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Functional Magnetic Resonance Imaging during Visual Perception Tasks in Adolescents Born Prematurely

Published online by Cambridge University Press:  15 September 2020

Annika Lind Open the ORCID record for Annika Lind [Opens in a new window] ,
Leena Haataja ,
Marja Laasonen ,
Virva Saunavaara ,
Henry Railo ,
Tuomo Lehtonen ,
Victor Vorobyev ,
Karoliina Uusitalo ,
Katri Lahti  and
Riitta Parkkola
Annika Lind*
Affiliation:
Department of Psychology, University of Turku, Turku, Finland Turku Institute for Advanced Studies (TIAS), University of Turku, Turku, Finland
Leena Haataja
Affiliation:
Children’s Hospital, Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Marja Laasonen
Affiliation:
Department of Speech and Language Pathology, University of Turku, Turku, Finland Department of Otorhinolaryngology and Phoniatrics, Head and Neck Surgery, Helsinki University Hospital and University of Helsinki, Helsinki, Finland Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
Virva Saunavaara
Affiliation:
Department of Medical Physics, Division of Medical Imaging, Turku University Hospital, Turku, Finland Turku PET Centre, Turku University Hospital, Turku, Finland
Henry Railo
Affiliation:
Department of Psychology, University of Turku, Turku, Finland Department of Clinical Neurophysiology, University of Turku and Turku University Hospital, Turku, Finland
Tuomo Lehtonen
Affiliation:
Department of Ophthalmology, University of Turku and Turku University Hospital, Turku, Finland
Victor Vorobyev
Affiliation:
Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland
Karoliina Uusitalo
Affiliation:
Department of Pediatric Neurology, University of Turku, Turku, Finland
Katri Lahti
Affiliation:
Department of Pediatric Neurology, University of Turku, Turku, Finland
Riitta Parkkola
Affiliation:
Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland
*
*Correspondence and reprint requests to: Annika Lind, Department of Psychology, University of Turku, 20014Turun yliopisto, Finland. Email: annika.lind@utu.fi
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Abstract

Objectives:

Impairments in visual perception are among the most common developmental difficulties related to being born prematurely, and they are often accompanied by problems in other developmental domains. Neural activation in participants born prematurely and full-term during tasks that assess several areas of visual perception has not been studied. To better understand the neural substrates of the visual perceptual impairments, we compared behavioral performance and brain activations during visual perception tasks in adolescents born very preterm (birth weight ≤1500 g or gestational age <32 weeks) and full-term.

Methods:

Tasks assessing visual closure, discrimination of a deviating figure, and discrimination of figure and ground from the Motor-Free Visual Perception Test, Third Edition were performed by participants born very preterm (n = 37) and full-term (n = 34) at 12 years of age during functional magnetic resonance imaging.

Results:

Behavioral performance in the visual perception tasks did not differ between the groups. However, during the visual closure task, brain activation was significantly stronger in the group born very preterm in a number of areas including the frontal, anterior cingulate, temporal, and posterior medial parietal/cingulate cortices, as well as in parts of the cerebellum, thalamus, and caudate nucleus.

Conclusions:

Differing activations during the visual closure task potentially reflect a compensatory neural process related to premature birth or lesser neural efficiency or may be a result of the use of compensatory behavioral strategies in the study group born very preterm.

Keywords

PrematurityVery pretermVery low birth weightfMRIVisual closureVisual discrimination
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 27 , Issue 3 , March 2021 , pp. 270 - 281
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

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References

REFERENCES

Adaval, R., Saluja, G., & Jiang, Y. (2019). Seeing and thinking in pictures: A review of visual information processing. Consumer Psychology Review, 2, 50–69.Google Scholar
Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38, 95–113.CrossRefGoogle ScholarPubMed
Binder, J.R., Swanson, S.J., Hammeke, T.A., & Sabsevitz, D.S. (2008). A comparison of five fMRI protocols for mapping speech comprehension systems. Epilepsia, 49, 1980–1997.CrossRefGoogle ScholarPubMed
Brittain, P.J., Froudist-Walsh, S., Nam, K.W., Giampietro, V., Karolis, V., Murray, R.M.,…Nosarti, C. (2014). Neural compensation in adulthood following very preterm birth demonstrated during a visual paired associates learning task. Neuroimage Clinical, 6, 54–63.CrossRefGoogle ScholarPubMed
Butcher, P.R., Bouma, A., Stremmelaar, E.F., Bos, A.F., Smithson, M., & Van Braeckel, K.N. (2012). Visuospatial perception in children born preterm with no major neurological disorders. Neuropsychology, 26, 723–734.CrossRefGoogle ScholarPubMed
Chaminade, T., Leutcher, R.H., Millet, V., & Deruelle, C. (2013). fMRI evidence for dorsal stream processing abnormality in adults born preterm. Brain and Cognition, 81, 67–72.CrossRefGoogle ScholarPubMed
Colarusso, R., & Hammill, D., (2003). Motor-free Visual Perception Test (3rd edn.). Novata, CA: Academic Therapy Publications.Google Scholar
Daamen, M., Bauml, J.G., Scheef, L., Sorg, C., Busch, B., Baumann, N.,…Boecker, H. (2015). Working memory in preterm-born adults: Load-dependent compensatory activity of the posterior default mode network. Human Brain Mapping, 36, 1121–1137.CrossRefGoogle ScholarPubMed
Davis, D.W., Burns, B.M., Wilkerson, S.A., & Steichen, J.J. (2005). Visual perceptual skills in children born with very low birth weights. Journal of Pediatric Health Care, 19, 363–368.CrossRefGoogle ScholarPubMed
Dorn, M., Lidzba, K., Bevot, A., Goelz, R., Hauser, T.K., & Wilke, M. (2014). Long-term neurobiological consequences of early postnatal hCMV-infection in former preterms: A functional MRI study. Human Brain Mapping, 35, 2594–2606.CrossRefGoogle ScholarPubMed
van Ettinger-Veenstra, H., Widen, C., Engstrom, M., Karlsson, T., Leijon, I., & Nelson, N. (2017). Neuroimaging of decoding and language comprehension in young very low birth weight (VLBW) adolescents: Indications for compensatory mechanisms. PLoS ONE, 12, e0185571.CrossRefGoogle ScholarPubMed
Froudist-Walsh, S., Karolis, V., Caldinelli, C., Brittain, P. J., Kroll, J., Rodriguez-Toscano, E., … Nosarti, C. (2015). Very early brain damage leads to remodeling of the working memory system in adulthood: A combined fMRI/Tractography study. The Journal of Neuroscience, 35, 15787–15799.CrossRefGoogle ScholarPubMed
Gaser, G., & Dahnke, R. (2016). CAT - A Computational Anatomy Toolbox for the Analysis of Structural MRI Data. HBM 2016, 336–348.Google Scholar
Geldof, C.J., van Wassenaer, A.G., de Kieviet, J.F., Kok, J.H., & Oosterlaan, J. (2012). Visual perception and visual-motor integration in very preterm and/or very low birth weight children: A meta-analysis. Research in Developmental Disabilities, 33, 726–736.CrossRefGoogle ScholarPubMed
Gimenez, M., Junque, C., Vendrell, P., Caldu, X., Narberhaus, A., Bargallo, N., … Mercader, J.M. (2005). Hippocampal functional magnetic resonance imaging during a face-name learning task in adolescents with antecedents of prematurity. Neuroimage, 25, 561–569.CrossRefGoogle Scholar
Griffiths, S.T., Aukland, S.M., Markestad, T., Eide, G.E., Elgen, I., Craven, A.R., & Hugdahl, K. (2014). Association between brain activation (fMRI), cognition and school performance in extremely preterm and term born children. Scandinavian Journal of Psychology, 55, 427–432.CrossRefGoogle Scholar
Grinband, J., Wager, T.D., Lindquist, M., Ferrera, V.P., & Hirsch, J. (2008). Detection of time-varying signals in event-related fMRI designs. Neuroimage, 43, 509–520.CrossRefGoogle ScholarPubMed
Johnson, S., Wolke, D., Hennessy, E., & Marlow, N. (2011). Educational outcomes in extremely preterm children: Neuropsychological correlates and predictors of attainment. Developmental Neuropsychology, 36, 74–95.CrossRefGoogle ScholarPubMed
de Kieviet, J.F., Heslenfeld, D.J., Pouwels, P.J., Lafeber, H.N., Vermeulen, R.J., van Elburg, R.M., & Oosterlaan, J. (2014). A crucial role for white matter alterations in interference control problems of very preterm children. Pediatric Research, 75, 731–737.CrossRefGoogle ScholarPubMed
Kravitz, D.J., Saleem, K.S., Baker, C.I., & Mishkin, M. (2011). A new neural framework for visuospatial processing. Nature reviews. Neuroscience, 12, 217–230.CrossRefGoogle ScholarPubMed
Leung, M.P., Thompson, B., Black, J., Dai, S., & Alsweiler, J.M. (2018). The effects of preterm birth on visual development. Clinical & Experimental Optometry, 101, 4–12.CrossRefGoogle ScholarPubMed
Lind, A., Korkman, M., Lehtonen, L., Lapinleimu, H., Parkkola, R., Matomaki, J., … the PIPARI Study Group (2011). Cognitive and neuropsychological outcomes at 5 years of age in preterm children born in the 2000s. Developmental Medicine and Child Neurology, 53, 256–262.CrossRefGoogle ScholarPubMed
Lind, A., Nyman, A., Lehtonen, L., & Haataja, L. (2020). Predictive value of psychological assessment at five years of age in the long-term follow-up of very preterm children. Child Neuropsychology, 26, 312–323.CrossRefGoogle ScholarPubMed
Molloy, C.S., Wilson-Ching, M., Anderson, V.A., Roberts, G., Anderson, P.J., & Doyle, L.W. (2013). Visual processing in adolescents born extremely low birth weight and/or extremely preterm. Pediatrics, 132, e704–12.CrossRefGoogle ScholarPubMed
Molloy, C.S., Di Battista, A.M., Anderson, V.A., Burnett, A., Lee, K.J., Roberts, G.,…Doyle, L.W. (2017). The contribution of visual processing to academic achievement in adolescents born extremely preterm or extremely low birth weight. Child Neuropsychology, 23, 361–379.CrossRefGoogle ScholarPubMed
Morcom, A.M., & Henson, R.N.A. (2018). Increased prefrontal activity with aging reflects nonspecific neural responses rather than compensation. The Journal of Neuroscience, 38, 7303–7313.CrossRefGoogle ScholarPubMed
Murner-Lavanchy, I., Ritter, B., Spencer-Smith, M.M., Perrig, W.J., Schroth, G., Steinlin, M., & Everts, R. (2014). Visuospatial working memory in very preterm and term born children--impact of age and performance. Developmental Cognitive Neuroscience, 9, 106–116.CrossRefGoogle ScholarPubMed
Murner-Lavanchy, I., Steinlin, M., Kiefer, C., Weisstanner, C., Ritter, B.C., Perrig, W., & Everts, R. (2014). Delayed development of neural language organization in very preterm born children. Developmental Neuropsychology, 39, 529–542.CrossRefGoogle ScholarPubMed
Narberhaus, A., Lawrence, E., Allin, M.P., Walshe, M., McGuire, P., Rifkin, L., … Nosarti, C. (2009). Neural substrates of visual paired associates in young adults with a history of very preterm birth: Alterations in fronto-parieto-occipital networks and caudate nucleus. Neuroimage, 47, 1884–1893.CrossRefGoogle ScholarPubMed
Perez-Roche, T., Altemir, I., Gimenez, G., Prieto, E., Gonzalez, I., Pena-Segura, J.L., … Pueyo, V. (2016). Effect of prematurity and low birth weight in visual abilities and school performance. Research in Developmental Disabilities, 59, 451–457.CrossRefGoogle ScholarPubMed
Salvan, P., Froudist Walsh, S., Allin, M.P., Walshe, M., Murray, R.M., Bhattacharyya, S., … Nosarti, C. (2013). Road work on memory lane-functional and structural alterations to the learning and memory circuit in adults born very preterm. Neuroimage, 15 (Pt 1), 152–161.Google Scholar
Smith, S.M., & Nichols, T.E. (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage, 44, 83–98.CrossRefGoogle ScholarPubMed
Wilke, M., Holland, S.K., Altaye, M., & Gaser, C. (2008). Template-O-Matic: A toolbox for creating customized pediatric templates. Neuroimage, 41, 903–913.CrossRefGoogle ScholarPubMed