Network connectivity underlying episodic memory in children: Application of a pediatric brain tumor survivor injury model.

التفاصيل البيبلوغرافية
العنوان:	Network connectivity underlying episodic memory in children: Application of a pediatric brain tumor survivor injury model.
المؤلفون:	Alonso KW; The Hospital for Sick Children, Toronto, Canada.; Department of Psychology, University of Toronto, Toronto, Canada., Dahhan NZA; The Hospital for Sick Children, Toronto, Canada., Riggs L; Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada.; Department of Pediatrics, University of Toronto, Toronto, Canada., Tseng J; The Hospital for Sick Children, Toronto, Canada., de Medeiros C; The Hospital for Sick Children, Toronto, Canada., Scott M; The Hospital for Sick Children, Toronto, Canada., Laughlin S; The Hospital for Sick Children, Toronto, Canada., Bouffet E; The Hospital for Sick Children, Toronto, Canada., Mabbott DJ; The Hospital for Sick Children, Toronto, Canada.; Department of Psychology, University of Toronto, Toronto, Canada.
المصدر:	Developmental science [Dev Sci] 2024 Jan; Vol. 27 (1), pp. e13413. Date of Electronic Publication: 2023 May 23.
نوع المنشور:	Journal Article
اللغة:	English
بيانات الدورية:	Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 9814574 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1467-7687 (Electronic) Linking ISSN: 1363755X NLM ISO Abbreviation: Dev Sci Subsets: MEDLINE
أسماء مطبوعة:	Original Publication: Oxford, UK ; Malden, MA, USA : Wiley-Blackwell, c1998-
مواضيع طبية MeSH:	Memory, Episodic* , Brain Neoplasms*, Adult ; Child ; Humans ; Brain ; Diffusion Magnetic Resonance Imaging ; Survivors ; Magnetic Resonance Imaging
مستخلص:	Episodic memory involves personal experiences paired with their context. The Medial Temporal, Posterior Medial, Anterior Temporal, and Medial Prefrontal networks have been found to support the hippocampus in episodic memory in adults. However, there lacks a model that captures how the structural and functional connections of these networks interact to support episodic memory processing in children. Using diffusion-weighted imaging, magnetoencephalography, and memory tests, we quantified differences in white matter microstructure, neural communication, and episodic memory performance, respectively, of healthy children (n = 23) and children with reduced memory performance. Pediatric brain tumor survivors (PBTS; n = 24) were used as a model, as they exhibit reduced episodic memory and perturbations in white matter and neural communication. We observed that PBTS, compared to healthy controls, showed significantly (p < 0.05) (1) disrupted white matter microstructure between these episodic memory networks through lower fractional anisotropy and higher mean and axial diffusivity, (2) perturbed theta band (4-7 Hz) oscillatory synchronization in these same networks through higher weighted phase lag indices (wPLI), and (3) lower episodic memory performance in the Transverse Patterning and Children's Memory Scale (CMS) tasks. Using partial-least squares path modeling, we found that brain tumor treatment predicted network white matter damage, which predicted inter-network theta hypersynchrony and lower verbal learning (directly) and lower verbal recall (indirectly via theta hypersynchrony). Novel to the literature, our findings suggest that white matter modulates episodic memory through effect on oscillatory synchronization within relevant brain networks. RESEARCH HIGHLIGHTS: Investigates the relationship between structural and functional connectivity of episodic memory networks in healthy children and pediatric brain tumor survivors Pediatric brain tumor survivors demonstrate disrupted episodic memory, white matter microstructure and theta oscillatory synchronization compared to healthy children Findings suggest white matter microstructure modulates episodic memory through effects on oscillatory synchronization within relevant episodic memory networks. (© 2023 The Authors. Developmental Science published by John Wiley & Sons Ltd.)
References:	Avants, B., Tustison, N., & Johnson, H. (2009). Advanced normalization tools (ANTS). Insight Journal, 2(365), 1-35. Avery, S. N., Rogers, B. P., & Heckers, S. (2018). Hippocampal network modularity is associated with relational memory dysfunction in schizophrenia. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3(5), 423-432. https://doi.org/10.1016/j.bpsc.2018.02.001. Barnett, A. J., Reilly, W., Dimsdale-Zucker, H. R., Mizrak, E., Reagh, Z., & Ranganath, C. (2021). Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain. PLoS Biology, 19(6), e3001275. https://doi.org/10.1371/journal.pbio.3001275. Bartolomei, F., Bosma, I., Klein, M., Baayen, J. C., Reijneveld, J. C., Postma, T. J., Heimans, J. J., van Dijk, B. W., de Munck, J. C., de Jongh, A., Cover, K. S., & Stam, C. J. (2006a). Disturbed functional connectivity in brain tumour patients: Evaluation by graph analysis of synchronization matrices. Clinical Neurophysiology, 117(9), 2039-2049. https://doi.org/10.1016/j.clinph.2006.05.018. Bartolomei, F., Bosma, I., Klein, M., Baayen, J. C., Reijneveld, J. C., Postma, T. J., Heimans, J. J., van Dijk, B. W., de Munck, J. C., de Jongh, A., Cover, K. S., & Stam, C. J. (2006b). How do brain tumors alter functional connectivity? A magnetoencephalography study. Annals of Neurology, 59(1), 128-138. https://doi.org/10.1002/ana.20710. Basser, P. J. (1995). Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR in Biomedicine, 8(7), 333-344. https://doi.org/10.1002/nbm.1940080707. Baum, G. L., Cui, Z., Roalf, D. R., Ciric, R., Betzel, R. F., Larsen, B., Cieslak, M., Cook, P. A., Xia, C. H., Moore, T. M., Ruparel, K., Oathes, D. J., Alexander-Bloch, A. F., Shinohara, R. T., Raznahan, A., Gur, R. E., Gur, R. C., Bassett, D. S., & Satterthwaite, T. D. (2020). Development of structure-function coupling in human brain networks during youth. PNAS, 117(1), 771-778. https://doi.org/10.1073/pnas.1912034117. Bells, S., Lefebvre, J., Longoni, G., Narayanan, S., Arnold, D. L., Yeh, E. A., & Mabbott, D. J. (2019). White matter plasticity and maturation in human cognition. Glia, 67(11), 2020-2037. https://doi.org/10.1002/glia.23661. Bells, S., Lefebvre, J., Prescott, S. A., Dockstader, C., Bouffet, E., Skocic, J., Laughlin, S., & Mabbott, D. J. (2017). Changes in white matter microstructure impact cognition by disrupting the ability of neural assemblies to synchronize. Journal of Neuroscience, 37(34), 8227-8238. https://doi.org/10.1523/JNEUROSCI.0560-17.2017. Bosma, I., Reijneveld, J. C., Klein, M., Douw, L., van Dijk, B. W., Heimans, J. J., & Stam, C. J. (2009). Disturbed functional brain networks and neurocognitive function in low-grade glioma patients: A graph theoretical analysis of resting-state MEG. Nonlinear Biomed Physics, 3, 1-11. https://doi.org/10.1186/1753-4631-3-9. Burke, J. F., Zaghlou, K. A., Jacobs, J., Williams, R. B., Sperling, M. R., Sharan, A. D., & Kahana, M. J. (2013). Synchronous and asynchronous theta and gamma activity during episodic memory formation. Journal of Neuroscience, 33(1), 292-304. https://doi.org/10.1523/JNEUROSCI.2057-12.2013. Buzsáki, G. (2006). Rhythms of the brain. Oxford university press. https://doi.org/10.1093/acprof:oSo/9780195301069.001.0001. Calamante, F., Tournier, J. D., Jackson, G. D., & Connelly, A. (2010). Track-density imaging (TDI): Super-resolution white matter imaging using whole-brain track-density mapping. Neuroimage, 53(4), 1233-1243. https://doi.org/10.1016/j.neuroimage.2010.07.024. Cohen, J. R., & D'Esposito, M. (2016). The segregation and integration of distinct brain networks and their relationship to cognition. Journal of Neuroscience, 36(48), 12083-12094. https://doi.org/10.1523/JNEUROSCI.2965-15.2016. Cohen, M. J. (1997). CMS children's memory scale. Pearson. Cox, E., Bells, S., Timmons, B. W., Laughlin, S., Bouffet, E., de Medeiros, C., Beera, K., Harasym, D., & Mabbott, D. J. (2020). A controlled clinical crossover trial of exercise training to improve cognition and neural communication in pediatric brain tumor survivors. Clinical Neurophysiology, 131(7), 1533-1547. https://doi.org/10.1016/j.clinph.2020.03.027. Czernochowski, D., Mecklinger, A., & Johansson, M. (2009). Age-related changes in the control of episodic retrieval: An ERP study of recognition memory in children and adults. Developmental Science, 12(6), 1026-1040. https://doi.org/10.1111/j.1467-7687.2009.00841.x. Decker, A. L., Szulc, K. U., Bouffet, E., Laughlin, S., Chakravarty, M. M., Skocic, J., de Medeiros, C. B., & Mabbott, D. J. (2017). Smaller hippocampal subfield volumes predict verbal associative memory in pediatric brain tumor survivors. Hippocampus, 27(11), 1140-1154. https://doi.org/10.1002/hipo.22758. De Master, D., Pathman, T., Lee, J. K., & Ghetti, S. (2014). Structural development of the hippocampus and episodic memory: Developmental differences along the anterior/posterior axis. Cerebral Cortex, 24(11), 3036-3045. https://doi.org/10.1093/cercor/bht160. DiNicola, L. M., Braga, R. M., & Buckner, R. L. (2020). Parallel distributed networks dissociate episodic and social functions within the individual. Journal of Neurophysiology, 123(3), 1144-1179. https://doi.org/10.1152/JN.00529.2019. Doppelmayr, M., Klimesch, W., Schwaiger, J., Auinger, P., & Winkler, T. (1998). Theta synchronization in the human EEG and episodic retrieval. Neuroscience Letters, 257(1), 41-44. https://doi.org/10.1016/S0304-3940(98)00805-2. Douet, V., & Chang, L. (2015). Fornix as an imaging marker for episodic memory deficits in healthy aging and in various neurological disorders. Frontiers in Aging Neuroscience, 7(JAN), 1-19. https://doi.org/10.3389/fnagi.2014.00343. Fell, J., & Axmacher, N. (2011). The role of phase synchronization in memory processes. Nature Reviews Neuroscience, 12(2), 105-118. https://doi.org/10.1038/nrn2979. Fields, R. D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neuroscience (Tins), 31(7), 361-370. https://doi.org/10.1016/j.tins.2008.04.001. Fields, R. D. (2015). A new mechanism of nervous system plasticity: Activity-dependent myelination. Nature Reviews Neuroscience, 16(12), 756-767. https://doi.org/10.1007/s11065-015-9294-9. Finn, A. S., Kalra, P. B., Goetz, C., Leonard, J. A., Sheridan, M. A., & Gabrieli, J. D. E. (2016). Developmental dissociation between the maturation of procedural memory and declarative memory. Journal of Experimental Child Psychology, 142(3), 212-220. https://doi.org/10.1016/j.jecp.2015.09.027. Flynn, J. R. (2013). Are we getting smarter? (Vol. 38). Cambridge University Press. https://doi.org/10.1017/CBO9781139235679.001. Fries, P. (2005). A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence. Trends in Cognitive Sciences, 9(10), 474-480. https://doi.org/10.1016/j.tics.2005.08.011. Fynes-Clinton, S., Marstaller, L., & Burianová, H. (2019). Differentiation of functional networks during long-term memory retrieval in children and adolescents. Neuroimage, 191(August 2018), 93-103. https://doi.org/10.1016/j.neuroimage.2019.01.065. Gauvreau, S., Lefebvre, J., Bells, S., Laughlin, S., Bouffet, E., & Mabbott, D. J. (2019). Disrupted network connectivity in pediatric brain tumor survivors is a signature of injury. Journal of Comparative Neurology, 527(17), 2896-2909. https://doi.org/10.1002/cne.24717. Ghetti, S., & Bunge, S. A. (2012). Neural changes underlying the development of episodic memory during middle childhood. Developmental Cognitive Neuroscience, 2(4), 381-395. https://doi.org/10.1016/j.dcn.2012.05.002. Glasser, M. F., Coalson, T. S., Robinson, E. C., Hacker, C. D., Harwell, J., Yacoub, E., Ugurbil, K., Andersson, J., Beckmann, C. F., Jenkinson, M., Smith, S. M., & Van Essen, D. C. (2016). A multi-modal parcellation of human cerebral cortex. Nature, 536(7615), 171-178. https://doi.org/10.1038/nature18933. Hanslmayr, S., Axmacher, N., & Inman, C. S. (2019). Modulating human memory via entrainment of brain oscillations. Trends in Neuroscience (Tins), 42(7), 485-499. https://doi.org/10.1016/j.tins.2019.04.004. Hoaglin, D. C., Mosteller, F., & Tukey, J. W. (1985). Exploring data tables, trends, and shapes . John Wiley & Sons. https://doi.org/10.2307/1164753. Hopf, L., Quraan, M. A., Cheung, M. J., Taylor, M. J., Ryan, J. D., & Moses, S. N. (2013). Hippocampal lateralization and memory in children and adults. Journal of the International Neuropsychological Society, 19(10), 1042-1052. https://doi.org/10.1017/S1355617713000751. Huang, M. X., Theilmann, R. J., Robb, A., Angeles, A., Nichols, S., Drake, A., D'Andrea, J., Levy, M., Holland, M., Song, T., Ge, S., Hwang, E., Yoo, K., Cui, L., Baker, D. G., Trauner, D., Coimbra, R., & Lee, R. R. (2009). Integrated imaging approach with MEG and DTI to detect mild traumatic brain injury in military and civilian patients. Journal of Neurotrauma, 26(8), 1213-1226. https://doi.org/10.1089/neu.2008.0672. Hutt, A., Mierau, A., & Lefebvre, J. (2016). Dynamic control of synchronous activity in networks of spiking neurons. PLoS ONE, 11(9), 1-15. https://doi.org/10.1371/journal.pone.0161488. Jakobowicz, E. (2006). Understanding PLS path modeling parameters estimates: A study based on monte carlo simulation and customer satisfaction surveys. 17th Symp Comput Stat, Published online, 1-8. http://163.173.228.40/fichiers/art_1057.pdf. Janzen, L., Mabbott, D., & Guger, S. L. (2015). Neuropsychological outcomes in pediatric brain tumor survivors. In Pediatric neuro-oncology (pp. 267-276). Springer. https://doi.org/10.1007/978-1-4939-1541-5_24. Jeurissen, B., Tournier, J. D., Dhollander, T., Connelly, A., & Sijbers, J. (2014). Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage, 103, 411-426. https://doi.org/10.1016/j.neuroimage.2014.07.061. Kieffer-Renaux, V., Bulteau, C., Grill, J., Kalifa, C., Viguier, D., & Jambaque, I. (2000). Patterns of neuropsychological deficits in children with medulloblastoma according to craniospatial irradiation doses. Developmental Medicine and Child Neurology, 42(11), 741-745. https://doi.org/10.1017/S0012162200001377. Krukow, P., Jonak, K., Grochowski, C., Plechawska-Wójcik, M., & Karakuła-Juchnowicz, H. (2020). Resting-state hyperconnectivity within the default mode network impedes the ability to initiate cognitive performance in first-episode schizophrenia patients. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 102(February). https://doi.org/10.1016/j.pnpbp.2020.109959. Lebel, C., & Beaulieu, C. (2011). Longitudinal development of human brain wiring continues from childhood into adulthood. Journal of Neuroscience, 31(30), 10937-10947. https://doi.org/10.1523/JNEUROSCI.5302-10.2011. Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., & Beaulieu, C. (2012). Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage, 60(1), 340-352. https://doi.org/10.1016/j.neuroimage.2011.11.094. Lefebvre, J., Hutt, A., Knebel, J. F., Whittingstall, K., & Murray, M. M. (2015). Stimulus statistics shape oscillations in nonlinear recurrent neural networks. Journal of Neuroscience, 35(7), 2895-2903. https://doi.org/10.1523/JNEUROSCI.3609-14.2015. Li, C. S. R., Yan, P., Bergquist, K. L., & Sinha, R. (2007). Greater activation of the “default” brain regions predicts stop signal errors. Neuroimage, 38(3), 640-648. https://doi.org/10.1016/j.neuroimage.2007.07.021. Libby, L. A., Ekstrom, A. D., Daniel Ragland, J., & Ranganath, C. (2012). Differential connectivity of perirhinal and parahippocampal cortices within human hippocampal subregions revealed by high-resolution functional imaging. Journal of Neuroscience, 32(19), 6550-6560. https://doi.org/10.1523/JNEUROSCI.3711-11.2012. Lingo, P. R., Choudhri, A. F., & Klimo, P. (2018). Principles of pediatric neurosurgery. Brain Tumors in Children, 17-31. https://doi.org/10.1007/978-3-319-43205-2_2. Liu, F., Scantlebury, N., Tabori, U., Bouffet, E., Laughlin, S., Strother, D., McConnell, D., Hukin, J., Fryer, C., Brière, M. E., Montour-Proulx, I., Keene, D., Wang, F., & Mabbott, D. J. (2014). White matter compromise predicts poor intellectual outcome in survivors of pediatric low-grade glioma. Neuro-oncology, 17(4), 604-613. https://doi.org/10.1093/neuonc/nou306. Mabbott, D. J., Noseworthy, M., Bouffet, E., Laughlin, S., & Rockel, C. (2006). White matter growth as a mechanism of cognitive development in children. Neuroimage, 33(3), 936-946. https://doi.org/10.1016/j.neuroimage.2006.07.024. Mabbott, D. J., Rovet, J., Noseworthy, M. D., Lou, S. M., & Rockel, C. (2009). The relations between white matter and declarative memory in older children and adolescents. Brain Research, 1294, 80-90. https://doi.org/10.1016/j.brainres.2009.07.046. MacDonald, S. M., Bindra, R. S., Sethi, R., & Ladra, M. (2018). Principles of radiation oncology. Brain Tumors in Children, 33-64. https://doi.org/10.1007/978-3-319-43205-2_3. Maechler, M., Todorov, V., Ruckstuhl, A., Salibian-barrera, M., Koller, M., & Conceicao, E. L. T. (2021). Package ‘robustbase ’. Basic Robust Statistics, 2021. Manual R, Connectome NBS. (2012). Reference Manual for NBS Connectome (v1.2) December 2012. Maril, A., Davis, P. E., Koo, J. J., Reggev, N., Zuckerman, M., Ehrenfeld, L., Mulkern, R. V., Waber, D. P., & Rivkin, M. J. (2010). Developmental fMRI study of episodic verbal memory encoding in children. Neurology, 75(23), 2110-2116. https://doi.org/10.1212/WNL.0b013e318201526e. May, C. P. (1999). Synchrony effects in cognition: The costs and a benefit. Psychonomic Bulletin & Review, 6(1), 142-147. https://doi.org/10.3758/BF03210822. McKiernan, K. A., Kaufman, J. N., Kucera-Thompson, J., & Binder, J. R. (2003). A parametric manipulation of factors affecting task-induced deactivation in functional neuroimaging. Journal of Cognitive Neuroscience, 15(3), 394-408. https://doi.org/10.1162/089892903321593117. Memel, M., Wank, A. A., Ryan, L., & Grilli, M. D. (2020). The relationship between episodic detail generation and anterotemporal, posteromedial, and hippocampal white matter tracts. Cortex; A Journal Devoted to the Study of the Nervous System and Behavior, 123, 124-140. https://doi.org/10.1016/j.cortex.2019.10.010. Micklewright, L. J., King, Z. T., Morris, D. R., & Krawiecki, N. (2008). Quantifying pediatric neuro-oncology risk factors: Development of the neurological predictor scale. Journal of Child Neurology, 23(4), 455-458. https://doi.org/10.1177/0883073807309241. Milton, C. K., Dhanaraj, V., Young, I. M., Taylor, H. M., Nicholas, P. J., Briggs, R. G., Bai, M. Y., Fonseka, R. D., Hormovas, J., Lin, Y. H., Tanglay, O., Conner, A. K., Glenn, C. A., Teo, C., Doyen, S., & Sughrue, M. E. (2021). Parcellation-based anatomic model of the semantic network. Brain Behaviour, 11(4), 1-13. https://doi.org/10.1002/brb3.2065. Mogan, R., Fischer, R., & Bulbulia, J. A. (2017). To be in synchrony or not? A meta-analysis of synchrony's effects on behavior, perception, cognition and affect. Journal of Experimental Social Psychology, 72(September 2016), 13-20. https://doi.org/10.1016/j.jesp.2017.03.009. Moore, B. D. (2005). Neurocognitive outcomes in survivors of childhood cancer. Journal of Pediatric Psychology, 30(1), 51-63. https://doi.org/10.1093/jpepsy/jsi016. Moxon-Emre, I., Farb, N. A. S., Oyefiade, A. A., Bouffet, E., Laughlin, S., Skocic, J., de Medeiros, C. B., & Mabbott, D. J. (2019). Facial emotion recognition in children treated for posterior fossa tumours and typically developing children: A divergence of predictors. NeuroImage Clinical, 23(October 2018), 101886. https://doi.org/10.1016/j.nicl.2019.101886. Moxon-Emre, I., Taylor, M. D., Bouffet, E., Hardy, K., Campen, C. J., Malkin, D., Hawkins, C., Laperriere, N., Ramaswamy, V., Bartels, U., Scantlebury, N., Janzen, L., Law, N., Walsh, K. S., & Mabbott, D. J. (2016). Intellectual outcome in molecular subgroups of medulloblastoma. Journal of Clinical Oncology, 34(34), 4161-4170. https://doi.org/10.1200/JCO.2016.66.9077. Mulhern, R. K., Merchant, T. E., Gajjar, A., Reddick, W. E., & Kun, L. E. (2004). Late neurocognitive sequelae in survivors of brain tumours in childhood. The Lancet Oncology, 5(7), 399-408. https://doi.org/10.1016/S1470-2045(04)01507-4. Nagel, B. J., Delis, D. C., Palmer, S. L., Reeves, C., Gajjar, A., & Mulhern, R. K. (2006). Early patterns of verbal memory impairment in children treated for medulloblastoma. Neuropsychology, 20(1), 105-112. https://doi.org/10.1037/0894-4105.20.1.105. Nagel, B. J., Palmer, S. L., Reddick, W. E., Glass, J. O., Helton, K. J., Wu, S., Xiong, X., Kun, L. E., Gajjar, A., & Mulhern, R. K. (2004). Abnormal hippocampal development in children with medulloblastoma treated with risk-adapted irradiation. American Journal of Neuroradiology, 25(9), 1575-1582. Ngo, C. T., Alm, K. H., Metoki, A., Hampton, W., Riggins, T., Newcombe, N. S., & Olson, I. R. (2017). White matter structural connectivity and episodic memory in early childhood. Developmental Cognitive Neuroscience, 28(November), 41-53. https://doi.org/10.1016/j.dcn.2017.11.001. Nolte, G. (2003). The magnetic lead field theorem in the quasi-static approximation and its use for magnetoenchephalography forward calculation in realistic volume conductors. Physics in Medicine and Biology, 48(22), 3637-3652. https://doi.org/10.1088/0031-9155/48/22/002. Northcott, P. A., Robinson, G. W., Kratz, C. P., Mabbott, D. J., Pomeroy, S. L., Clifford, S. C., Rutkowski, S., Ellison, D. W., Malkin, D., Taylor, M. D., Gajjar, A., & Pfister, S. M. (2019). Medulloblastoma. Nature Reviews Disease Primers, 5(1), 11. https://doi.org/10.1038/s41572-019-0063-6. Nyhus, E., & Curran, T. (2010). Functional role of gamma and theta oscillations in episodic memory. Neuroscience and Biobehavioral Reviews, 34(7), 1023-1035. https://doi.org/10.1016/j.neubiorev.2009.12.014. Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J. M. (2011). FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational Intelligence and Neuroscience, 2011. https://doi.org/10.1155/2011/156869. Oyefiade, A., Paltin, I., De Luca, C. R., Hardy, K. K., Grosshans, D. R., Chintagumpala, M., Mabbott, D. J., & Kahalley, L. S. (2021). Cognitive risk in survivors of pediatric brain tumors. Journal of Clinical Oncology, 39(16), 1718-1726. https://doi.org/10.1200/JCO.20.02338. Pajevic, S., Basser, P. J., & Fields, R. D. (2014). Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience, 276, 135-147. https://doi.org/10.1016/j.neuroscience.2013.11.007. Pollack, I. F. (2011). Multidisciplinary management of childhood brain tumors: A review of outcomes, recent advances, and challenges - A review. Journal of Neurosurgery: Pediatrics, 8(2), 135-148. https://doi.org/10.3171/2011.5.PEDS1178. Pollack, I. F., Agnihotri, S., & Broniscer, A. (2019). Childhood brain tumors: Current management, biological insights, and future directions. Journal of Neurosurgery: Pediatrics, 23(3), 261-273. https://doi.org/10.3171/2018.10.PEDS18377. Ranganath, C., & Ritchey, M. (2012). Two cortical systems for memory-guided behaviour. Nature Reviews Neuroscience, 13(10), 713-726. https://doi.org/10.1038/nrn3338. Reddick, W. E., White, H. A., Glass, J. O., Wheeler, G. C., Thompson, S. J., Gajjar, A., Leigh, L., & Mulhern, R. K. (2003). Developmental model relating white matter volume to neurocognitive deficits in pediatric brain tumor survivors. Cancer, 97(10), 2512-2519. https://doi.org/10.1002/cncr.11355. Riggs, L., Bouffet, E., Laughlin, S., Laperriere, N., Liu, F., Skocic, J., Scantlebury, N., Wang, F., Schoenhoff, N. J., Strother, D., Hukin, J., Fryer, C., McConnell, D., & Mabbott, D. J. (2014). Changes to memory structures in children treated for posterior fossa tumors. Journal of the International Neuropsychological Society, 20(2), 168-180. https://doi.org/10.1017/S135561771300129X. Ritchey, M., & Cooper, R. A. (2020). Deconstructing the posterior medial episodic network. Trends in Cognitive Sciences, 24(6), 451-465. https://doi.org/10.1016/j.tics.2020.03.006. Ritchey, M., Libby, L. A., & Ranganath, C. (2015). Cortico-hippocampal systems involved in memory and cognition: The PMAT framework (Vol 219, 1st ed.). Elsevier B.V. https://doi.org/10.1016/bs.pbr.2015.04.001. Roberts, B. M., Clarke, A., Addante, R. J., & Ranganath, C. (2018). Entrainment enhances theta oscillations and improves episodic memory. Cognitive Neuroscience, 9(3-4), 181-193. https://doi.org/10.1080/17588928.2018.1521386. Rönnlund, M., & Nilsson, L. G. (2009). Flynn effects on sub-factors of episodic and semantic memory: Parallel gains over time and the same set of determining factors. Neuropsychologia, 47(11), 2174-2180. https://doi.org/10.1016/j.neuropsychologia.2008.11.007. Rugg, M. D., & Vilberg, K. L. (2013). Brain networks underlying episodic memory retrieval. Current Opinion in Neurobiology, 23(2), 255-260. https://doi.org/10.1016/j.conb.2012.11.005. Sánchez, G. (2013). PLS path modeling with R. Berkeley Trowchez Ed, 383(1), 235. http://gastonsanchez.com/PLS_Path_Modeling_with_R.pdf. Scantlebury, N., Bouffet, E., Laughlin, S., Strother, D., McConnell, D., Hukin, J., Fryer, C., Laperriere, N., Montour-Proulx, I., Keene, D., Fleming, A., Jabado, N., Liu, F., Riggs, L., Law, N., & Mabbott, D. J. (2016). White matter and information processing speed following treatment with cranial-spinal radiation for pediatric brain tumor. Neuropsychology, 30(4), 425-438. https://doi.org/10.1037/neu0000258. Smith, M. L., & McAndrews, M. P. (2013). The hippocampus and episodic memory in children. Journal of the International Neuropsychological Society, 19(10), 1027-1030. https://doi.org/10.1017/S1355617713001070. Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2012). Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage, 62(3), 1924-1938. https://doi.org/10.1016/j.neuroimage.2012.06.005. Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2015). SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography. Neuroimage, 119, 338-351. https://doi.org/10.1016/j.neuroimage.2015.06.092. Squire, L. R., & Zola-Morgan, S. (1991). The medial temporal lobe memory system. Science (80-), 253(5026), 1380-1386. https://doi.org/10.1126/science.1896849. Staudigl, T., Hanslmayr, S., & Bäuml, K. H. T. (2010). Theta oscillations reflect the dynamics of interference in episodic memory retrieval. Journal of Neuroscience, 30(34), 11356-11362. https://doi.org/10.1523/JNEUROSCI.0637-10.2010. Suárez, L. E., Markello, R. D., Betzel, R. F., & Misic, B. (2020). Linking structure and function in macroscale brain networks. Trends in Cognitive Sciences, 24(4), 302-315. https://doi.org/10.1016/j.tics.2020.01.008. Swanson, S. J., Chapin, J. S., & Janecek, J. K. (2014). The neuropsychology of epilepsy. In: Clinical neuropsychology: A pocket handbook for assessment (pp. 181-207). Technology R-T. (2022). R-Studio for Mac. Published online. Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159-205. https://doi.org/10.1016/j.csda.2004.03.005. Tournier, J. D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C. H., & Connelly, A. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage, 202, 116137. https://doi.org/10.1016/j.neuroimage.2019.116137. Tulving, E., & Markowitsch, H. J. (1997). Memory beyond the hippocampus. Current Opinion in Neurobiology, 7(2), 209-216. https://doi.org/10.1016/S0959-4388(97)80009-8. Uhlhaas, P. J., Roux, F., Rodriguez, E., Rotarska-Jagiela, A., & Singer, W. (2010). Neural synchrony and the development of cortical networks. Trends in Cognitive Sciences, 14(2), 72-80. https://doi.org/10.1016/j.tics.2009.12.002. Uhlhaas, P. J., & Singer, W. (2011). The development of neural synchrony and large-scale cortical networks during adolescence: Relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis. Schizophrenia Bulletin, 37(3), 514-523. https://doi.org/10.1093/schbul/sbr034. Vinck, M., Oostenveld, R., Van Wingerden, M., Battaglia, F., & Pennartz, C. M. A. (2011). An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage, 55(4), 1548-1565. https://doi.org/10.1016/j.neuroimage.2011.01.055. Ward, A. M., Schultz, A. P., Huijbers, W., Van Dijk, K. R. A., Hedden, T., & Sperling, R. A (2014). The parahippocampal gyrus links the default-mode cortical network with the medial temporal lobe memory system. Human Brain Mapping, 35(3), 1061-1073. https://doi.org/10.1002/hbm.22234. Wongupparaj, P., Wongupparaj, R., Kumari, V., & Morris, R. G. (2017). The Flynn effect for verbal and visuospatial short-term and working memory: A cross-temporal meta-analysis. Intelligence, 64(March 2016), 71-80. https://doi.org/10.1016/j.intell.2017.07.006. Yonelinas, A. P., Ranganath, C., Ekstrom, A. D., & Wiltgen, B. J. (2019). A contextual binding theory of episodic memory: Systems consolidation reconsidered. Nature Reviews Neuroscience, 20(6), 364-375. https://doi.org/10.1038/s41583-019-0150-4. Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: Identifying differences in brain networks. Neuroimage, 53(4), 1197-1207. https://doi.org/10.1016/j.neuroimage.2010.06.041.
معلومات مُعتمدة:	MOP-123537 Canada CAPMC CIHR; MOP-123537 Canada CAPMC CIHR
فهرسة مساهمة:	Keywords: episodic memory; network connectivity; oscillatory synchronization; path modeling; pediatric brain tumors; white matter
تواريخ الأحداث:	Date Created: 20230523 Date Completed: 20231216 Latest Revision: 20231216
رمز التحديث:	20231217
DOI:	10.1111/desc.13413
PMID:	37218519
قاعدة البيانات:	MEDLINE

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تدمد:	1467-7687
DOI:	10.1111/desc.13413