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Blanchett R, Chen H, Vlasova RM, Cornea E, Maza M, Davenport M, Reinhartsen D, DeRamus M, Edmondson Pretzel R, Gilmore JH, Hooper SR, Styner MA, Gao W, Knickmeyer RC. White matter microstructure and functional connectivity in the brains of infants with Turner syndrome. Cereb Cortex 2024; 34:bhae351. [PMID: 39256896 PMCID: PMC11387115 DOI: 10.1093/cercor/bhae351] [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: 07/03/2023] [Revised: 08/01/2024] [Accepted: 08/13/2024] [Indexed: 09/12/2024] Open
Abstract
Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.
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Affiliation(s)
- Reid Blanchett
- Genetics and Genome Sciences, Michigan State University, Biomedical & Physical Sciences, Room 2165, East Lansing, MI 48824, United States
- Department of Epigenetics, Van Andel Research Institute, 33 Bostwick Ave NE, Grand Rapids, MI 49503, United States
| | - Haitao Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Roza M Vlasova
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Emil Cornea
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Maria Maza
- Department of Psychology and Neuroscience, Campus Box #3270, 235 E. Cameron Avenue, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Marsha Davenport
- Department of Pediatrics, 333 South Columbia Street, Suite 260 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Debra Reinhartsen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Margaret DeRamus
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Rebecca Edmondson Pretzel
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - John H Gilmore
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Stephen R Hooper
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Health Sciences, Bondurant Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Martin A Styner
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Computer Science, Campus Box 3175, Brooks Computer Science Building, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Rebecca C Knickmeyer
- Department of Pediatrics and Human Development, Life Sciences Bldg. 1355 Bogue, #B240B, Michigan State University, East Lansing, MI 48824, United States
- Institute for Quantitative Health Sciences and Engineering, Room 2114, 775 Woodlot Dr., East Lansing, MI 48824, United States
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2
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Wainwright CE, Vidmar S, Anderson V, Bourgeat P, Byrnes C, Carlin JB, Cheney J, Cooper P, Davidson A, Gailer N, Grayson-Collins J, Quittner A, Robertson C, Salvado O, Zannino D, Armstrong FD. Long-term outcomes of early exposure to repeated general anaesthesia in children with cystic fibrosis (CF-GAIN): a multicentre, open-label, randomised controlled phase 4 trial. THE LANCET. RESPIRATORY MEDICINE 2024; 12:703-713. [PMID: 38851197 DOI: 10.1016/s2213-2600(24)00170-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/14/2024] [Accepted: 05/21/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Long-term effects of early, recurrent human exposure to general anaesthesia remain unknown. The Australasian Cystic Fibrosis Bronchoalveolar Lavage (ACFBAL) trial provided an opportunity to examine this issue in children randomly assigned in infancy to either repeated bronchoalveolar-lavage (BAL)-directed therapy with general anaesthesia or standard care with no planned lavages up to 5 years of age when all children received BAL-directed therapy under general anaesthesia. METHODS This multicentre, randomised, open-label phase 4 trial (CF-GAIN) used the original ACFBAL trial randomisation at 3·6 months (SD 1·6) to BAL-directed therapy or standard-care groups to assess the impact of general anaesthesia exposures over early childhood. Children who completed the ACFBAL trial, with a mean age of 5·1 (SD 0·18) years, received standardised neurobehavioural and health-related-quality-of-life assessment and brain MRI scans between Oct 8, 2013, and June 30, 2017, at a mean age of 12·8 (SD 1·7) years at three hospitals in Australia and one hospital in New Zealand. The primary outcome was a composite score of performance on a standardised, computer-based assessment of child attention, processing speed, and response inhibition skills (Conners Continuous Performance test, second edition). Secondary outcomes included intellectual function, other neurobehavioural measures, and brain imaging as an exploratory outcome. The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN 12613000057785) and is completed. FINDINGS At 2 years, the BAL-directed therapy group (n=52) and standard-care group (n=45) had a median of 2·0 (IQR 1·0-3·0) and 0·0 (0·0-0·0) exposures, respectively. At completion of the ACFBAL trial, the BAL-directed therapy group had a median of 6·0 (4·0-9·5) exposures and the standard-care group 2·0 (1·0-4·0) exposures. At CF-GAIN completion, the BAL-directed therapy group had a median of 10·0 (IQR 6·5-14·5) exposures and the standard-care group 4·0 (3·0-7·0) exposures. Cumulative general anaesthesia exposure time was not prospectively collected but, for those with complete cumulative exposure time data to the end of the ACFBAL trial, the median cumulative exposure time for the BAL-directed therapy group (n=29) was 180 (IQR 140-285) min and for the standard-care group (n=32) was 48 (30-122) min. The mean Conners Continuous Performance test, second edition composite score was 51 (SD 8·1) in BAL-directed therapy group and 53 (8·8) in the standard-care group; difference -1·7 (95% CI -5·2 to 1·7; p=0·32) with similar performance on other neurobehavioural measures, including measures of executive function, intellectual quotient scores, and brain imaging. INTERPRETATION Our findings suggest that repeated general anaesthesia exposure in young children with cystic fibrosis is not related to functional impairment in attention, intellectual quotient, executive function, or brain structure compared with a group with fewer and shorter cumulative anaesthesia durations. FUNDING National Health and Medical Research Council Australia, Queensland Government Health Service and Clinical Innovation Fellowship, and the Children's Hospital Foundation Queensland.
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Affiliation(s)
- Claire Elizabeth Wainwright
- Centre for Child Health Research, University of Queensland, South Brisbane, QLD, Australia; Department of Respiratory and Sleep Medicine, Queensland Children's Hospital Brisbane, South Brisbane, QLD, Australia.
| | - Suzanna Vidmar
- Murdoch Children's Research Institute, Parkville, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Vicki Anderson
- Murdoch Children's Research Institute, Parkville, VIC, Australia
| | | | | | - John Brooke Carlin
- Murdoch Children's Research Institute, Parkville, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Joyce Cheney
- Centre for Child Health Research, University of Queensland, South Brisbane, QLD, Australia; Department of Respiratory and Sleep Medicine, Queensland Children's Hospital Brisbane, South Brisbane, QLD, Australia
| | - Peter Cooper
- The Children's Hospital at Westmead, Sydney, NSW, Australia
| | - Andrew Davidson
- Murdoch Children's Research Institute, Parkville, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Royal Children's Hospital, Melbourne, VIC, Australia
| | - Nicholas Gailer
- Centre for Child Health Research, University of Queensland, South Brisbane, QLD, Australia
| | | | - Alexandra Quittner
- Joe DiMaggio Cystic Fibrosis, Pulmonary and Sleep Center, Hollywood, FL, USA
| | | | | | - Diana Zannino
- Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Floyd Daniel Armstrong
- University of Miami Miller School of Medicine & Holtz Children's Hospital, Miami, FL, USA
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3
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Ozarkar SS, Patel RKR, Vulli T, Smith AL, Shen MD, Burette AC, Philpot BD, Styner MA, Hazlett HC. Comparative profiling of white matter development in the human and mouse brain reveals volumetric deficits and delayed myelination in Angelman syndrome. RESEARCH SQUARE 2024:rs.3.rs-4681861. [PMID: 39149488 PMCID: PMC11326408 DOI: 10.21203/rs.3.rs-4681861/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Background Angelman syndrome (AS), a severe neurodevelopmental disorder resulting from the loss of the maternal UBE3A gene, is marked by changes in the brain's white matter (WM). The extent of WM abnormalities seems to correlate with the severity of clinical symptoms, but these deficits are still not well characterized or understood. This study provides the first large-scale measurement of WM volume reduction in children with AS. Furthermore, we probed the underlying neuropathology by examining the progression of myelination in an AS mouse model. Methods We conducted magnetic resonance imaging (MRI) on children with AS (n=32) and neurotypical controls (n=99) aged 0.5-12 years. In parallel, we examined myelination in postnatal Ube3a maternal-null mice (Ube3a m-/p+; AS model), Ube3a paternal-null mice (Ube3a m+/p-), and wildtype controls (Ube3a m+/p+) using immunohistochemistry, Western blotting, and electron microscopy. Results Our data revealed that AS individuals exhibit significant reductions in brain volume by ~1 year of age, with WM reduced by 26% and gray matter by 21% by 6-12 years of age-approximately twice the reductions observed in the adult AS mouse model. In our AS mouse model, we saw a global delay in the onset of myelination, which normalized within days (likely corresponding to months or years in human development). This myelination delay is caused by the loss of UBE3A in neurons rather than UBE3A haploinsufficiency in oligodendrocytes. Interestingly, ultrastructural analyses did not reveal any abnormalities in myelinated or unmyelinated axons. Limitations It is difficult to extrapolate the timing and duration of the myelination delay observed in AS model mice to individuals with AS. Conclusions This study reveals WM deficits as a hallmark in children with AS, demonstrating for the first time that these deficits are already apparent at 1 year of age. Parallel studies in a mouse model of AS show that these deficits may be associated with delayed onset of myelination due to the loss of neuronal (but not glial) UBE3A. These findings emphasize the potential of WM as both a therapeutic target for interventions and a valuable biomarker for tracking the progression of AS and the effectiveness of potential treatments.
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Affiliation(s)
- Siddhi S Ozarkar
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Ridthi K-R Patel
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tasmai Vulli
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Audrey L Smith
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Mark D Shen
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alain C Burette
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Benjamin D Philpot
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Martin A Styner
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel
| | - Heather C Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC
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4
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Janson E, Koolschijn PCMP, Schipper L, Boerma TD, Wijnen FNK, de Boode WP, van den Akker CHP, Licht-van der Stap RG, Nuytemans DHGM, Onland W, Obermann-Borst SA, Dudink J, de Theije CGM, Benders MJNL, van der Aa NE. Dolphin CONTINUE: a multi-center randomized controlled trial to assess the effect of a nutritional intervention on brain development and long-term outcome in infants born before 30 weeks of gestation. BMC Pediatr 2024; 24:384. [PMID: 38849784 PMCID: PMC11157897 DOI: 10.1186/s12887-024-04849-1] [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: 05/18/2023] [Accepted: 05/22/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND Preterm born infants are at risk for brain injury and subsequent developmental delay. Treatment options are limited, but optimizing postnatal nutrition may improve brain- and neurodevelopment in these infants. In pre-clinical animal models, combined supplementation of docosahexaenoic acid (DHA), choline, and uridine-5-monophosphate (UMP) have shown to support neuronal membrane formation. In two randomized controlled pilot trials, supplementation with the investigational product was associated with clinically meaningful improvements in cognitive, attention, and language scores. The present study aims to assess the effect of a similar nutritional intervention on brain development and subsequent neurodevelopmental outcome in infants born very and extremely preterm. METHODS This is a randomized, placebo-controlled, double-blinded, parallel-group, multi-center trial. A total of 130 infants, born at less than 30 weeks of gestation, will be randomized to receive a test or control product between term-equivalent age and 12 months corrected age (CA). The test product is a nutrient blend containing DHA, choline, and UMP amongst others. The control product contains only fractions of the active components. Both products are isocaloric powder supplements which can be added to milk and solid feeds. The primary outcome parameter is white matter integrity at three months CA, assessed using diffusion-tensor imaging (DTI) on MRI scanning. Secondary outcome parameters include volumetric brain development, cortical thickness, cortical folding, the metabolic and biochemical status of the brain, and product safety. Additionally, language, cognitive, motor, and behavioral development will be assessed at 12 and 24 months CA, using the Bayley Scales of Infant Development III and digital questionnaires (Dutch version of the Communicative Development Inventories (N-CDI), Ages and Stages Questionnaire 4 (ASQ-4), and Parent Report of Children's Abilities - Revised (PARCA-R)). DISCUSSION The investigated nutritional intervention is hypothesized to promote brain development and subsequent neurodevelopmental outcome in preterm born infants who have an inherent risk of developmental delay. Moreover, this innovative study may give rise to new treatment possibilities and improvements in routine clinical care. TRIAL REGISTRATION WHO International Clinical Trials Registry: NL-OMON56181 (registration assigned October 28, 2021).
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Affiliation(s)
- E Janson
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands.
- University Medical Center Utrecht Brain Center, Utrecht, The Netherlands.
| | | | - L Schipper
- Danone Nutricia Research, Utrecht, The Netherlands
| | - T D Boerma
- Institute for Language Sciences, Utrecht University, Utrecht, The Netherlands
| | - F N K Wijnen
- Institute for Language Sciences, Utrecht University, Utrecht, The Netherlands
| | - W P de Boode
- Department of Neonatology, Radboud University Medical Center, Radboud Institute for Health Sciences, Amalia Children's Hospital, Nijmegen, The Netherlands
| | - C H P van den Akker
- Department of Pediatrics and Neonatology, Emma Children's Hospital, Amsterdam University Medical Center, Location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development, Research Institute, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | | | - W Onland
- Neonatology Network Netherlands, Amsterdam, The Netherlands
| | | | - J Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
| | - C G M de Theije
- Department for Developmental Origins of Disease, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
| | - M J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
| | - N E van der Aa
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
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5
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Rokach M, Portioli C, Brahmachari S, Estevão BM, Decuzzi P, Barak B. Tackling myelin deficits in neurodevelopmental disorders using drug delivery systems. Adv Drug Deliv Rev 2024; 207:115218. [PMID: 38403255 DOI: 10.1016/j.addr.2024.115218] [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: 11/14/2023] [Revised: 01/27/2024] [Accepted: 02/20/2024] [Indexed: 02/27/2024]
Abstract
Interest in myelin and its roles in almost all brain functions has been greatly increasing in recent years, leading to countless new studies on myelination, as a dominant process in the development of cognitive functions. Here, we explore the unique role myelin plays in the central nervous system and specifically discuss the results of altered myelination in neurodevelopmental disorders. We present parallel developmental trajectories involving myelination that correlate with the onset of cognitive impairment in neurodevelopmental disorders and discuss the key challenges in the treatment of these chronic disorders. Recent developments in drug repurposing and nano/micro particle-based therapies are reviewed as a possible pathway to circumvent some of the main hurdles associated with early intervention, including patient's adherence and compliance, side effects, relapse, and faster route to possible treatment of these disorders. The strategy of drug encapsulation overcomes drug solubility and metabolism, with the possibility of drug targeting to a specific compartment, reducing side effects upon systemic administration.
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Affiliation(s)
- May Rokach
- Sagol School of Neuroscience, Tel-Aviv University, Israel
| | - Corinne Portioli
- Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Sayanti Brahmachari
- Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Bianca Martins Estevão
- Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Paolo Decuzzi
- Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Boaz Barak
- Sagol School of Neuroscience, Tel-Aviv University, Israel; Faculty of Social Sciences, The School of Psychological Sciences, Tel-Aviv University, Israel.
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6
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Donald KA, Hendrikse CJ, Roos A, Wedderburn CJ, Subramoney S, Ringshaw JE, Bradford L, Hoffman N, Burd T, Narr KL, Woods RP, Zar HJ, Joshi SH, Stein DJ. Prenatal alcohol exposure and white matter microstructural changes across the first 6-7 years of life: A longitudinal diffusion tensor imaging study of a South African birth cohort. Neuroimage Clin 2024; 41:103572. [PMID: 38309186 PMCID: PMC10847766 DOI: 10.1016/j.nicl.2024.103572] [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: 06/15/2023] [Revised: 01/24/2024] [Accepted: 01/26/2024] [Indexed: 02/05/2024]
Abstract
Prenatal alcohol exposure (PAE) can affect brain development in early life, but few studies have investigated the effects of PAE on trajectories of white matter tract maturation in young children. Here we used diffusion weighted imaging (DWI) repeated over three time points, to measure the effects of PAE on patterns of white matter microstructural development during the pre-school years. Participants were drawn from the Drakenstein Child Health Study (DCHS), an ongoing birth cohort study conducted in a peri-urban community in the Western Cape, South Africa. A total of 342 scans acquired from 237 children as neonates (N = 82 scans: 30 PAE; 52 controls) and at ages 2-3 (N = 121 scans: 27 PAE; 94 controls) and 6-7 years (N = 139 scans: 45 PAE; 94 controls) were included. Maternal alcohol use during pregnancy and other antenatal covariates were collected from 28 to 32 weeks' gestation. Linear mixed effects models with restricted maxium likelihood to accommodate missing data were implemented to investigate the effects of PAE on fractional anisotropy (FA) and mean diffusivity (MD) in specific white matter tracts over time, while adjusting for child sex and maternal education. We found significant PAE-by-time effects on trajectories of FA development in the left superior cerebellar peduncle (SCP-L: p = 0.001; survived FDR correction) and right superior longitudinal fasciculus (SLF-R: p = 0.046), suggesting altered white matter development among children with PAE. Compared with controls, children with PAE demonstrated a more rapid change in FA in these tracts from the neonatal period to 2-3 years of age, followed by a more tapered trajectory for the period from 2-3 to 6-7 years of age, with these trajectories differing from unexposed control children. Given their supporting roles in various aspects of neurocognitive functioning (i.e., motor regulation, learning, memory, language), altered patterns of maturation in the SCP and SLF may contribute to a spectrum of physical, social, emotional, and cognitive difficulties often experienced by children with PAE. This study highlights the value of repeated early imaging in longitudinal studies of PAE, and focus for early childhood as a critical window of potential susceptibility as well as an opportunity for early intervention.
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Affiliation(s)
- K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - C J Hendrikse
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - A Roos
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa; South African Medical Research Council (SAMRC), Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
| | - C J Wedderburn
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - S Subramoney
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - J E Ringshaw
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - L Bradford
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - N Hoffman
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - T Burd
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; South African Medical Research Council (SAMRC), Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - K L Narr
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - R P Woods
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States; The Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, United States; David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; South African Medical Research Council (SAMRC), Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - S H Joshi
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - D J Stein
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa; South African Medical Research Council (SAMRC), Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
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7
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Alex AM, Aguate F, Botteron K, Buss C, Chong YS, Dager SR, Donald KA, Entringer S, Fair DA, Fortier MV, Gaab N, Gilmore JH, Girault JB, Graham AM, Groenewold NA, Hazlett H, Lin W, Meaney MJ, Piven J, Qiu A, Rasmussen JM, Roos A, Schultz RT, Skeide MA, Stein DJ, Styner M, Thompson PM, Turesky TK, Wadhwa PD, Zar HJ, Zöllei L, de Los Campos G, Knickmeyer RC. A global multicohort study to map subcortical brain development and cognition in infancy and early childhood. Nat Neurosci 2024; 27:176-186. [PMID: 37996530 PMCID: PMC10774128 DOI: 10.1038/s41593-023-01501-6] [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: 04/11/2022] [Accepted: 10/16/2023] [Indexed: 11/25/2023]
Abstract
The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.
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Affiliation(s)
- Ann M Alex
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
| | - Fernando Aguate
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
- Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, MI, USA
| | - Kelly Botteron
- Mallinickrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Claudia Buss
- Department of Medical Psychology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Yap-Seng Chong
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - Stephen R Dager
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Kirsten A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sonja Entringer
- Department of Medical Psychology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Diagnostic & Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore
| | - Nadine Gaab
- Harvard Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Nynke A Groenewold
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SA-MRC) Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
| | - Heather Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Weili Lin
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael J Meaney
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- NUS (Suzhou) Research Institute, National University of Singapore, Suzhou, China
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
- Institute of Data Science, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, China
| | - Jerod M Rasmussen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Annerine Roos
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Robert T Schultz
- Center for Autism Research, Children's Hospital of Philadelphia and the University of Pennsylvania, Philadelphia, PA, USA
| | - Michael A Skeide
- Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dan J Stein
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Martin Styner
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, CA, USA
| | - Ted K Turesky
- Harvard Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Pathik D Wadhwa
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
- Departments of Psychiatry and Human Behavior, Obstetrics & Gynecology, Epidemiology, University of California, Irvine, Irvine, CA, USA
| | - Heather J Zar
- South African Medical Research Council (SA-MRC) Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Gustavo de Los Campos
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
- Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, MI, USA
- Department of Statistics & Probability, Michigan State University, East Lansing, MI, USA
| | - Rebecca C Knickmeyer
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA.
- Department of Pediatrics and Human Development, Michigan State University, East Lansing, MI, USA.
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8
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De Benedictis A, Rossi-Espagnet MC, de Palma L, Sarubbo S, Marras CE. Structural networking of the developing brain: from maturation to neurosurgical implications. Front Neuroanat 2023; 17:1242757. [PMID: 38099209 PMCID: PMC10719860 DOI: 10.3389/fnana.2023.1242757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023] Open
Abstract
Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.
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Affiliation(s)
| | | | - Luca de Palma
- Clinical and Experimental Neurology, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Silvio Sarubbo
- Department of Neurosurgery, Santa Chiara Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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9
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Mucignat-Caretta C, Soravia G. Positive or negative environmental modulations on human brain development: the morpho-functional outcomes of music training or stress. Front Neurosci 2023; 17:1266766. [PMID: 38027483 PMCID: PMC10657192 DOI: 10.3389/fnins.2023.1266766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/18/2023] [Indexed: 12/01/2023] Open
Abstract
In the last couple of decades, the study of human living brain has benefitted of neuroimaging and non-invasive electrophysiological techniques, which are particularly valuable during development. A number of studies allowed to trace the usual stages leading from pregnancy to adult age, and relate them to functional and behavioral measurements. It was also possible to explore the effects of some interventions, behavioral or not, showing that the commonly followed pathway to adulthood may be steered by external interventions. These events may result in behavioral modifications but also in structural changes, in some cases limiting plasticity or extending/modifying critical periods. In this review, we outline the healthy human brain development in the absence of major issues or diseases. Then, the effects of negative (different stressors) and positive (music training) environmental stimuli on brain and behavioral development is depicted. Hence, it may be concluded that the typical development follows a course strictly dependent from environmental inputs, and that external intervention can be designed to positively counteract negative influences, particularly at young ages. We also focus on the social aspect of development, which starts in utero and continues after birth by building social relationships. This poses a great responsibility in handling children education and healthcare politics, pointing to social accountability for the responsible development of each child.
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Affiliation(s)
| | - Giulia Soravia
- Department of Mother and Child Health, University of Padova, Padova, Italy
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10
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Ćirović M, Jeličić L, Maksimović S, Fatić S, Marisavljević M, Bošković Matić T, Subotić M. EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up. Diagnostics (Basel) 2023; 13:2878. [PMID: 37761245 PMCID: PMC10529253 DOI: 10.3390/diagnostics13182878] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/21/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.
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Affiliation(s)
- Milica Ćirović
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
- Department of Speech, Language and Hearing Sciences, Institute for Experimental Phonetics and Speech Pathology, 11000 Belgrade, Serbia
| | - Ljiljana Jeličić
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
- Department of Speech, Language and Hearing Sciences, Institute for Experimental Phonetics and Speech Pathology, 11000 Belgrade, Serbia
| | - Slavica Maksimović
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
- Department of Speech, Language and Hearing Sciences, Institute for Experimental Phonetics and Speech Pathology, 11000 Belgrade, Serbia
| | - Saška Fatić
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
- Department of Speech, Language and Hearing Sciences, Institute for Experimental Phonetics and Speech Pathology, 11000 Belgrade, Serbia
| | - Maša Marisavljević
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
- Department of Speech, Language and Hearing Sciences, Institute for Experimental Phonetics and Speech Pathology, 11000 Belgrade, Serbia
| | - Tatjana Bošković Matić
- Department of Neurology, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia;
- Clinic of Neurology, University Clinical Centre of Kragujevac, 34000 Kragujevac, Serbia
| | - Miško Subotić
- Cognitive Neuroscience Department, Research and Development Institute “Life Activities Advancement Institute”, 11000 Belgrade, Serbia; (M.Ć.); (S.M.); (S.F.); (M.M.); (M.S.)
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11
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Estrada KA, Govindaraj S, Abdi H, Moraglia LE, Wolff JJ, Meera SS, Dager SR, McKinstry RC, Styner MA, Zwaigenbaum L, Piven J, Swanson MR. Language exposure during infancy is negatively associated with white matter microstructure in the arcuate fasciculus. Dev Cogn Neurosci 2023; 61:101240. [PMID: 37060675 PMCID: PMC10130606 DOI: 10.1016/j.dcn.2023.101240] [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: 10/30/2022] [Revised: 04/04/2023] [Accepted: 04/04/2023] [Indexed: 04/17/2023] Open
Abstract
Decades of research have established that the home language environment, especially quality of caregiver speech, supports language acquisition during infancy. However, the neural mechanisms behind this phenomenon remain under studied. In the current study, we examined associations between the home language environment and structural coherence of white matter tracts in 52 typically developing infants from English speaking homes in a western society. Infants participated in at least one MRI brain scan when they were 3, 6, 12, and/or 24 months old. Home language recordings were collected when infants were 9 and/or 15 months old. General linear regression models indicated that infants who heard the most adult words and participated in the most conversational turns at 9 months of age also had the lowest fractional anisotropy in the left posterior parieto-temporal arcuate fasciculus at 24 months. Similarly, infants who vocalized the most at 9 months also had the lowest fractional anisotropy in the same tract at 6 months of age. This is one of the first studies to report significant associations between caregiver speech collected in the home and white matter structural coherence in the infant brain. The results are in line with prior work showing that protracted white matter development during infancy confers a cognitive advantage.
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Affiliation(s)
- Katiana A Estrada
- Department of Psychological Sciences, Purdue University, West Lafayette, IN 47906, USA; Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Sharnya Govindaraj
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Hervé Abdi
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Luke E Moraglia
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Jason J Wolff
- Department of Educational Psychology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Shoba Sreenath Meera
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, India
| | - Stephen R Dager
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Robert C McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton AB T6G 2R3, Canada
| | - Joseph Piven
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Meghan R Swanson
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA.
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12
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Pittner K, Rasmussen J, Lim MM, Gilmore JH, Styner M, Entringer S, Wadhwa PD, Buss C. Sleep across the first year of life is prospectively associated with brain volume in 12-months old infants. Neurobiol Sleep Circadian Rhythms 2023. [DOI: 10.1016/j.nbscr.2023.100091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023] Open
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13
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Huber E, Corrigan NM, Yarnykh VL, Ferjan Ramírez N, Kuhl PK. Language Experience during Infancy Predicts White Matter Myelination at Age 2 Years. J Neurosci 2023; 43:1590-1599. [PMID: 36746626 PMCID: PMC10008053 DOI: 10.1523/jneurosci.1043-22.2023] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 01/06/2023] [Accepted: 01/06/2023] [Indexed: 02/08/2023] Open
Abstract
Parental input is considered a key predictor of language achievement during the first years of life, yet relatively few studies have assessed the effects of parental language input and parent-infant interactions on early brain development. We examined the relationship between measures of parent and child language, obtained from naturalistic home recordings at child ages 6, 10, 14, 18, and 24 months, and estimates of white matter myelination, derived from quantitative MRI at age 2 years (mean = 26.30 months, SD = 1.62, N = 22). Analysis of the white matter focused on dorsal pathways associated with expressive language development and long-term language ability, namely, the left arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Frequency of parent-infant conversational turns (CT) uniquely predicted myelin density estimates in both the AF and SLF. Moreover, the effect of CT remained significant while controlling for total adult speech and child speech-related utterances, suggesting a specific role for interactive language experience, rather than simply speech exposure or production. An exploratory analysis of 18 additional tracts, including the right AF and SLF, indicated a high degree of anatomic specificity. Longitudinal analyses of parent and child language variables indicated an effect of CT as early as 6 months of age, as well as an ongoing effect over infancy. Together, these results link parent-infant conversational turns to white matter myelination at age 2 years, and suggest that early, interactive experiences with language uniquely contribute to the development of white matter associated with long-term language ability.SIGNIFICANCE STATEMENT Children's earliest experiences with language are thought to have profound and lasting developmental effects. Recent studies suggest that intervention can increase the quality of parental language input and improve children's learning outcomes. However, important questions remain about the optimal timing of intervention, and the relationship between specific aspects of language experience and brain development. We report that parent-infant turn-taking during home language interactions correlates with myelination of language related white matter pathways through age 2 years. Effects were independent of total speech exposure and infant vocalizations and evident starting at 6 months of age, suggesting that structured language interactions throughout infancy may uniquely support the ongoing development of brain systems critical to long-term language ability.
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Affiliation(s)
- Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, Washington 98195
| | - Naja Ferjan Ramírez
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Linguistics, University of Washington, Seattle, Washington 98195
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
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14
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Bowe AK, Lightbody G, Staines A, Murray DM. Big data, machine learning, and population health: predicting cognitive outcomes in childhood. Pediatr Res 2023; 93:300-307. [PMID: 35681091 PMCID: PMC7614199 DOI: 10.1038/s41390-022-02137-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/05/2022] [Accepted: 05/17/2022] [Indexed: 11/09/2022]
Abstract
The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a complex public health issue rooted in the social determinants of health, exacerbated by inequity, characterised by intergenerational transmission, and which will continue unabated without novel approaches to address it. Early life, the period of optimal neuroplasticity, presents a window of opportunity for early intervention to improve cognitive development. Unfortunately for many, this window will be missed, and intervention may never occur or occur only when overt signs of cognitive delay manifest. In this review, we explore the potential value of ML and big data analysis in the early identification of children at risk for poor cognitive outcome, an area where there is an apparent dearth of research. We compare and contrast traditional statistical methods with ML approaches, provide examples of how ML has been used to date in the field of neurodevelopmental disorders, and present a discussion of the opportunities and risks associated with its use at a population level. The review concludes by highlighting potential directions for future research in this area. IMPACT: To date, the application of machine learning to address population health challenges in paediatrics lags behind other clinical applications. This review provides an overview of the public health challenge we face in addressing disparities in childhood cognitive development and focuses on the cornerstone of early intervention. Recent advances in our ability to collect large volumes of data, and in analytic capabilities, provide a potential opportunity to improve current practices in this field. This review explores the potential role of machine learning and big data analysis in the early identification of children at risk for poor cognitive outcomes.
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Affiliation(s)
- Andrea K. Bowe
- grid.7872.a0000000123318773INFANT Research Centre, University College Cork, Cork, Ireland
| | - Gordon Lightbody
- grid.7872.a0000000123318773INFANT Research Centre, University College Cork, Cork, Ireland ,grid.7872.a0000000123318773Department of Electrical and Electronic Engineering, University College Cork, Cork, Ireland
| | - Anthony Staines
- grid.15596.3e0000000102380260School of Nursing, Psychotherapy, and Community Health, Dublin City University, Dublin, Ireland
| | - Deirdre M. Murray
- grid.7872.a0000000123318773INFANT Research Centre, University College Cork, Cork, Ireland
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15
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Weiss Y, Huber E, Ferjan Ramírez N, Corrigan NM, Yarnykh VL, Kuhl PK. Language input in late infancy scaffolds emergent literacy skills and predicts reading related white matter development. Front Hum Neurosci 2022; 16:922552. [PMID: 36457757 PMCID: PMC9705348 DOI: 10.3389/fnhum.2022.922552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 10/26/2022] [Indexed: 11/17/2022] Open
Abstract
Longitudinal studies provide the unique opportunity to test whether early language provides a scaffolding for the acquisition of the ability to read. This study tests the hypothesis that parental language input during the first 2 years of life predicts emergent literacy skills at 5 years of age, and that white matter development observed early in the 3rd year (at 26 months) may help to account for these effects. We collected naturalistic recordings of parent and child language at 6, 10, 14, 18, and 24 months using the Language ENvironment Analysis system (LENA) in a group of typically developing infants. We then examined the relationship between language measures during infancy and follow-up measures of reading related skills at age 5 years, in the same group of participants (N = 53). A subset of these children also completed diffusion and quantitative MRI scans at age 2 years (N = 20). Within this subgroup, diffusion tractography was used to identify white matter pathways that are considered critical to language and reading development, namely, the arcuate fasciculus (AF), superior and inferior longitudinal fasciculi, and inferior occipital-frontal fasciculus. Quantitative macromolecular proton fraction (MPF) mapping was used to characterize myelin density within these separately defined regions of interest. The longitudinal data were then used to test correlations between early language input and output, white matter measures at age 2 years, and pre-literacy skills at age 5 years. Parental language input, child speech output, and parent-child conversational turns correlated with pre-literacy skills, as well as myelin density estimates within the left arcuate and superior longitudinal fasciculus. Mediation analyses indicated that the left AF accounted for longitudinal relationships between infant home language measures and 5-year letter identification and letter-sound knowledge, suggesting that the left AF myelination at 2 years may serve as a mechanism by which early language experience supports emergent literacy.
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Affiliation(s)
- Yael Weiss
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Elizabeth Huber
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Naja Ferjan Ramírez
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Linguistics, University of Washington, Seattle, WA, United States
| | - Neva M. Corrigan
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Patricia K. Kuhl
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
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16
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Corrigan NM, Yarnykh VL, Huber E, Zhao TC, Kuhl PK. Brain myelination at 7 months of age predicts later language development. Neuroimage 2022; 263:119641. [PMID: 36170763 PMCID: PMC10038938 DOI: 10.1016/j.neuroimage.2022.119641] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/24/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
Between 6 and 12 months of age there are dramatic changes in infants' processing of language. The neurostructural underpinnings of these changes are virtually unknown. The objectives of this study were to (1) examine changes in brain myelination during this developmental period and (2) examine the relationship between myelination during this period and later language development. Macromolecular proton fraction (MPF) was used as a marker of myelination. Whole-brain MPF maps were obtained with 1.25 mm3 isotropic spatial resolution from typically developing children at 7 and 11 months of age. Effective myelin density was calculated from MPF based on a linear relationship known from the literature. Voxel-based analyses were used to identify longitudinal changes in myelin density and to calculate correlations between myelin density at these ages and later language development. Increases in myelin density were more predominant in white matter than in gray matter. A strong predictive relationship was found between myelin density at 7 months of age, language production at 24 and 30 months of age, and rate of language growth. No relationships were found between myelin density at 11 months, or change in myelin density between 7 and 11 months of age, and later language measures. Our findings suggest that critical changes in brain structure may precede periods of pronounced change in early language skills.
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Affiliation(s)
- Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - T Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
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17
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Kiese-Himmel C. [Early detection of primary developmental language disorders-increasing relevance due to changes in diagnostic criteria?]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2022; 65:909-916. [PMID: 35861864 PMCID: PMC9436846 DOI: 10.1007/s00103-022-03571-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2022] [Indexed: 11/29/2022]
Abstract
Language development disorders (in German: Sprachentwicklungsstörungen, SES) are the most common developmental disorders in childhood. In contrast to "secondary SES," "primary SES" (prevalence about 7%) are not (co-)caused by other developmental disorders or diseases. In the German modification of the International Statistical Classification of Diseases and Related Health Problems (ICD-10-GM-22), primary SES are referred to as "circumscribed developmental disorders of speech and language" (in German: USES; international previously known as Specific Language Impairment SLI), with an intelligence quotient (IQ) < 85 as an exclusion criterion, among other criteria. In ICD-11, primary SES are listed as "developmental language disorders" (DLD).German-speaking speech and language therapists would now like to replace the term "USES" with "DLD" using the diagnostic criteria proposed by the international CATALISE consortium (Criteria and Terminology Applied to Language Impairments Synthesizing the Evidence), in an effort to redefine the disorder. However, according to this conceptualization, only children with an intellectual disability (IQ < 70) would be excluded from the diagnosis. This change in the diagnostic criteria would most likely result in an increase in prevalence of DLDs. This makes the issue of early detection more important than ever. This discussion paper explains that the public health relevance of primary SES is growing and that systematic early detection examinations will play an even more important role. With early diagnosis and treatment, risks in the areas of mental health, behaviour and skill development can be mitigated.Currently, diagnosis (and therapy) are usually carried out relatively late. The way out could lie in the application of neurobiological parameters. However, this requires further studies that examine child cohorts for early indicators in a prospective longitudinal design. The formation of an early detection index from several indicators should also be considered.
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Affiliation(s)
- Christiane Kiese-Himmel
- Phoniatrisch/Pädaudiologische Psychologie, Institut für Medizinische Psychologie und Medizinische Soziologie, Universitätsmedizin Göttingen, Georg-August-Universität Göttingen, Waldweg 35, 37075, Göttingen, Deutschland.
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18
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Vaher K, Galdi P, Blesa Cabez M, Sullivan G, Stoye DQ, Quigley AJ, Thrippleton MJ, Bogaert D, Bastin ME, Cox SR, Boardman JP. General factors of white matter microstructure from DTI and NODDI in the developing brain. Neuroimage 2022; 254:119169. [PMID: 35367650 DOI: 10.1016/j.neuroimage.2022.119169] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 03/15/2022] [Accepted: 03/30/2022] [Indexed: 10/18/2022] Open
Abstract
Preterm birth is closely associated with diffuse white matter dysmaturation inferred from diffusion MRI and neurocognitive impairment in childhood. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are distinct dMRI modalities, yet metrics derived from these two methods share variance across tracts. This raises the hypothesis that dimensionality reduction approaches may provide efficient whole-brain estimates of white matter microstructure that capture (dys)maturational processes. To investigate the optimal model for accurate classification of generalised white matter dysmaturation in preterm infants we assessed variation in DTI and NODDI metrics across 16 major white matter tracts using principal component analysis and structural equation modelling, in 79 term and 141 preterm infants at term equivalent age. We used logistic regression models to evaluate performances of single-metric and multimodality general factor frameworks for efficient classification of preterm infants based on variation in white matter microstructure. Single-metric general factors from DTI and NODDI capture substantial shared variance (41.8-72.5%) across 16 white matter tracts, and two multimodality factors captured 93.9% of variance shared between DTI and NODDI metrics themselves. General factors associate with preterm birth and a single model that includes all seven DTI and NODDI metrics provides the most accurate prediction of microstructural variations associated with preterm birth. This suggests that despite global covariance of dMRI metrics in neonates, each metric represents information about specific (and additive) aspects of the underlying microstructure that differ in preterm compared to term subjects.
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Affiliation(s)
- Kadi Vaher
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Manuel Blesa Cabez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - David Q Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Alan J Quigley
- Department of Paediatric Radiology, Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Debby Bogaert
- Centre for Inflammation Research, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Simon R Cox
- Lothian Birth Cohort Studies group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom.
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19
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De Luca A, Karayumak SC, Leemans A, Rathi Y, Swinnen S, Gooijers J, Clauwaert A, Bahr R, Sandmo SB, Sochen N, Kaufmann D, Muehlmann M, Biessels GJ, Koerte I, Pasternak O. Cross-site harmonization of multi-shell diffusion MRI measures based on rotational invariant spherical harmonics (RISH). Neuroimage 2022; 259:119439. [PMID: 35788044 DOI: 10.1016/j.neuroimage.2022.119439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 06/23/2022] [Accepted: 06/30/2022] [Indexed: 11/25/2022] Open
Abstract
Quantification methods based on the acquisition of diffusion magnetic resonance imaging (dMRI) with multiple diffusion weightings (e.g., multi-shell) are becoming increasingly applied to study the in-vivo brain. Compared to single-shell data for diffusion tensor imaging (DTI), multi-shell data allows to apply more complex models such as diffusion kurtosis imaging (DKI), which attempts to capture both diffusion hindrance and restriction effects, or biophysical models such as NODDI, which attempt to increase specificity by separating biophysical components. Because of the strong dependence of the dMRI signal on the measurement hardware, DKI and NODDI metrics show scanner and site differences, much like other dMRI metrics. These effects limit the implementation of multi-shell approaches in multicenter studies, which are needed to collect large sample sizes for robust analyses. Recently, a post-processing technique based on rotation invariant spherical harmonics (RISH) features was introduced to mitigate cross-scanner differences in DTI metrics. Unlike statistical harmonization methods, which require repeated application to every dMRI metric of choice, RISH harmonization is applied once on the raw data, and can be followed by any analysis. RISH features harmonization has been tested on DTI features but not its generalizability to harmonize multi-shell dMRI. In this work, we investigated whether performing the RISH features harmonization of multi-shell dMRI data removes cross-site differences in DKI and NODDI metrics while retaining longitudinal effects. To this end, 46 subjects underwent a longitudinal (up to 3 time points) two-shell dMRI protocol at 3 imaging sites. DKI and NODDI metrics were derived before and after harmonization and compared both at the whole brain level and at the voxel level. Then, the harmonization effects on cross-sectional and on longitudinal group differences were evaluated. RISH features averaged for each of the 3 sites exhibited prominent between-site differences in the frontal and posterior part of the brain. Statistically significant differences in fractional anisotropy, mean diffusivity and mean kurtosis were observed both at the whole brain and voxel level between all the acquisition sites before harmonization, but not after. The RISH method also proved effective to harmonize NODDI metrics, particularly in white matter. The RISH based harmonization maintained the magnitude and variance of longitudinal changes as compared to the non-harmonized data of all considered metrics. In conclusion, the application of RISH feature based harmonization to multi-shell dMRI data can be used to remove cross-site differences in DKI metrics and NODDI analyses, while retaining inherent relations between longitudinal acquisitions.
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Affiliation(s)
- Alberto De Luca
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands; Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia.
| | | | - Alexander Leemans
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephan Swinnen
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Jolien Gooijers
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Amanda Clauwaert
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Roald Bahr
- Oslo Sports Trauma Research Center, Norwegian School of Sport Sciences, Oslo, Norway
| | - Stian Bahr Sandmo
- Oslo Sports Trauma Research Center, Norwegian School of Sport Sciences, Oslo, Norway
| | - Nir Sochen
- Department of Applied Mathematics, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - David Kaufmann
- Radiology Department, Charite University Hospital, Berlin, Germany
| | - Marc Muehlmann
- Department of Radiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Geert-Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Inga Koerte
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Ludwig-Maximilians-Universität, Munich, Germany
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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20
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Raja R, Na X, Moore A, Otoo R, Glasier CM, Badger TM, Ou X. Associations Between White Matter Microstructures and Cognitive Functioning in 8-Year-Old Children: A Track-Weighted Imaging Study. J Child Neurol 2022; 37:471-490. [PMID: 35254148 PMCID: PMC9149064 DOI: 10.1177/08830738221083487] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE Quantitative tractography using diffusion-weighted magnetic resonance imaging data is widely used in characterizing white matter microstructure throughout childhood, but more studies are still needed to investigate comprehensive brain-behavior relationships between tract-specific white matter measures and multiple cognitive functions in children. METHODS In this study, we analyzed diffusion-weighted MRI data of 71 healthy 8-year-old children utilizing white matter tract-specific quantitative measures derived from diffusion-weighted MRI tractography based on a novel track-weighted imaging approach. Track density imaging, average path length map and 4 track-weighted diffusion tensor imaging measures including: mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for 63 white matter tracts. The track-weighted imaging measures were then correlated with a comprehensive set of neuropsychological test scores in different cognitive domains including intelligence, language, memory, academic skills, and executive functions to identify tract-specific brain-behavior relationships. RESULTS Significant correlations (P < .05, false discovery rate corrected; r = 0.27-0.57) were found in multiple white matter tracts, with a total of 40 correlations identified between various track-weighted imaging measures including average path length map, track-weighted imaging-fractional anisotropy, and neuropsychological test scores and subscales. Specifically, track-weighted imaging measures indicative of better white matter connectivity and/or microstructural development significantly correlated with higher IQ and better language abilities. CONCLUSION Our findings demonstrate the ability of track-weighted imaging measures in establishing associations between white matter and cognitive functioning in healthy children and can serve as a reference for normal brain/cognition relationships in young school-age children and further aid in identifying imaging biomarkers predictive of adverse neurodevelopmental outcomes.
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Affiliation(s)
- Rajikha Raja
- Department of Radiology, University of Arkansas for Medical Sciences
| | - Xiaoxu Na
- Department of Radiology, University of Arkansas for Medical Sciences
| | - Alexandra Moore
- College of Medicine, University of Arkansas for Medical Sciences
| | - Raymond Otoo
- College of Medicine, University of Arkansas for Medical Sciences
| | - Charles M. Glasier
- Department of Radiology, University of Arkansas for Medical Sciences
- Department of Pediatrics, University of Arkansas for Medical Sciences
| | - Thomas M. Badger
- Department of Pediatrics, University of Arkansas for Medical Sciences
- Arkansas Children’s Nutrition Center
| | - Xiawei Ou
- Department of Radiology, University of Arkansas for Medical Sciences
- Department of Pediatrics, University of Arkansas for Medical Sciences
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21
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Gale-Grant O, Fenn-Moltu S, França LGS, Dimitrova R, Christiaens D, Cordero-Grande L, Chew A, Falconer S, Harper N, Price AN, Hutter J, Hughes E, O'Muircheartaigh J, Rutherford M, Counsell SJ, Rueckert D, Nosarti C, Hajnal JV, McAlonan G, Arichi T, Edwards AD, Batalle D. Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies. Hum Brain Mapp 2022; 43:1577-1589. [PMID: 34897872 PMCID: PMC8886657 DOI: 10.1002/hbm.25743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 11/19/2021] [Accepted: 11/30/2021] [Indexed: 11/12/2022] Open
Abstract
Infants born in early term (37-38 weeks gestation) experience slower neurodevelopment than those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain. Here we characterise brain volume and white matter correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome using T2 and diffusion weighted MRI acquired in the neonatal period from a cohort (n = 454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor-based morphometry and tract-based spatial statistics. Neurodevelopment was assessed at age 18 months using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Infants born earlier had higher relative ventricular volume and lower relative brain volume in the deep grey matter, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial, and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Regression models predicting outcome from gestational age at birth were significantly improved after adding neuroimaging features associated with gestational age at birth. This work adds to the body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.
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Affiliation(s)
- Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Lucas G S França
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Daan Christiaens
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Andrew Chew
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Nicholas Harper
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Anthony N Price
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Daniel Rueckert
- Department of Computing, Imperial College London, London, UK.,Department of Medicine and Informatics, Technical University of Munich, Munich, Germany
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,Paediatric Neurosciences, Evelina London Children's Hospital Guy's and St Thomas' NHS Foundation Trust, London, UK.,Department of Bioengineering, Imperial College London, London, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
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22
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Fenchel D, Dimitrova R, Robinson EC, Batalle D, Chew A, Falconer S, Kyriakopoulou V, Nosarti C, Hutter J, Christiaens D, Pietsch M, Brandon J, Hughes EJ, Allsop J, O'Keeffe C, Price AN, Cordero-Grande L, Schuh A, Makropoulos A, Passerat-Palmbach J, Bozek J, Rueckert D, Hajnal JV, McAlonan G, Edwards AD, O'Muircheartaigh J. Neonatal multi-modal cortical profiles predict 18-month developmental outcomes. Dev Cogn Neurosci 2022; 54:101103. [PMID: 35364447 PMCID: PMC8971851 DOI: 10.1016/j.dcn.2022.101103] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 02/08/2022] [Accepted: 03/23/2022] [Indexed: 12/16/2022] Open
Abstract
Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills.
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Affiliation(s)
- Daphna Fenchel
- MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK; Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK
| | - Ralica Dimitrova
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Emma C Robinson
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK
| | - Dafnis Batalle
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK; Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Andrew Chew
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Shona Falconer
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK
| | - Jana Hutter
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Daan Christiaens
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK; Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Maximilian Pietsch
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Jakki Brandon
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Emer J Hughes
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Joanna Allsop
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Camilla O'Keeffe
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Anthony N Price
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK; Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, Spain
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Antonios Makropoulos
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | | | - Jelena Bozek
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK; Institute für Artificial Intelligence and Informatics in Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joseph V Hajnal
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Grainne McAlonan
- MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK; Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK; South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| | - A David Edwards
- MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK; Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK
| | - Jonathan O'Muircheartaigh
- MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK; Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK; Centre for the Developing Brain, Department of Perinatal Imaging & Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EH UK.
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23
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Short SJ, Jang DK, Steiner RJ, Stephens RL, Girault JB, Styner M, Gilmore JH. Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations. Front Neurosci 2022; 16:806268. [PMID: 35401073 PMCID: PMC8985548 DOI: 10.3389/fnins.2022.806268] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 01/27/2022] [Indexed: 01/14/2023] Open
Abstract
Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available.
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Affiliation(s)
- Sarah J. Short
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Dae Kun Jang
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
| | - Rachel J. Steiner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rebecca L. Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jessica B. Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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24
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Korom M, Camacho MC, Filippi CA, Licandro R, Moore LA, Dufford A, Zöllei L, Graham AM, Spann M, Howell B, Shultz S, Scheinost D. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Dev Cogn Neurosci 2021; 53:101055. [PMID: 34974250 PMCID: PMC8733260 DOI: 10.1016/j.dcn.2021.101055] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/28/2021] [Accepted: 12/26/2021] [Indexed: 01/07/2023] Open
Abstract
The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging. The field of infant MRI is young with evolving standards. We address 20 questions that researchers commonly receive reviewers. These come from research ethics boards, grant, and manuscript reviewers. This article reflects the cumulative knowledge of experts in the FIT’NG community.
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Affiliation(s)
- Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA.
| | - M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University School of Medicine, St. Louis, MO, USA.
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Roxane Licandro
- Institute of Visual Computing and Human-Centered Technology, Computer Vision Lab, TU Wien, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research, Medical University of Vienna, Vienna, Austria
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Alexander Dufford
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Department of Human Development and Family Science, Virginia Polytechnic Institute and State University, Roanoke, VA, USA
| | | | - Sarah Shultz
- Division of Autism & Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
| | - Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
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25
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Yrjölä P, Stjerna S, Palva JM, Vanhatalo S, Tokariev A. Phase-Based Cortical Synchrony Is Affected by Prematurity. Cereb Cortex 2021; 32:2265-2276. [PMID: 34668522 PMCID: PMC9113310 DOI: 10.1093/cercor/bhab357] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/26/2021] [Accepted: 08/30/2021] [Indexed: 11/22/2022] Open
Abstract
Inter-areal synchronization by phase–phase correlations (PPCs) of cortical oscillations mediates many higher neurocognitive functions, which are often affected by prematurity, a globally prominent neurodevelopmental risk factor. Here, we used electroencephalography to examine brain-wide cortical PPC networks at term-equivalent age, comparing human infants after early prematurity to a cohort of healthy controls. We found that prematurity affected these networks in a sleep state-specific manner, and the differences between groups were also frequency-selective, involving brain-wide connections. The strength of synchronization in these networks was predictive of clinical outcomes in the preterm infants. These findings show that prematurity affects PPC networks in a clinically significant manner, suggesting early functional biomarkers of later neurodevelopmental compromise that may be used in clinical or translational studies after early neonatal adversity.
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Affiliation(s)
- Pauliina Yrjölä
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, 00076 AALTO, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
| | - Susanna Stjerna
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland.,Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital and University of Helsinki, PL 340, 00029 HUS, Finland
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, 00076 AALTO, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland.,Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
| | - Anton Tokariev
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
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26
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Nutritional Intake, White Matter Integrity, and Neurodevelopment in Extremely Preterm Born Infants. Nutrients 2021; 13:nu13103409. [PMID: 34684410 PMCID: PMC8539908 DOI: 10.3390/nu13103409] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 09/20/2021] [Accepted: 09/22/2021] [Indexed: 02/05/2023] Open
Abstract
Background: Determining optimal nutritional regimens in extremely preterm infants remains challenging. This study aimed to evaluate the effect of a new nutritional regimen and individual macronutrient intake on white matter integrity and neurodevelopmental outcome. Methods: Two retrospective cohorts of extremely preterm infants (gestational age < 28 weeks) were included. Cohort B (n = 79) received a new nutritional regimen, with more rapidly increased, higher protein intake compared to cohort A (n = 99). Individual protein, lipid, and caloric intakes were calculated for the first 28 postnatal days. Diffusion tensor imaging was performed at term-equivalent age, and cognitive and motor development were evaluated at 2 years corrected age (CA) (Bayley-III-NL) and 5.9 years chronological age (WPPSI-III-NL, MABC-2-NL). Results: Compared to cohort A, infants in cohort B had significantly higher protein intake (3.4 g/kg/day vs. 2.7 g/kg/day) and higher fractional anisotropy (FA) in several white matter tracts but lower motor scores at 2 years CA (mean (SD) 103 (12) vs. 109 (12)). Higher protein intake was associated with higher FA and lower motor scores at 2 years CA (B = −6.7, p = 0.001). However, motor scores at 2 years CA were still within the normal range and differences were not sustained at 5.9 years. There were no significant associations with lipid or caloric intake. Conclusion: In extremely preterm born infants, postnatal protein intake seems important for white matter development but does not necessarily improve long-term cognitive and motor development.
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27
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Nolvi S, Tuulari JJ, Lavonius T, Scheinin NM, Lehtola SJ, Lavonius M, Merisaari H, Saunavaara J, Korja R, Kataja EL, Pelto J, Parkkola R, Karlsson L, Karlsson H. Newborn white matter microstructure moderates the association between maternal postpartum depressive symptoms and infant negative reactivity. Soc Cogn Affect Neurosci 2021; 15:649-660. [PMID: 32577747 PMCID: PMC7393309 DOI: 10.1093/scan/nsaa081] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/29/2020] [Accepted: 06/08/2020] [Indexed: 12/20/2022] Open
Abstract
Maternal postpartum depression is a prominent risk factor for aberrant child socioemotional development, but there is little understanding about the neural phenotypes that underlie infant sensitivity to maternal depression. We examined whether newborn white matter fractional anisotropy (FA), a measure of white matter maturity, moderates the association between maternal postpartum depressive symptoms and infant negative reactivity at 6 months. Participants were 80 mother–infant dyads participating in a prospective population-based cohort, and included families whose newborns underwent a magnetic resonance/diffusion tensor imaging scan at 2–5 weeks of age and whose mothers reported their own depressive symptoms at 3 and 6 months postpartum and infant negative emotional reactivity at 6 months. The whole-brain FA moderated the association between maternal depressive symptoms and mother-reported infant negative reactivity at 6 months after adjusting for the covariates. Maternal depressive symptoms were positively related to infant negative reactivity among infants with high or average FA in the whole brain and in corpus callosum and cingulum, but not among those with low FA. The link between maternal depressive symptoms and infant negative reactivity was moderated by newborn FA. The variation in white matter microstructure might play a role in child susceptibility to parental distress.
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Affiliation(s)
- Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Medical Psychology, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Psychology and Speech-Language Pathology, University of Turku, Turku, Finland.,Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Department of Psychiatry, University of Oxford, Oxford, UK
| | - Tuomas Lavonius
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Noora M Scheinin
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland
| | - Satu J Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Maria Lavonius
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Future Technologies, University of Turku, Turku, Finland.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychology and Speech-Language Pathology, University of Turku, Turku, Finland
| | - Eeva-Leena Kataja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychology and Speech-Language Pathology, University of Turku, Turku, Finland
| | - Juho Pelto
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Radiology, Turku University Hospital and University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Child Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
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28
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Girault JB, Cornea E, Goldman BD, Jha SC, Murphy VA, Li G, Wang L, Shen D, Knickmeyer RC, Styner M, Gilmore JH. Cortical Structure and Cognition in Infants and Toddlers. Cereb Cortex 2021; 30:786-800. [PMID: 31365070 DOI: 10.1093/cercor/bhz126] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 05/21/2019] [Accepted: 05/22/2019] [Indexed: 12/21/2022] Open
Abstract
Cortical structure has been consistently related to cognitive abilities in children and adults, yet we know little about how the cortex develops to support emergent cognition in infancy and toddlerhood when cortical thickness (CT) and surface area (SA) are maturing rapidly. In this report, we assessed how regional and global measures of CT and SA in a sample (N = 487) of healthy neonates, 1-year-olds, and 2-year-olds related to motor, language, visual reception, and general cognitive ability. We report novel findings that thicker cortices at ages 1 and 2 and larger SA at birth, age 1, and age 2 confer a cognitive advantage in infancy and toddlerhood. While several expected brain-cognition relationships were observed, overlapping cortical regions were also implicated across cognitive domains, suggesting that infancy marks a period of plasticity and refinement in cortical structure to support burgeoning motor, language, and cognitive abilities. CT may be a particularly important morphological indicator of ability, but its impact on cognition is relatively weak when compared with gestational age and maternal education. Findings suggest that prenatal and early postnatal cortical developments are important for cognition in infants and toddlers but should be considered in relation to other child and demographic factors.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Barbara D Goldman
- Department of Psychology & Neuroscience and FPG Child Development Institute, University of North Carolina, Chapel Hill, NC, USA
| | - Shaili C Jha
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Veronica A Murphy
- Neuroscience Curriculum, University of North Carolina, Chapel Hill, NC, USA
| | - Gang Li
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Li Wang
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dinggang Shen
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rebecca C Knickmeyer
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.,Department of Pediatrics and Human Development, Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
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29
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Langworthy BW, Stephens RL, Gilmore JH, Fine JP. Canonical correlation analysis for elliptical copulas. J MULTIVARIATE ANAL 2021; 183:104715. [PMID: 33518826 PMCID: PMC7839949 DOI: 10.1016/j.jmva.2020.104715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Canonical correlation analysis (CCA) is a common method used to estimate the associations between two different sets of variables by maximizing the Pearson correlation between linear combinations of the two sets of variables. We propose a version of CCA for transelliptical distributions with an elliptical copula using pairwise Kendall's tau to estimate a latent scatter matrix. Because Kendall's tau relies only on the ranks of the data this method does not make any assumptions about the marginal distributions of the variables, and is valid when moments do not exist. We establish consistency and asymptotic normality for canonical directions and correlations estimated using Kendall's tau. Simulations indicate that this estimator outperforms standard CCA for data generated from heavy tailed elliptical distributions. Our method also identifies more meaningful relationships when the marginal distributions are skewed. We also propose a method for testing for non-zero canonical correlations using bootstrap methods. This testing procedure does not require any assumptions on the joint distribution of the variables and works for all elliptical copulas. This is in contrast to permutation tests which are only valid when data are generated from a distribution with a Gaussian copula. This method's practical utility is shown in an analysis of the association between radial diffusivity in white matter tracts and cognitive tests scores for six-year-old children from the Early Brain Development Study at UNC-Chapel Hill. An R package implementing this method is available at github.com/blangworthy/transCCA.
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Affiliation(s)
- Benjamin W. Langworthy
- Department of Biostatistics, University of North Carolina - Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenberg Hall, Chapel Hill, NC 27599
| | - Rebecca L. Stephens
- Department of Psychiatry, University of North Carolina - Chapel Hill, 101 Manning Dr 1, Chapel Hill, NC 27514
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina - Chapel Hill, 101 Manning Dr 1, Chapel Hill, NC 27514
| | - Jason P. Fine
- Department of Biostatistics, University of North Carolina - Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenberg Hall, Chapel Hill, NC 27599
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30
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Cai L, Okada E, Minagawa Y, Kawaguchi H. Correlating functional near-infrared spectroscopy with underlying cortical regions of 0-, 1-, and 2-year-olds using theoretical light propagation analysis. NEUROPHOTONICS 2021; 8:025009. [PMID: 34079846 PMCID: PMC8166262 DOI: 10.1117/1.nph.8.2.025009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 05/18/2021] [Indexed: 05/03/2023]
Abstract
Significance: The establishment of a light propagation analysis-based scalp-cortex correlation (SCC) between the scalp location of the source-detector (SD) pair and brain regions is essential for measuring functional brain development in the first 2 years of life using functional near-infrared spectroscopy (fNIRS). Aim: We aimed to reveal the optics-based SCC of 0-, 1-, and 2-year-olds (yo) and the suitable SD distance for this age period. Approach: Light propagation analyses using age-appropriate head models were conducted on SD pairs at 10-10 fiducial points on the scalp to obtain optics-based SCC and its metrics: the number of corresponding brain regions ( N C B R ), selectivity and sensitivity of the most likely corresponding brain region (MLCBR), and consistency of the MLCBR across developmental ages. Moreover, we assessed the suitable SD distances for 0-, 1-, and 2-yo by simultaneously considering the selectivity and sensitivity of the MLCBR. Results: Age-related changes in the SCC metrics were observed. For instance, the N C B R of 0-yo was larger than that of 1- and 2-yo. Conversely, the selectivity of 0-yo was lower than that of 1- and 2-yo. The sensitivity of 1-yo was higher than that of 0-yo at 15- to 30-mm SD distances and higher than that of 2-yo at 10-mm SD distance. Notably, the MLCBR of the fiducial points around the longitudinal fissure was inconsistent across age groups. An SD distance between 15 and 25 mm was found to be appropriate for satisfying both sensitivity and selectivity requirements. In addition, this work provides reference tables of optics-based SCC for 0-, 1-, and 2-yo. Conclusions: Optics-based SCC will be informative in designing and explaining child developmental studies using fNIRS. The suitable SD distances were between 15 and 25 mm for the first 2 years of life.
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Affiliation(s)
- Lin Cai
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
| | - Eiji Okada
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
| | | | - Hiroshi Kawaguchi
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
- National Institute of Advanced Industrial Science and Technology, Human Informatics and Interaction Research Institute, Tsukuba, Japan
- Address all correspondence to Hiroshi Kawaguchi,
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31
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Aggarwal N, Moody JF, Dean DC, Tromp DPM, Kecskemeti SR, Oler JA, Alexander AL, Kalin NH. Spatiotemporal dynamics of nonhuman primate white matter development during the first year of life. Neuroimage 2021; 231:117825. [PMID: 33549752 DOI: 10.1016/j.neuroimage.2021.117825] [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: 09/25/2020] [Revised: 01/22/2021] [Accepted: 01/27/2021] [Indexed: 11/15/2022] Open
Abstract
White matter (WM) development early in life is a critical component of brain development that facilitates the coordinated function of neuronal pathways. Additionally, alterations in WM have been implicated in various neurodevelopmental disorders, including psychiatric disorders. Because of the need to understand WM development in the weeks immediately following birth, we characterized changes in WM microstructure throughout the postnatal macaque brain during the first year of life. This is a period in primates during which genetic, developmental, and environmental factors may have long-lasting impacts on WM microstructure. Studies in nonhuman primates (NHPs) are particularly valuable as a model for understanding human brain development because of their evolutionary relatedness to humans. Here, 34 rhesus monkeys (23 females, 11 males) were imaged longitudinally at 3, 7, 13, 25, and 53 weeks of age with T1-weighted (MPnRAGE) and diffusion tensor imaging (DTI). With linear mixed-effects (LME) modeling, we demonstrated robust logarithmic growth in FA, MD, and RD trajectories extracted from 18 WM tracts across the brain. Estimated rate of change curves for FA, MD, and RD exhibited an initial 10-week period of exceedingly rapid WM development, followed by a precipitous decline in growth rates. K-means clustering of raw DTI trajectories and rank ordering of LME model parameters revealed distinct posterior-to-anterior and medial-to-lateral gradients in WM maturation. Finally, we found that individual differences in WM microstructure assessed at 3 weeks of age were significantly related to those at 1 year of age. This study provides a quantitative characterization of very early WM growth in NHPs and lays the foundation for future work focused on the impact of alterations in early WM developmental trajectories in relation to human psychopathology.
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Affiliation(s)
- Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States.
| | - Jason F Moody
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States
| | - Douglas C Dean
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Department of Pediatrics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Steve R Kecskemeti
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Andy L Alexander
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States; Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
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32
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Raper J, Chahroudi A. Clinical and Preclinical Evidence for Adverse Neurodevelopment after Postnatal Zika Virus Infection. Trop Med Infect Dis 2021; 6:tropicalmed6010010. [PMID: 33445671 PMCID: PMC7838975 DOI: 10.3390/tropicalmed6010010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 01/04/2021] [Indexed: 02/07/2023] Open
Abstract
Although the Zika virus (ZIKV) typically causes mild or no symptoms in adults, during the 2015−2016 outbreak, ZIKV infection in pregnancy resulted in a spectrum of diseases in infants, including birth defects and neurodevelopmental disorders identified in childhood. While intense clinical and basic science research has focused on the neurodevelopmental outcomes of prenatal ZIKV infection, less is known about the consequences of infection during early life. Considering the neurotropism of ZIKV and the rapidly-developing postnatal brain, it is important to understand how infection during infancy may disrupt neurodevelopment. This paper reviews the current knowledge regarding early postnatal ZIKV infection. Emerging clinical evidence supports the hypothesis that ZIKV infection during infancy can result in negative neurologic consequences. However, clinical data regarding postnatal ZIKV infection in children are limited; as such, animal models play an important role in understanding the potential complications of ZIKV infection related to the vulnerable developing brain. Preclinical data provide insight into the potential behavioral, cognitive, and motor domains that clinical studies should examine in pediatric populations exposed to ZIKV during infancy.
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Affiliation(s)
- Jessica Raper
- Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, USA;
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Ann Chahroudi
- Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, USA;
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Center for Childhood Infections and Vaccines of Children’s Healthcare of Atlanta and Emory University, Atlanta, GA 30322, USA
- Correspondence:
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33
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Stephens RL, Langworthy BW, Short SJ, Girault JB, Styner MA, Gilmore JH. White Matter Development from Birth to 6 Years of Age: A Longitudinal Study. Cereb Cortex 2020; 30:6152-6168. [PMID: 32591808 DOI: 10.1093/cercor/bhaa170] [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] [Received: 07/29/2019] [Revised: 04/30/2020] [Accepted: 05/22/2020] [Indexed: 11/13/2022] Open
Abstract
Human white matter development in the first years of life is rapid, setting the foundation for later development. Microstructural properties of white matter are linked to many behavioral and psychiatric outcomes; however, little is known about when in development individual differences in white matter microstructure are established. The aim of the current study is to characterize longitudinal development of white matter microstructure from birth through 6 years to determine when in development individual differences are established. Two hundred and twenty-four children underwent diffusion-weighted imaging after birth and at 1, 2, 4, and 6 years. Diffusion tensor imaging data were computed for 20 white matter tracts (9 left-right corresponding tracts and 2 commissural tracts), with tract-based measures of fractional anisotropy and axial and radial diffusivity. Microstructural maturation between birth and 1 year are much greater than subsequent changes. Further, by 1 year, individual differences in tract average values are consistently predictive of the respective 6-year values, explaining, on average, 40% of the variance in 6-year microstructure. Results provide further evidence of the importance of the first year of life with regard to white matter development, with potential implications for informing early intervention efforts that target specific sensitive periods.
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Affiliation(s)
- Rebecca L Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Benjamin W Langworthy
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Sarah J Short
- Department of Educational Psychology, Center for Healthy Minds, University of Wisconsin, Madison, Madison, WI 53703, USA
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.,Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Gale-Grant O, Christiaens D, Cordero-Grande L, Chew A, Falconer S, Makropoulos A, Harper N, Price AN, Hutter J, Hughes E, Victor S, Counsell SJ, Rueckert D, Hajnal JV, Edwards AD, O'Muircheartaigh J, Batalle D. Parental age effects on neonatal white matter development. NEUROIMAGE-CLINICAL 2020; 27:102283. [PMID: 32526683 PMCID: PMC7284122 DOI: 10.1016/j.nicl.2020.102283] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 04/28/2020] [Accepted: 05/10/2020] [Indexed: 12/29/2022]
Abstract
Advanced paternal age is associated with a range of later negative outcomes. It is not known if these negative outcomes are due to genetics or environment. We use neonatal diffusion MRI to demonstrate paternal age effect on white matter. The babies of older fathers had reduced fractional anisotropy in multiple areas. These changes correlated with cognitive outcome at 18 months.
Objective Advanced paternal age is associated with poor offspring developmental outcome. Though an increase in paternal age-related germline mutations may affect offspring white matter development, outcome differences could also be due to psychosocial factors. Here we investigate possible cerebral changes prior to strong environmental influences using brain MRI in a cohort of healthy term-born neonates. Methods We used structural and diffusion MRI images acquired soon after birth from a cohort (n = 275) of healthy term-born neonates. Images were analysed using a customised tract based spatial statistics (TBSS) processing pipeline. Neurodevelopmental assessment using the Bayley-III scales was offered to all participants at age 18 months. For statistical analysis neonates were compared in two groups, representing the upper quartile (paternal age ≥38 years) and lower three quartiles. The same method was used to assess associations with maternal age. Results In infants with older fathers (≥38 years), fractional anisotropy, a marker of white matter organisation, was significantly reduced in three early maturing anatomical locations (the corticospinal tract, the corpus callosum, and the optic radiation). Fractional anisotropy in these locations correlated positively with Bayley-III cognitive composite score at 18 months in the advanced paternal age group. A small but significant reduction in total brain volume was also observed in in the infants of older fathers. No significant associations were found between advanced maternal age and neonatal imaging. Conclusions The epidemiological association between advanced paternal age and offspring outcome is extremely robust. We have for the first time demonstrated a neuroimaging phenotype of advanced paternal age before sustained parental interaction that correlates with later outcome.
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Affiliation(s)
- Oliver Gale-Grant
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
| | - Daan Christiaens
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Andrew Chew
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | | | - Nicholas Harper
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Suresh Victor
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - Daniel Rueckert
- Department of Computing, Imperial College London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, United Kingdom
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
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35
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Association between diffusivity measures and language and cognitive-control abilities from early toddler’s age to childhood. Brain Struct Funct 2020; 225:1103-1122. [DOI: 10.1007/s00429-020-02062-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 03/20/2020] [Indexed: 12/20/2022]
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Sket GM, Overfeld J, Styner M, Gilmore JH, Entringer S, Wadhwa PD, Rasmussen JM, Buss C. Neonatal White Matter Maturation Is Associated With Infant Language Development. Front Hum Neurosci 2019; 13:434. [PMID: 31920593 PMCID: PMC6927985 DOI: 10.3389/fnhum.2019.00434] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 11/25/2019] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND While neonates have no sophisticated language skills, the neural basis for acquiring this function is assumed to already be present at birth. Receptive language is measurable by 6 months of age and meaningful speech production by 10-18 months of age. Fiber tracts supporting language processing include the corpus callosum (CC), which plays a key role in the hemispheric lateralization of language; the left arcuate fasciculus (AF), which is associated with syntactic processing; and the right AF, which plays a role in prosody and semantics. We examined if neonatal maturation of these fiber tracts is associated with receptive language development at 12 months of age. METHODS Diffusion-weighted imaging (DWI) was performed in 86 infants at 26.6 ± 12.2 days post-birth. Receptive language was assessed via the MacArthur-Bates Communicative Development Inventory at 12 months of age. Tract-based fractional anisotropy (FA) was determined using the NA-MIC atlas-based fiber analysis toolkit. Associations between neonatal regional FA, adjusted for gestational age at birth and age at scan, and language development at 12 months of age were tested using ANOVA models. RESULTS After multiple comparisons correction, higher neonatal FA was positively associated with receptive language at 12 months of age within the genu (p < 0.001), rostrum (p < 0.001), and tapetum (p < 0.001) of the CC and the left fronto-parietal AF (p = 0.008). No significant clusters were found in the right AF. CONCLUSION Microstructural development of the CC and the AF in the newborn is associated with receptive language at 12 months of age, demonstrating that interindividual variation in white matter microstructure is relevant for later language development, and indicating that the neural foundation for language processing is laid well ahead of the majority of language acquisition. This suggests that some origins of impaired language development may lie in the intrauterine and potentially neonatal period of life. Understanding how interindividual differences in neonatal brain maturity relate to the acquisition of function, particularly during early development when the brain is in an unparalleled window of plasticity, is key to identifying opportunities for harnessing neuroplasticity in health and disease.
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Affiliation(s)
- Georgina M. Sket
- Department of Medical Psychology, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Judith Overfeld
- Department of Medical Psychology, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sonja Entringer
- Department of Medical Psychology, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Development, Health, and Disease Research Program, University of California, Irvine, Orange, CA, United States
| | - Pathik D. Wadhwa
- Development, Health, and Disease Research Program, University of California, Irvine, Orange, CA, United States
| | - Jerod M. Rasmussen
- Development, Health, and Disease Research Program, University of California, Irvine, Orange, CA, United States
| | - Claudia Buss
- Department of Medical Psychology, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Development, Health, and Disease Research Program, University of California, Irvine, Orange, CA, United States
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37
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Swanson MR, Hazlett HC. White matter as a monitoring biomarker for neurodevelopmental disorder intervention studies. J Neurodev Disord 2019; 11:33. [PMID: 31839003 PMCID: PMC6912948 DOI: 10.1186/s11689-019-9295-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 11/11/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Early intervention is a valuable tool to support the development of toddlers with neurodevelopmental disorders. With recent research advances in early identification that allow for pre-symptomatic detection of autism in infancy, scientists are looking forward to intervention during infancy. These advances may be supported by the identification of biologically based treatment and outcome measures that are sensitive and dimensional. The purpose of this review is to evaluate white matter neurodevelopment as a monitoring biomarker for early treatment of neurodevelopmental disorders. Fragile X syndrome (FXS) and autism spectrum disorder (ASD) as used as exemplars. White matter has unique neurobiology, including a prolonged period of dynamic development. This developmental pattern may make white matter especially responsive to treatment. White matter develops aberrantly in children with ASD and FXS. Histologic studies in rodents have provided targets for FXS pharmacological intervention. However, pharmaceutical clinical trials in humans failed to garner positive clinical results. In this article, we argue that the use of neurobiological monitoring biomarkers may overcome some of these limitations, as they are objective, not susceptible to placebo effects, and are dimensional in nature. SHORT CONCLUSION As the field moves towards earlier detection and early intervention for neurodevelopmental disorders, we encourage scientists to consider the advantages of using neurobiological features as monitoring biomarkers.
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Affiliation(s)
- Meghan R Swanson
- School of Behavioral and Brain Sciences, University of Texas at Dallas, GR41, 800 W. Campbell Road, Richardson, TX, 75080-3021, USA.
| | - Heather C Hazlett
- Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA
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Girault JB, Piven J. The Neurodevelopment of Autism from Infancy Through Toddlerhood. Neuroimaging Clin N Am 2019; 30:97-114. [PMID: 31759576 DOI: 10.1016/j.nic.2019.09.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Autism spectrum disorder (ASD) emerges during early childhood and is marked by a relatively narrow window in which infants transition from exhibiting normative behavioral profiles to displaying the defining features of the ASD phenotype in toddlerhood. Prospective brain imaging studies in infants at high familial risk for autism have revealed important insights into the neurobiology and developmental unfolding of ASD. In this article, we review neuroimaging studies of brain development in ASD from birth through toddlerhood, relate these findings to candidate neurobiological mechanisms, and discuss implications for future research and translation to clinical practice.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA.
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA
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39
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Dai X, Hadjipantelis P, Wang J, Deoni SCL, Müller H. Longitudinal associations between white matter maturation and cognitive development across early childhood. Hum Brain Mapp 2019; 40:4130-4145. [PMID: 31187920 PMCID: PMC6771612 DOI: 10.1002/hbm.24690] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 05/02/2019] [Accepted: 05/27/2019] [Indexed: 12/11/2022] Open
Abstract
From birth to 5 years of age, brain structure matures and evolves alongside emerging cognitive and behavioral abilities. In relating concurrent cognitive functioning and measures of brain structure, a major challenge that has impeded prior investigation of their time-dynamic relationships is the sparse and irregular nature of most longitudinal neuroimaging data. We demonstrate how this problem can be addressed by applying functional concurrent regression models (FCRMs) to longitudinal cognitive and neuroimaging data. The application of FCRM in neuroimaging is illustrated with longitudinal neuroimaging and cognitive data acquired from a large cohort (n = 210) of healthy children, 2-48 months of age. Quantifying white matter myelination by using myelin water fraction (MWF) as imaging metric derived from MRI scans, application of this methodology reveals an early period (200-500 days) during which whole brain and regional white matter structure, as quantified by MWF, is positively associated with cognitive ability, while we found no such association for whole brain white matter volume. Adjusting for baseline covariates including socioeconomic status as measured by maternal education (SES-ME), infant feeding practice, gender, and birth weight further reveals an increasing association between SES-ME and cognitive development with child age. These results shed new light on the emerging patterns of brain and cognitive development, indicating that FCRM provides a useful tool for investigating these evolving relationships.
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Affiliation(s)
- Xiongtao Dai
- Department of StatisticsIowa State UniversityAmesIowa
| | | | - Jane‐Ling Wang
- Department of StatisticsUniversity of California DavisDavisCalifornia
| | - Sean C. L. Deoni
- Advanced Baby Imaging LabBrown University School of EngineeringProvidenceRhode Island
- Children's Hospital Imaging of Learning & Development Lab, Department of RadiologyUniversity of Colorado School of Medicine, Anschutz Medical CampusAuroraColorado
| | - Hans‐Georg Müller
- Department of StatisticsUniversity of California DavisDavisCalifornia
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40
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Ahn SJ, Cornea E, Murphy V, Styner M, Jarskog LF, Gilmore JH. White matter development in infants at risk for schizophrenia. Schizophr Res 2019; 210:107-114. [PMID: 31182322 PMCID: PMC6689450 DOI: 10.1016/j.schres.2019.05.039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 05/23/2019] [Accepted: 05/26/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Schizophrenia is considered a neurodevelopmental disorder with a pathophysiology that likely begins long before the onset of clinical symptoms. White matter abnormalities have been observed in schizophrenia and we hypothesized that the first 2 years of life is a period in which white matter abnormalities associated with schizophrenia risk may emerge. METHODS 38 infants at high risk for schizophrenia and 202 healthy controls underwent diffusion tensor MRIs after birth and at 1 and 2 years of age. Quantitative tractography was used to determine diffusion properties (fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD)) of 18 white matter tracts and a general linear model was used to analyze group differences at each age. RESULTS Adjusting gestational age at birth, postnatal age at MRI, gender, MRI scanner type, and maternal education, neonates at high risk had significantly lower FA (p = 0.02) and AD (p = 0.03) in the superior segment of the left cingulate, and higher RD in the hippocampal segment of the left cingulate (p = 0.04). High risk one year olds had significantly lower FA (p < 0.01) and AD (p = 0.02) in the hippocampal segment of the left cingulate. High risk two year olds had significantly lower FA in the left prefrontal cortico-thalamic tract (p = 0.04) and higher RD in the right uncinate fasciculus (p = 0.04). None of the tract differences remained significant after correction for multiple comparisons. CONCLUSIONS There is evidence of abnormal white matter development in young children at risk for schizophrenia, especially in the hippocampal segment of left cingulum. These results support the neurodevelopmental theory of schizophrenia and indicate that impaired white matter may be present in early childhood.
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Affiliation(s)
- Sung Jun Ahn
- Department of Radiology, Yonsei University College of Medicine, Seoul 06273, Korea
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599-7160, USA
| | - Veronica Murphy
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599-7160, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599-7160, USA,Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - L. Fredrik Jarskog
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599-7160, USA
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, 27599-7160, USA
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Girault JB, Munsell BC, Puechmaille D, Goldman BD, Prieto JC, Styner M, Gilmore JH. White matter connectomes at birth accurately predict cognitive abilities at age 2. Neuroimage 2019; 192:145-155. [PMID: 30825656 DOI: 10.1016/j.neuroimage.2019.02.060] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 02/18/2019] [Accepted: 02/22/2019] [Indexed: 12/14/2022] Open
Abstract
Cognitive ability is an important predictor of mental health outcomes that is influenced by neurodevelopment. Evidence suggests that the foundational wiring of the human brain is in place by birth, and that the white matter (WM) connectome supports developing brain function. It is unknown, however, how the WM connectome at birth supports emergent cognition. In this study, a deep learning model was trained using cross-validation to classify full-term infants (n = 75) as scoring above or below the median at age 2 using WM connectomes generated from diffusion weighted magnetic resonance images at birth. Results from this model were used to predict individual cognitive scores. We additionally identified WM connections important for classification. The model was also evaluated in a separate set of preterm infants (n = 37) scanned at term-age equivalent. Findings revealed that WM connectomes at birth predicted 2-year cognitive score group with high accuracy in both full-term (89.5%) and preterm (83.8%) infants. Scores predicted by the model were strongly correlated with actual scores (r = 0.98 for full-term and r = 0.96 for preterm). Connections within the frontal lobe, and between the frontal lobe and other brain areas were found to be important for classification. This work suggests that WM connectomes at birth can accurately predict a child's 2-year cognitive group and individual score in full-term and preterm infants. The WM connectome at birth appears to be a useful neuroimaging biomarker of subsequent cognitive development that deserves further study.
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Affiliation(s)
- Jessica B Girault
- Department of Psychiatry, UNC Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Brent C Munsell
- Department of Computer Science, College of Charleston, Charleston, SC, 29424, USA
| | | | - Barbara D Goldman
- Department of Psychology & Neuroscience, UNC Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Juan C Prieto
- Department of Psychiatry, UNC Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Martin Styner
- Department of Psychiatry, UNC Chapel Hill, Chapel Hill, NC, 27599, USA
| | - John H Gilmore
- Department of Psychiatry, UNC Chapel Hill, Chapel Hill, NC, 27599, USA.
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42
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Girault JB, Cornea E, Goldman BD, Knickmeyer RC, Styner M, Gilmore JH. White matter microstructural development and cognitive ability in the first 2 years of life. Hum Brain Mapp 2018; 40:1195-1210. [PMID: 30353962 DOI: 10.1002/hbm.24439] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 09/27/2018] [Accepted: 10/12/2018] [Indexed: 12/13/2022] Open
Abstract
White matter (WM) integrity has been related to cognitive ability in adults and children, but it remains largely unknown how WM maturation in early life supports emergent cognition. The associations between tract-based measures of fractional anisotropy (FA) and axial and radial diffusivity (AD, RD) shortly after birth, at age 1, and at age 2 and cognitive measures at 1 and 2 years were investigated in 447 healthy infants. We found that generally higher FA and lower AD and RD across many WM tracts in the first year of life were associated with better performance on measures of general cognitive ability, motor, language, and visual reception skills at ages 1 and 2, suggesting an important role for the overall organization, myelination, and microstructural properties of fiber pathways in emergent cognition. RD in particular was consistently related to ability, and protracted development of RD from ages 1 to 2 years in several tracts was associated with higher cognitive scores and better language performance, suggesting prolonged plasticity may confer cognitive benefits during the second year of life. However, we also found that cognition at age 2 was weakly associated with WM properties across infancy in comparison to child and demographic factors including gestational age and maternal education. Our findings suggest that early postnatal WM integrity across the brain is important for infant cognition, though its role in cognitive development should be considered alongside child and demographic factors.
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Affiliation(s)
- Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Barbara D Goldman
- Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Rebecca C Knickmeyer
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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