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Argyropoulou MI, Xydis VG, Astrakas LG. Functional connectivity of the pediatric brain. Neuroradiology 2024; 66:2071-2082. [PMID: 39230715 DOI: 10.1007/s00234-024-03453-5] [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: 03/30/2024] [Accepted: 08/14/2024] [Indexed: 09/05/2024]
Abstract
PURPOSE This review highlights the importance of functional connectivity in pediatric neuroscience, focusing on its role in understanding neurodevelopment and potential applications in clinical practice. It discusses various techniques for analyzing brain connectivity and their implications for clinical interventions in neurodevelopmental disorders. METHODS The principles and applications of independent component analysis and seed-based connectivity analysis in pediatric brain studies are outlined. Additionally, the use of graph analysis to enhance understanding of network organization and topology is reviewed, providing a comprehensive overview of connectivity methods across developmental stages, from fetuses to adolescents. RESULTS Findings from the reviewed studies reveal that functional connectivity research has uncovered significant insights into the early formation of brain circuits in fetuses and neonates, particularly the prenatal origins of cognitive and sensory systems. Longitudinal research across childhood and adolescence demonstrates dynamic changes in brain connectivity, identifying critical periods of development and maturation that are essential for understanding neurodevelopmental trajectories and disorders. CONCLUSION Functional connectivity methods are crucial for advancing pediatric neuroscience. Techniques such as independent component analysis, seed-based connectivity analysis, and graph analysis offer valuable perspectives on brain development, creating new opportunities for early diagnosis and targeted interventions in neurodevelopmental disorders, thereby paving the way for personalized therapeutic strategies.
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Affiliation(s)
- Maria I Argyropoulou
- Department of Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, Ioannina, 45110, Greece.
| | - Vasileios G Xydis
- Department of Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, Ioannina, 45110, Greece
| | - Loukas G Astrakas
- Medical Physics Laboratory, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, Ioannina, 45110, Greece
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Cui W, Chen B, He J, Fan G, Wang S. Dynamic functional network connectivity in children with profound bilateral congenital sensorineural hearing loss. Pediatr Radiol 2024; 54:1738-1747. [PMID: 39134864 DOI: 10.1007/s00247-024-06022-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Functional magnetic resonance imaging (fMRI) studies have revealed extensive functional reorganization in patients with sensorineural hearing loss (SNHL). However, almost no study focuses on the dynamic functional connectivity after hearing loss. OBJECTIVE This study aimed to investigate dynamic functional connectivity changes in children with profound bilateral congenital SNHL under the age of 3 years. MATERIALS AND METHODS Thirty-two children with profound bilateral congenital SNHL and 24 children with normal hearing were recruited for the present study. Independent component analysis identified 18 independent components composing five resting-state networks. A sliding window approach was used to acquire dynamic functional matrices. Three states were identified using the k-means algorithm. Then, the differences in temporal properties and the variance of network efficiency between groups were compared. RESULTS The children with SNHL showed longer mean dwell time and decreased functional connectivity between the auditory network and sensorimotor network in state 3 (P < 0.05), which was characterized by relatively stronger functional connectivity between high-order resting-state networks and motion and perception networks. There was no difference in the variance of network efficiency. CONCLUSIONS These results indicated the functional reorganization due to hearing loss. This study also provided new perspectives for understanding the state-dependent connectivity patterns in children with SNHL.
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Affiliation(s)
- Wenzhuo Cui
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Boyu Chen
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Jiachuan He
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Guoguang Fan
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Shanshan Wang
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
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Siffredi V, Liverani MC, Fernandez N, Freitas LGA, Borradori Tolsa C, Van De Ville D, Hüppi PS, Ha‐Vinh Leuchter R. Impact of a mindfulness-based intervention on neurobehavioral functioning and its association with large-scale brain networks in preterm young adolescents. Psychiatry Clin Neurosci 2024; 78:416-425. [PMID: 38757554 PMCID: PMC11488620 DOI: 10.1111/pcn.13675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 04/15/2024] [Accepted: 04/18/2024] [Indexed: 05/18/2024]
Abstract
AIM Adolescents born very preterm (VPT; <32 weeks of gestation) face an elevated risk of executive, behavioral, and socioemotional difficulties. Evidence suggests beneficial effects of mindfulness-based intervention (MBI) on these abilities. This study seeks to investigate the association between the effects of MBI on executive, behavioral, and socioemotional functioning and reliable changes in large-scale brain networks dynamics during rest in VPT young adolescents who completed an 8-week MBI program. METHODS Neurobehavioral assessments and resting-state functional magnetic resonance imaging were performed before and after MBI in 32 VPT young adolescents. Neurobehavioral abilities in VPT participants were compared with full-term controls. In the VPT group, dynamic functional connectivity was extracted by using the innovation-driven coactivation patterns framework. The reliable change index was used to quantify change after MBI. A multivariate data-driven approach was used to explore associations between MBI-related changes on neurobehavioral measures and temporal brain dynamics. RESULTS Compared with term-born controls, VPT adolescents showed reduced executive and socioemotional functioning before MBI. After MBI, a significant improvement was observed for all measures that were previously reduced in the VPT group. The increase in executive functioning, only, was associated with reliable changes in the duration of activation of large-scale brain networks, including frontolimbic, amygdala-hippocampus, dorsolateral prefrontal, and visual networks. CONCLUSION The improvement in executive functioning after an MBI was associated with reliable changes in large-scale brain network dynamics during rest. These changes encompassed frontolimbic, amygdala-hippocampus, dorsolateral prefrontal, and visual networks that are related to different executive processes including self-regulation, attentional control, and attentional awareness of relevant sensory stimuli.
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Affiliation(s)
- Vanessa Siffredi
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
- Neuro‐X InstituteÉcole polytechnique fédérale de LausanneGenevaSwitzerland
- Department of Radiology and Medical Informatics, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Maria Chiara Liverani
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
- SensoriMotor, Affective and Social Development Laboratory, Faculty of Psychology and Educational SciencesUniversity of GenevaGenevaSwitzerland
| | - Natalia Fernandez
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
| | - Lorena G. A. Freitas
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
- Neuro‐X InstituteÉcole polytechnique fédérale de LausanneGenevaSwitzerland
- Department of Radiology and Medical Informatics, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Cristina Borradori Tolsa
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
| | - Dimitri Van De Ville
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
- Neuro‐X InstituteÉcole polytechnique fédérale de LausanneGenevaSwitzerland
- Department of Radiology and Medical Informatics, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Petra Susan Hüppi
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
| | - Russia Ha‐Vinh Leuchter
- Division of Development and Growth, Department of Paediatrics, Gynaecology and ObstetricsGeneva University Hospitals and University of GenevaGenevaSwitzerland
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4
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Boerwinkle VL, Manjón I, Sussman BL, McGary A, Mirea L, Gillette K, Broman-Fulks J, Cediel EG, Arhin M, Hunter SE, Wyckoff SN, Allred K, Tom D. Resting-State Functional Magnetic Resonance Imaging Network Association With Mortality, Epilepsy, Cognition, and Motor Two-Year Outcomes in Suspected Severe Neonatal Acute Brain Injury. Pediatr Neurol 2024; 152:41-55. [PMID: 38198979 DOI: 10.1016/j.pediatrneurol.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/14/2023] [Accepted: 12/06/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND AND OBJECTIVES In acute brain injury of neonates, resting-state functional magnetic resonance imaging (MRI) (RS) showed incremental association with consciousness, mortality, cognitive and motor development, and epilepsy, with correction for multiple comparisons, at six months postgestation in neonates with suspected acute brain injury (ABI). However, there are relatively few developmental milestones at six months to benchmark against, thus, we extended this cohort study to evaluate two-year outcomes. METHODS In 40 consecutive neonates with ABI and RS, ordinal scores of resting-state networks; MRI, magnetic resonance spectroscopy, and electroencephalography; and up to 42-month outcomes of mortality, general and motor development, Pediatric Cerebral Performance Category Scale (PCPC), and epilepsy informed associations between tests and outcomes. RESULTS Mean gestational age was 37.8 weeks, 68% were male, and 60% had hypoxic-ischemic encephalopathy. Three died in-hospital, four at six to 42 months, and five were lost to follow-up. Associations included basal ganglia network with PCPC (P = 0.0003), all-mortality (P = 0.005), and motor (P = 0.0004); language/frontoparietal network with developmental delay (P = 0.009), PCPC (P = 0.006), and all-mortality (P = 0.01); default mode network with developmental delay (P = 0.003), PCPC (P = 0.004), neonatal intensive care unit mortality (P = 0.01), and motor (P = 0.009); RS seizure onset zone with epilepsy (P = 0.01); and anatomic MRI with epilepsy (P = 0.01). CONCLUSION For the first time, at any age, resting state functional MRI in ABI is associated with long-term epilepsy and RSNs predicted mortality in neonates. Severity of RSN abnormality was associated with incrementally worsened neurodevelopment including cognition, language, and motor function over two years.
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Affiliation(s)
- Varina L Boerwinkle
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina.
| | - Iliana Manjón
- University of Arizona College of Medicine - Tucson, Tucson, Arizona
| | - Bethany L Sussman
- Division of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, Arizona
| | - Alyssa McGary
- Department of Clinical Research, Phoenix Children's Hospital, Phoenix, Arizona
| | - Lucia Mirea
- Department of Clinical Research, Phoenix Children's Hospital, Phoenix, Arizona
| | - Kirsten Gillette
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Jordan Broman-Fulks
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Emilio G Cediel
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Martin Arhin
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Senyene E Hunter
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Sarah N Wyckoff
- Division of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, Arizona
| | - Kimberlee Allred
- Division of Neonatology, Phoenix Children's Hospital, Phoenix, Arizona
| | - Deborah Tom
- Division of Neonatology, Phoenix Children's Hospital, Phoenix, Arizona
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5
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Millevert C, Vidas-Guscic N, Vanherp L, Jonckers E, Verhoye M, Staelens S, Bertoglio D, Weckhuysen S. Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents. J Neurosci 2023; 43:8275-8293. [PMID: 38073598 PMCID: PMC10711730 DOI: 10.1523/jneurosci.1043-23.2023] [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: 09/18/2023] [Revised: 06/09/2023] [Accepted: 09/13/2023] [Indexed: 12/18/2023] Open
Abstract
Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.
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Affiliation(s)
- Charissa Millevert
- Applied & Translational Neurogenomics Group, Vlaams Instituut voor Biotechnology (VIB) Center for Molecular Neurology, VIB, Antwerp 2610, Belgium
- Department of Neurology, University Hospital of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Nicholas Vidas-Guscic
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Liesbeth Vanherp
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Elisabeth Jonckers
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp (MICA), University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Daniele Bertoglio
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- Molecular Imaging Center Antwerp (MICA), University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Sarah Weckhuysen
- Applied & Translational Neurogenomics Group, Vlaams Instituut voor Biotechnology (VIB) Center for Molecular Neurology, VIB, Antwerp 2610, Belgium
- Department of Neurology, University Hospital of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
- Translational Neurosciences, Faculty of Medicine and Health Science, University of Antwerp, Antwerp 2610, Belgium
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Boerwinkle VL, Sussman BL, Manjón I, Mirea L, Suleman S, Wyckoff SN, Bonnell A, Orgill A, Tom DJ. Association of network connectivity via resting state functional MRI with consciousness, mortality, and outcomes in neonatal acute brain injury. Neuroimage Clin 2022; 34:102962. [PMID: 35152054 PMCID: PMC8851268 DOI: 10.1016/j.nicl.2022.102962] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 02/05/2022] [Accepted: 02/07/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND An accurate and comprehensive test of integrated brain network function is needed for neonates during the acute brain injury period to inform on morbidity. This retrospective cohort study assessed whether integrated brain network function acquired by resting state functional MRI during the acute period in neonates with brain injury, is associated with acute exam, neonatal mortality, and 6-month outcomes. METHODS Study subjects included 40 consecutive neonates with resting state functional MRI acquired within 31 days after suspected brain insult from March 2018 to July 2019 at Phoenix Children's Hospital. Acute-period exam and test results were assigned ordinal scores based on severity as documented by respective treating specialists. Analyses (Fisher exact, Wilcoxon-rank sum test, ordinal/multinomial logistic regression) examined association of resting state networks with demographics, presentation, neurological exam, electroencephalogram, anatomical MRI, magnetic resonance spectroscopy, passive task functional MRI, and outcomes of discharge condition, outpatient development, motor tone, seizure, and mortality. RESULTS Subjects had a mean (standard deviation) gestational age of 37.8 (2.6) weeks, a majority were male (63%), with a diagnosis of hypoxic ischemic encephalopathy (68%). Findings at birth included mild distress (48%), moderately abnormal neurological exam (33%), and consciousness characterized as awake but irritable (40%). Significant associations after multiple testing corrections were detected for resting state networks: basal ganglia with outpatient developmental delay (odds ratio [OR], 14.5; 99.4% confidence interval [CI], 2.00-105; P < .001) and motor tone/weakness (OR, 9.98; 99.4% CI, 1.72-57.9; P < .001); language/frontoparietal network with discharge condition (OR, 5.13; 99.4% CI, 1.22-21.5; P = .002) and outpatient developmental delay (OR, 4.77; 99.4% CI, 1.21-18.7; P=.002); default mode network with discharge condition (OR, 3.72; 99.4% CI, 1.01-13.78; P=.006) and neurological exam (P = .002 (FE); OR, 11.8; 99.4% CI, 0.73-191; P = .01 (OLR)); and seizure onset zone with motor tone/weakness (OR, 3.31; 99.4% CI, 1.08-10.1; P=.003). Resting state networks were not detected in three neonates, who died prior to discharge. CONCLUSIONS This study provides level 3 evidence (OCEBM Levels of Evidence Working Group) demonstrating that in neonatal acute brain injury, the degree of abnormality of resting state networks is associated with acute exam and outcomes. Total lack of brain network detection was only found in patients who did not survive.
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Affiliation(s)
- Varina L Boerwinkle
- Division of Pediatric Neurology, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA.
| | - Bethany L Sussman
- Department of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Iliana Manjón
- University of Arizona College of Medicine - Tucson, 1501 N. Campbell Ave, Tucson, AZ 85724, USA
| | - Lucia Mirea
- Department of Clinical Research, Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Saher Suleman
- Division of Pediatric Neurology, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Sarah N Wyckoff
- Department of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Alexandra Bonnell
- Department of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Andrew Orgill
- Department of Clinical Research, Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
| | - Deborah J Tom
- Division of Neonatology, Phoenix Children's Hospital, 1919 E. Thomas Rd, Phoenix, AZ 85016, USA
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Differential age-dependent development of inter-area brain connectivity in term and preterm neonates. Pediatr Res 2022; 92:1017-1025. [PMID: 35094022 PMCID: PMC9586860 DOI: 10.1038/s41390-022-01939-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 12/03/2021] [Accepted: 12/04/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Among preterm infants, higher morbidities of neurological disturbances and developmental delays are critical issues. Resting-state networks (RSNs) in the brain are suitable measures for assessing higher-level neurocognition. Since investigating task-related brain activity is difficult in neonates, assessment of RSNs provides invaluable insight into their neurocognitive development. METHODS The participants, 32 term and 71 preterm neonates, were divided into three groups based on gestational age (GA) at birth. Cerebral hemodynamic activity of RSNs was measured using functional near-infrared spectroscopy in the temporal, frontal, and parietal regions. RESULTS High-GA preterm infants (GA ≥ 30 weeks) had a significantly stronger RSN than low-GA preterm infants and term infants. Regression analyses of RSNs as a function of postnatal age (PNA) revealed a steeper regression line in the high-GA preterm and term infants than in the low-GA infants, particularly for inter-area brain connectivity between the frontal and left temporal areas. CONCLUSIONS Slower PNA-dependent development of the frontal-temporal network found only in the low-GA group suggests that significant brain growth optimal in the intrauterine environment takes place before 30 weeks of gestation. The present study suggests a likely reason for the high incidence of neurodevelopmental impairment in early preterm infants. IMPACT Resting-state fNIRS measurements in three neonate groups differing in gestational age (GA) showed stronger networks in the high-GA preterm infants than in the term and low-GA infants, which was partly explained by postnatal age (PNA). Regression analyses revealed a similar PNA-dependence in the development of the inter-area networks in the frontal and temporal lobes in the high-GA and term infants, and significantly slower development in the low-GA infants. These results suggest that optimal intrauterine brain growth takes place before 30 weeks of gestation. This explains one of the reasons for the high incidence of neurodevelopmental impairment in early preterm infants.
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8
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de Vareilles H, Rivière D, Sun Z, Fischer C, Leroy F, Neumane S, Stopar N, Eijsermans R, Ballu M, Tataranno ML, Benders M, Mangin JF, Dubois J. Shape variability of the central sulcus in the developing brain: a longitudinal descriptive and predictive study in preterm infants. Neuroimage 2021; 251:118837. [PMID: 34965455 DOI: 10.1016/j.neuroimage.2021.118837] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/17/2021] [Accepted: 12/18/2021] [Indexed: 02/04/2023] Open
Abstract
Despite growing evidence of links between sulcation and function in the adult brain, the folding dynamics, occurring mostly before normal-term-birth, is vastly unknown. Looking into the development of cortical sulci in infants can give us keys to address fundamental questions: what is the sulcal shape variability in the developing brain? When are the shape features encoded? How are these morphological parameters related to further functional development? In this study, we aimed to investigate the shape variability of the developing central sulcus, which is the frontier between the primary somatosensory and motor cortices. We studied a cohort of 71 extremely preterm infants scanned twice using MRI - once around 30 weeks post-menstrual age (w PMA) and once at term-equivalent age, around 40w PMA -, in order to quantify the sulcus's shape variability using manifold learning, regardless of age-group or hemisphere. We then used these shape descriptors to evaluate the sulcus's variability at both ages and to assess hemispheric and age-group specificities. This led us to propose a description of ten shape features capturing the variability in the central sulcus of preterm infants. Our results suggested that most of these features (8/10) are encoded as early as 30w PMA. We unprecedentedly observed hemispheric asymmetries at both ages, and the one captured at term-equivalent age seems to correspond with the asymmetry pattern previously reported in adults. We further trained classifiers in order to explore the predictive value of these shape features on manual performance at 5 years of age (handedness and fine motor outcome). The central sulcus's shape alone showed a limited but relevant predictive capacity in both cases. The study of sulcal shape features during early neurodevelopment may participate to a better comprehension of the complex links between morphological and functional organization of the developing brain.
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Affiliation(s)
- H de Vareilles
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France.
| | - D Rivière
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - Z Sun
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - C Fischer
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - F Leroy
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France; Université Paris-Saclay, NeuroSpin-UNICOG, Inserm, CEA, Gif-sur-Yvette, France
| | - S Neumane
- Université de Paris, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
| | - N Stopar
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - R Eijsermans
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - M Ballu
- Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, United Kingdom
| | - M L Tataranno
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - Mjnl Benders
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - J F Mangin
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - J Dubois
- Université de Paris, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
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9
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Huang P, Luan XH, Xie Z, Li MT, Chen SD, Liu J, Jia XZ, Cao L, Zhou HY. Altered Local Brain Amplitude of Fluctuations in Patients With Myotonic Dystrophy Type 1. Front Aging Neurosci 2021; 13:790632. [PMID: 34955817 PMCID: PMC8703136 DOI: 10.3389/fnagi.2021.790632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 11/17/2021] [Indexed: 01/18/2023] Open
Abstract
This study is aimed at investigating the characteristics of the spontaneous brain activity in patients with myotonic dystrophy type 1 (DM1). A total of 18 patients with DM1 and 18 healthy controls (HCs) were examined by resting-state functional MRI. Combined methods include amplitude of low-frequency fluctuations (ALFFs), the fractional amplitude of low-frequency fluctuations (fALFFs), and Wavelet transform-based ALFFs (Wavelet-ALFFs) with standardization, percent amplitude of fluctuation (PerAF) with/without standardization were applied to evaluate the spontaneous brain activity of patients with DM1. Compared with HCs, patients with DM1 showed decreased ALFFs and Wavelet-ALFFs in the bilateral precuneus (PCUN), angular gyrus (ANG), inferior parietal, but supramarginal and angular gyri (IPL), posterior cingulate gyrus (PCG), superior frontal gyrus, medial (SFGmed), middle occipital gyrus (MOG), which were mainly distributed in the brain regions of default mode network (DMN). Decreased ALFFs and Wavelet-ALFFs were also seen in bilateral middle frontal gyrus (MFG), inferior frontal gyrus, opercular part (IFGoperc), which were the main components of the executive control network (ECN). Patients with DM1 also showed decreased fALFFs in SFGmed.R, the right anterior cingulate and paracingulate gyri (ACGR), bilateral MFG. Reduced PerAF in bilateral PCUN, ANG, PCG, MOG, and IPLL as well as decreased PerAF without standardization in PCUNR and bilateral PCG also existed in patients with DM1. In conclusion, patients with DM1 had decreased activity in DMN and ECN with increased fluctuations in the temporal cortex and cerebellum. Decreased brain activity in DMN was the most repeatable and reliable with PCUN and PCG being the most specific imaging biomarker of brain dysfunction in patients with DM1.
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Affiliation(s)
- Pei Huang
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xing-Hua Luan
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Neurology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Meng-Ting Li
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Sheng-Di Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xi-Ze Jia
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Li Cao
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Neurology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Hai-Yan Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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