neuroimage 2018; 174:57-68. [PMID: 29462724 DOI: 10.1016/j.neuroimage.2018.02.018] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 02/07/2018] [Accepted: 02/10/2018] [Indexed: 12/11/2022] Open
Abstract
The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.
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Affiliation(s)
- Sheraz Khan
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Department of Radiology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, USA.
| | - Javeria A Hashmi
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Fahimeh Mamashli
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Konstantinos Michmizos
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Manfred G Kitzbichler
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Hari Bharadwaj
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Yousra Bekhti
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Santosh Ganesan
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Keri-Lee A Garel
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | | | - Randy L Gollub
- Department of Psychiatry MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Jian Kong
- Department of Psychiatry MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Lucia M Vaina
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Department of Biomedical Engineering, Boston University, Boston, USA
| | - Kunjan D Rana
- Department of Biomedical Engineering, Boston University, Boston, USA
| | - Steven M Stufflebeam
- Department of Radiology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Matti S Hämäläinen
- Department of Radiology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
| | - Tal Kenet
- Department of Neurology, MGH, Harvard Medical School, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, USA
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39
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Ho TC, Dennis EL, Thompson PM, Gotlib IH. Network-based approaches to examining stress in the adolescent brain. Neurobiol Stress 2018; 8:147-157. [PMID: 29888310 PMCID: PMC5991327 DOI: 10.1016/j.ynstr.2018.05.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 04/06/2018] [Accepted: 05/04/2018] [Indexed: 01/22/2023] Open
Abstract
Exposure to stress, particularly in periods of rapid brain maturation such as adolescence, can profoundly influence developmental processes that undergird the organization of structural and functional brain networks and that may mediate the association between stressful experiences and maladaptive outcomes. While studies in translational developmental neuroscience often focus on how specific brain regions or targeted connections are altered by stress and psychiatric disease, the emerging field of network science may be especially valuable for elucidating the impact of stress on the intricate connectomics of the adolescent brain. Here we review recent studies that use graph theory and other network science approaches to understand normative adolescent brain development, effects of childhood maltreatment on the brain, and disorders characterized by pathological responses to stress in adolescents. Overall, these studies demonstrate that graph theory can be useful in identifying and quantifying developmental processes related to segregation, integration, and localized hub influence that are affected by stress exposure and that may lead to psychopathology. Finally, we discuss limitations in the current application of graph theory in this area and suggest what we believe are important directions for future work.
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Affiliation(s)
| | - Emily L. Dennis
- Imaging Genetics Center, Mary and Mark Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mary and Mark Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, USA
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40
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Chan JSY, Wang Y, Yan JH, Chen H. Developmental implications of children's brain networks and learning. Rev Neurosci 2018; 27:713-727. [PMID: 27362958 DOI: 10.1515/revneuro-2016-0007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 05/14/2016] [Indexed: 11/15/2022]
Abstract
The human brain works as a synergistic system where information exchanges between functional neuronal networks. Rudimentary networks are observed in the brain during infancy. In recent years, the question of how functional networks develop and mature in children has been a hotly discussed topic. In this review, we examined the developmental characteristics of functional networks and the impacts of skill training on children's brains. We first focused on the general rules of brain network development and on the typical and atypical development of children's brain networks. After that, we highlighted the essentials of neural plasticity and the effects of learning on brain network development. We also discussed two important theoretical and practical concerns in brain network training. Finally, we concluded by presenting the significance of network training in typically and atypically developed brains.
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41
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Grayson DS, Fair DA. Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature. Neuroimage 2017; 160:15-31. [PMID: 28161313 PMCID: PMC5538933 DOI: 10.1016/j.neuroimage.2017.01.079] [Citation(s) in RCA: 252] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2016] [Revised: 01/16/2017] [Accepted: 01/31/2017] [Indexed: 02/08/2023] Open
Abstract
The development of human cognition results from the emergence of coordinated activity between distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to (1) better characterize normative developmental trajectories, (2) link these trajectories to biologic mechanistic events, as well as component behaviors and (3) better understand the clinical implications and pathophysiological basis of aberrant network development.
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Affiliation(s)
- David S Grayson
- The MIND Institute, University of California Davis, Sacramento, CA 95817, USA; Center for Neuroscience, University of California Davis, Davis, CA 95616, USA; Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA
| | - Damien A Fair
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA; Department of Psychiatry, Oregon Health and Science University, Portland, OR 97239, USA; Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA.
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42
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Altered intrinsic functional connectivity of the cingulate cortex in children with severe temper outbursts. Dev Psychopathol 2017; 30:571-579. [PMID: 28803557 DOI: 10.1017/s0954579417001080] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Severe temper outbursts (STO) in children are associated with impaired school and family functioning and may contribute to negative outcomes. These outbursts can be conceptualized as excessive frustration responses reflecting reduced emotion regulation capacity. The anterior cingulate cortex (ACC) has been implicated in negative affect as well as emotional control, and exhibits disrupted function in children with elevated irritability and outbursts. This study examined the intrinsic functional connectivity (iFC) of a region of the ACC, the anterior midcingulate cortex (aMCC), in 5- to 9-year-old children with STO (n = 20), comparing them to children with attention-deficit/hyperactivity disorder (ADHD) without outbursts (ADHD; n = 18). Additional analyses compared results to a sample of healthy children (HC; n = 18) and examined specific associations with behavioral and emotional dysregulation. Compared to the ADHD group, STO children exhibited reduced iFC between the aMCC and surrounding regions of the ACC, and increased iFC between the aMCC and precuneus. These differences were also seen between the STO and HC groups; ADHD and HC groups did not differ. Specificity analyses found associations between aMCC-ACC connectivity and hyperactivity, and between aMCC-precuneus iFC and emotion dysregulation. Disruption in aMCC networks may underlie the behavioral and emotional dysregulation characteristic of children with STO.
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43
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Holla B, Panda R, Venkatasubramanian G, Biswal B, Bharath RD, Benegal V. Disrupted resting brain graph measures in individuals at high risk for alcoholism. Psychiatry Res Neuroimaging 2017; 265:54-64. [PMID: 28531764 DOI: 10.1016/j.pscychresns.2017.05.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 05/03/2017] [Accepted: 05/04/2017] [Indexed: 01/13/2023]
Abstract
Familial susceptibility to alcoholism is likely to be linked to the externalizing diathesis seen in high-risk offspring from high-density alcohol use disorder (AUD) families. The present study aimed at comparing resting brain functional connectivity and their association with externalizing symptoms and alcoholism familial density in 40 substance-naive high-risk (HR) male offspring from high-density AUD families and 30 matched healthy low-risk (LR) males without a family history of substance dependence using graph theory-based network analysis. The HR subjects from high-density AUD families compared with LR, showed significantly reduced clustering, small-worldness, and local network efficiency. The frontoparietal, cingulo-opercular, sensorimotor and cerebellar networks exhibited significantly reduced functional segregation. These disruptions exhibited independent incremental value in predicting the externalizing symptoms over and above the demographic variables. The reduction of functional segregation in HR subjects was significant across both the younger and older age groups and was proportional to the family loading of AUDs. Detection and estimation of these developmentally relevant disruptions in small-world architecture at critical brain regions sub-serving cognitive, affective, and sensorimotor processes are vital for understanding the familial risk for early onset alcoholism as well as for understanding the pathophysiological mechanism of externalizing behaviors.
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Affiliation(s)
- Bharath Holla
- Centre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road, Bangalore, India.
| | - Rajanikant Panda
- Cognitive Neuroscience Centre and Department of Neuroimaging and Interventional Radiology (NIIR), NIMHANS, Hosur Road, Bangalore, India
| | | | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology (NJIT), University Heights, Newark, NJ, USA
| | - Rose Dawn Bharath
- Cognitive Neuroscience Centre and Department of Neuroimaging and Interventional Radiology (NIIR), NIMHANS, Hosur Road, Bangalore, India.
| | - Vivek Benegal
- Centre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road, Bangalore, India.
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44
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Knyazev GG, Savostyanov AN, Bocharov AV, Slobodskaya HR, Bairova NB, Tamozhnikov SS, Stepanova VV. Effortful control and resting state networks: A longitudinal EEG study. Neuroscience 2017; 346:365-381. [DOI: 10.1016/j.neuroscience.2017.01.031] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 01/14/2017] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
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45
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Functional connectomics from a "big data" perspective. Neuroimage 2017; 160:152-167. [PMID: 28232122 DOI: 10.1016/j.neuroimage.2017.02.031] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Revised: 01/21/2017] [Accepted: 02/13/2017] [Indexed: 01/10/2023] Open
Abstract
In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field.
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46
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Bray S. Age-associated patterns in gray matter volume, cerebral perfusion and BOLD oscillations in children and adolescents. Hum Brain Mapp 2017; 38:2398-2407. [PMID: 28117505 DOI: 10.1002/hbm.23526] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2016] [Revised: 11/05/2016] [Accepted: 12/13/2016] [Indexed: 11/07/2022] Open
Abstract
Healthy brain development involves changes in brain structure and function that are believed to support cognitive maturation. However, understanding how structural changes such as grey matter thinning relate to functional changes is challenging. To gain insight into structure-function relationships in development, the present study took a data driven approach to define age-related patterns of variation in gray matter volume (GMV), cerebral blood flow (CBF) and blood-oxygen level dependent (BOLD) signal variation (fractional amplitude of low-frequency fluctuations; fALFF) in 59 healthy children aged 7-18 years, and examined relationships between modalities. Principal components analysis (PCA) was applied to each modality in parallel, and participant scores for the top components were assessed for age associations. We found that decompositions of CBF, GMV and fALFF all included components for which scores were significantly associated with age. The dominant patterns in GMV and CBF showed significant (GMV) or trend level (CBF) associations with age and a strong spatial overlap, driven by increased signal intensity in default mode network (DMN) regions. GMV, CBF and fALFF additionally showed components accounting for 3-5% of variability with significant age associations. However, these patterns were relatively spatially independent, with small-to-moderate overlap between modalities. Independence of age effects was further demonstrated by correlating individual subject maps between modalities: CBF was significantly less correlated with GMV and fALFF in older children relative to younger. These spatially independent effects of age suggest that the parallel decline observed in global GMV and CBF may not reflect spatially synchronized processes. Hum Brain Mapp 38:2398-2407, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Signe Bray
- Departments of Radiology and Pediatrics, Cumming School of Medicine, University of Calgary, 2500 University Ave NW, Calgary AB, T2N1N4, Canada.,Child and Adolescent Imaging Research (CAIR) Program, 2888 Shaganappi Trail NW, Calgary, AB, T3B 6A8, Canada.,Alberta Children's Hospital Research Institute (ACHRI), 2888 Shaganappi Trail NW, Calgary, AB, T3B 6A8, Canada
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47
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Development of brain networks and relevance of environmental and genetic factors: A systematic review. Neurosci Biobehav Rev 2016; 71:215-239. [DOI: 10.1016/j.neubiorev.2016.08.024] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Revised: 07/10/2016] [Accepted: 08/23/2016] [Indexed: 01/25/2023]
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48
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The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation. Neurosci Biobehav Rev 2016; 70:13-32. [DOI: 10.1016/j.neubiorev.2016.07.027] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 07/21/2016] [Accepted: 07/24/2016] [Indexed: 12/18/2022]
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49
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Meng L, Xiang J. Frequency specific patterns of resting-state networks development from childhood to adolescence: A magnetoencephalography study. Brain Dev 2016; 38:893-902. [PMID: 27287665 DOI: 10.1016/j.braindev.2016.05.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 05/14/2016] [Accepted: 05/16/2016] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The present study investigated frequency dependent developmental patterns of the brain resting-state networks from childhood to adolescence. METHOD Magnetoencephalography (MEG) data were recorded from 20 healthy subjects at resting-state with eyes-open. The resting-state networks (RSNs) was analyzed at source-level. Brain network organization was characterized by mean clustering coefficient and average path length. The correlations between brain network measures and subjects' age during development from childhood to adolescence were statistically analyzed in delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), and beta (12-30Hz) frequency bands. RESULTS A significant positive correlation between functional connectivity with age was found in alpha and beta frequency bands. A significant negative correlation between average path lengths with age was found in beta frequency band. CONCLUSIONS The results suggest that there are significant developmental changes of resting-state networks from childhood to adolescence, which matures from a lattice network to a small-world network.
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Affiliation(s)
- Lu Meng
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110000, China; MEG Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45220, USA.
| | - Jing Xiang
- MEG Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45220, USA
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50
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Cao M, Huang H, Peng Y, Dong Q, He Y. Toward Developmental Connectomics of the Human Brain. Front Neuroanat 2016; 10:25. [PMID: 27064378 PMCID: PMC4814555 DOI: 10.3389/fnana.2016.00025] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 02/29/2016] [Indexed: 12/23/2022] Open
Abstract
Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders.
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Affiliation(s)
- Miao Cao
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of PhiladelphiaPhiladelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphia, PA, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital Affiliated to Capital Medical University Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
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