Alterations in neural connectivity in preterm children at school age

Converging data suggest recovery from injury in the preterm brain. We used functional magnetic resonance imaging (fMRI) to test the hypothesis that cerebral connectivity involving Wernicke's area and other important cortical language regions would differ between preterm (PT) and term (T) control school age children during performance of an auditory language task. Fifty-four PT children (600-1250 g birth weight) and 24 T controls were evaluated using an fMRI passive language task and neurodevelopmental assessments including: the Wechsler Intelligence Scale for Children - III (WISC-III), the Peabody Individual Achievement Test - Revised (PIAT-R) and the Peabody Picture Vocabulary Test - Revised (PPVT-R) at 8 years of age. Neural activity was assessed for language processing and the data were evaluated for connectivity and correlations to cognitive outcomes. We found that PT subjects scored significantly lower on all components of the WISC-III (p<0.009), the PIAT-R Reading Comprehension test (p=0.013), and the PPVT-R (p=0.001) compared to term subjects. Connectivity analyses revealed significantly stronger neural circuits in PT children between Wernicke's area and the right inferior frontal gyrus (R IFG, Broca's area homologue) and both the left and the right supramarginal gyri (SMG) components of the inferior parietal lobules (p</=0.02 for all). We conclude that PT subjects employ neural systems for auditory language function at school age differently than T controls; these alterations may represent a delay in maturation of neural networks or the engagement of alternate circuits for language processing.

[1]  E. Bullmore,et al.  Lateralisation of language function in young adults born very preterm , 2004, Archives of Disease in Childhood - Fetal and Neonatal Edition.

[2]  R Todd Constable,et al.  Longitudinal Brain Volume Changes in Preterm and Term Control Subjects During Late Childhood and Adolescence , 2009, Pediatrics.

[3]  Angela D. Friederici,et al.  Functional Neural Networks of Semantic and Syntactic Processes in the Developing Brain , 2007, Journal of Cognitive Neuroscience.

[4]  N. C. Silver,et al.  Averaging Correlation Coefficients: Should Fishers z Transformation Be Used? , 1987 .

[5]  Volkmar Glauche,et al.  Ventral and dorsal pathways for language , 2008, Proceedings of the National Academy of Sciences.

[6]  J. Volpe,et al.  Outcome of neonatal intraventricular hemorrhage with periventricular echodense lesions , 1984, Annals of neurology.

[7]  P. Skudlarski,et al.  Brain Connectivity Related to Working Memory Performance , 2006, The Journal of Neuroscience.

[8]  B. Vohr,et al.  Brain volume reductions within multiple cognitive systems in male preterm children at age twelve. , 2008, The Journal of pediatrics.

[9]  H. Harrison Outcomes in young adulthood for very-low-birth-weight infants. , 2002, The New England journal of medicine.

[10]  T. Klingberg,et al.  Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network. , 2003, Brain research. Cognitive brain research.

[11]  B. Vohr,et al.  Prematurely Born Children Demonstrate White Matter Microstructural Differences at 12 Years of Age, Relative to Term Control Subjects: An Investigation of Group and Gender Effects , 2008, Pediatrics.

[12]  Christopher J. Cannistraci,et al.  Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. , 2000, JAMA.

[13]  D. Shannon,et al.  Neurologic sequelae in the survivors of neonatal intraventricular hemorrhage. , 1979, Pediatrics.

[14]  Xenophon Papademetris,et al.  More accurate Talairach coordinates for neuroimaging using non-linear registration , 2008, NeuroImage.

[15]  W. Szymonowicz,et al.  Neurodevelopmental outcome of periventricular haemorrhage and leukomalacia in infants 1250 g or less at birth. , 1986, Early human development.

[16]  Karl J. Friston,et al.  Movement‐Related effects in fMRI time‐series , 1996, Magnetic resonance in medicine.

[17]  Allan L. Reiss,et al.  Increased temporal lobe gyrification in preterm children , 2006, Neuropsychologia.

[18]  Walter Allan,et al.  Change in cognitive function over time in very low‐birth‐weight infants. , 2003, JAMA.

[19]  S. Petersen,et al.  Development of distinct control networks through segregation and integration , 2007, Proceedings of the National Academy of Sciences.

[20]  B. Shaywitz,et al.  Dyslexia (specific reading disability). , 2003, Pediatrics in review.

[21]  David L. Streiner,et al.  Transition of Extremely Low-Birth-Weight Infants From Adolescence to Young Adulthood: Comparison With Normal Birth-Weight Controls , 2006 .

[22]  Vincent Schmithorst,et al.  Age-related connectivity changes in fMRI data from children listening to stories , 2007, NeuroImage.

[23]  S. Petersen,et al.  The maturing architecture of the brain's default network , 2008, Proceedings of the National Academy of Sciences.

[24]  Joseph Hajnal,et al.  Natural History of Brain Lesions in Extremely Preterm Infants Studied With Serial Magnetic Resonance Imaging From Birth and Neurodevelopmental Assessment , 2006, Pediatrics.

[25]  Heping Zhang,et al.  A functional magnetic resonance imaging study of language processing and its cognitive correlates in prematurely born children. , 2002, Pediatrics.

[26]  Allan L Reiss,et al.  Sex differences in cerebral volumes of 8-year-olds born preterm. , 2004, The Journal of pediatrics.

[27]  Michelle Hampson,et al.  Connectivity–behavior analysis reveals that functional connectivity between left BA39 and Broca's area varies with reading ability , 2006, NeuroImage.

[28]  Carles Falcón,et al.  Hippocampal functional magnetic resonance imaging during a face–name learning task in adolescents with antecedents of prematurity , 2005, NeuroImage.

[29]  Núria Bargalló,et al.  White matter volume and concentration reductions in adolescents with history of very preterm birth: A voxel-based morphometry study , 2006, NeuroImage.

[30]  B. Vohr,et al.  Volumetric analysis of regional cerebral development in preterm children. , 2004, Pediatric neurology.

[31]  B. Vohr,et al.  Transition of Extremely Low-Birth-Weight Infants From Adolescence to Young Adulthood: Comparison With Normal Birth-Weight Controls , 2007 .

[32]  Vince D. Calhoun,et al.  Measuring brain connectivity: Diffusion tensor imaging validates resting state temporal correlations , 2008, NeuroImage.

[33]  S. Shinnar,et al.  Intraventricular hemorrhage in the premature infant. , 1982, The New England journal of medicine.

[34]  R Todd Constable,et al.  Cortical recruitment patterns in children born prematurely compared with control subjects during a passive listening functional magnetic resonance imaging task. , 2006, The Journal of pediatrics.

[35]  Jed A. Meltzer,et al.  A Functional Magnetic Resonance Imaging Study of the Long-term Influences of Early Indomethacin Exposure on Language Processing in the Brains of Prematurely Born Children , 2006, Pediatrics.

[36]  Núria Bargalló,et al.  Correlations of thalamic reductions with verbal fluency impairment in those born prematurely , 2006, Neuroreport.

[37]  Chiara Nosarti,et al.  Adolescents who were born very preterm have decreased brain volumes. , 2002, Brain : a journal of neurology.

[38]  Mark Schluchter,et al.  Poor Predictive Validity of the Bayley Scales of Infant Development for Cognitive Function of Extremely Low Birth Weight Children at School Age , 2005, Pediatrics.

[39]  G. Cioni,et al.  Atypical language lateralization and early linguistic development in children with focal brain lesions. , 2005, Developmental medicine and child neurology.

[40]  P. Skudlarski,et al.  Disruption of posterior brain systems for reading in children with developmental dyslexia , 2002, Biological Psychiatry.

[41]  T. Inder,et al.  Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. , 2006, The New England journal of medicine.

[42]  Peter Fransson,et al.  Resting-state networks in the infant brain , 2007, Proceedings of the National Academy of Sciences.