Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T09:29:39.995Z Has data issue: false hasContentIssue false
  • English
  • Français

Double Dissociation of Auditory Attention Span and Visual Attention in Long-Term Survivors of Childhood Cerebellar Tumor: A Deterministic Tractography Study of the Cerebellar-Frontal and the Superior Longitudinal Fasciculus Pathways

Published online by Cambridge University Press:  28 April 2020

Alyssa S. Ailion ,
Tricia Z. King Open the ORCID record for Tricia Z. King [Opens in a new window] ,
Simone R. Roberts ,
Brian Tang ,
Jessica A. Turner ,
Christopher M. Conway  and
Bruce Crosson
Alyssa S. Ailion
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA
Tricia Z. King*
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA
Simone R. Roberts
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA Atlanta VA Center of Excellence for Visual and Neurocognitive Rehabilitation, Atlanta, GA, USA
Brian Tang
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA
Jessica A. Turner
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA
Christopher M. Conway
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA
Bruce Crosson
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA 30302-5010, USA Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA Atlanta VA Center of Excellence for Visual and Neurocognitive Rehabilitation, Atlanta, GA, USA Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
*
*Correspondence and reprint requests to: Tricia Z. King, Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA 30302-5010, USA. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

Right cerebellar-left frontal (RC-LF) white matter integrity (WMI) has been associated with working memory. However, prior studies have employed measures of working memory that include processing speed and attention. We examined the relationships between the RC-LF WMI and processing speed, attention, and working memory to clarify the relationship of RC-LF WMI with a specific cognitive function. Right superior longitudinal fasciculus II (SLF II) WMI and visual attention were included as a negative control tract and task to demonstrate a double dissociation.

Methods:

Adult survivors of childhood brain tumors [n = 29, age: M = 22 years (SD = 5), 45% female] and demographically matched controls were recruited (n = 29). Tests of auditory attention span, working memory, and visual attention served as cognitive measures. Participants completed a 3-T MRI diffusion-weighted imaging scan. Fractional anisotropy (FA) and radial diffusivity (RD) served as WMI measures. Partial correlations between WMI and cognitive scores included controlling for type of treatment.

Results:

A correlational double dissociation was found. RC-LF WMI was associated with auditory attention (FA: r = .42, p = .03; RD: r = −.50, p = .01) and was not associated with visual attention (FA: r = −.11, p = .59; RD: r = −.11, p = .57). SLF II FA WMI was associated with visual attention (FA: r = .44, p = .02; RD: r = −.17, p = .40) and was not associated with auditory attention (FA: r = .24, p = .22; RD: r = −.10, p = .62).

Conclusions:

The results show that RC-LF WMI is associated with auditory attention span rather than working memory per se and provides evidence for a specificity based on the correlational double dissociation.

Keywords

Structural MRIDiffusion tractographyCerebellumNeurocognitive outcomesCognitionWhite matter pathwayWorking memoryDigit span
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 26 , Issue 10 , November 2020 , pp. 939 - 953
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ailion, A.S., Hortman, K., & King, T.Z. (2017). Childhood brain tumors: A systematic review of the structural neuroimaging literature. Neuropsychology Review, 27, 220–244. doi: 10.1007/s11065-017-9352-6 CrossRefGoogle ScholarPubMed
Ailion, A.S., King, T.Z., Wang, L., Fox, M.E., Mao, H., Morris, R.M., & Crosson, B. (2016). Cerebellar atrophy in adult survivors of childhood cerebellar tumor. Journal of International Neuropsychological Society, 22(5), 501–511. doi: 10.1017/s1355617716000138 CrossRefGoogle ScholarPubMed
Ailion, A.S., Roberts, S.R., Crosson, B., & King, T.Z. (2019). Neuroimaging of the component white matter connections and structures within the cerebellar-frontal pathway in posterior fossa tumor survivors. NeuroImage. Clinical, 23, 101894. doi: 10.1016/j.nicl.2019.101894 CrossRefGoogle ScholarPubMed
Aukema, E.J., Caan, M.W., Oudhuis, N., Majoie, C.B., Vos, F.M., Reneman, L., … Schouten-van Meeteren, A.Y. (2009). White matter fractional anisotropy correlates with speed of processing and motor speed in young childhood cancer survivors. International Journal of Radiation Oncology, Biology, Physics, 74(3), 837–843. doi: 10.1016/j.ijrobp.2008.08.060 CrossRefGoogle ScholarPubMed
Baddeley, A. (1996). The fractionation of working memory. Proceedings of the National Academy of Sciences, 93(24), 13468–13472. Retrieved from http://www.pnas.org/content/93/24/13468.abstract CrossRefGoogle ScholarPubMed
Bartzokis, G., Lu, P.H., Heydari, P., Couvrette, A., Lee, G.J., Kalashyan, G., … Altshuler, L.L. (2012). Multimodal magnetic resonance imaging assessment of white matter aging trajectories over the lifespan of healthy individuals. Biological Psychiatry, 72(12), 1026–1034. doi: 10.1016/j.biopsych.2012.07.010 CrossRefGoogle ScholarPubMed
Bechara, A., Tranel, D., Damasio, H., Adolphs, R., Rockland, C., & Damasio, A.R. (1995). Double dissociation of conditioning and declarative knowledge relative to the amygdala and hippocampus in humans. Science (New York, N.Y.), 269(5227), 1115–1118. https://doi.org/10.1126/science.7652558 CrossRefGoogle ScholarPubMed
Benjamini, Y. & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57(1), 289–300. doi: 10.2307/2346101 Google Scholar
Bennett, C.M., Wolford, G.L., & Miller, M.B. (2009). The principled control of false positives in neuroimaging. Social Cognitive and Affective Neuroscience, 4, 417–422. doi: 10.1093/scan/nsp053 CrossRefGoogle Scholar
Ben-Yehudah, G., Guediche, S., and Fiez, J.E. (2007). Cerebellar contributions to verbal working memory: Beyond cognitive theory. The Cerebellum, 6, 193–201.CrossRefGoogle Scholar
Bisley, J.W. and Goldberg, M.E. (2003). Neuronal activity in the lateral intraparietal area and spatial attention. Science, 299, 81–86.CrossRefGoogle Scholar
Black, F.W., & Strub, R.L. (1978). Digit repetition performance in patients with focal brain damage. Cortex, 14(1), 12–21.CrossRefGoogle ScholarPubMed
Blumenfeld, H. (2010). Neuroanatomy through Clinical Cases (2nd ed.). Sunderland, MA: Sinauer Associates, Inc., ISBN 978-0-87893.Google Scholar
Bohsali, A., Triplett, W., Sudhyadhom, A., Gullett, J.M., McGregor, K., FitzGerald, D.B., … Crosson, B. (2015). Broca’s area - Thalamic connectivity. Brain and Language, 141C, 80–88. doi: 10.1016/j.bandl.2014.12.001 CrossRefGoogle Scholar
Brodmann, K. (1909). Vergleichende lokalisationslehre der großhirnrinde: In ihren prinzipien. Leipzig, Germany: Barth.Google Scholar
Brown, J. (1958). Some tests of the decay theory of immediate memory. Quarterly Journal of Experimental Psychology, 10(1), 12–21. doi: 10.1080/17470215808416249.CrossRefGoogle Scholar
Bunce, D. & Macready, A. (2005). Processing speed, executive function, and age differences in remembering and knowing. The Quarterly Journal of Experimental Psychology A, 58(1), 155–168. doi: 10.1080/02724980443000197 CrossRefGoogle ScholarPubMed
Cascio, C.J., Gerig, G., & Piven, J. (2007). Diffusion tensor imaging: Application to the study of the developing brain. Journal of the American Academy of Child and Adolescent Psychiatry, 46(2), 213–223.CrossRefGoogle Scholar
Catani, M., Dell’acqua, F., Vergani, F., Malik, F., Hodge, H., Roy, P., … Thiebaut de Schotten, M. (2012). Short frontal lobe connections of the human brain. Cortex, 48(2), 273–291. doi: 10.1016/j.cortex.2011.12.001 CrossRefGoogle ScholarPubMed
Chen, S.H. & Desmond, J.E. (2005). Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks. Neuroimage, 24(2), 332–338.CrossRefGoogle ScholarPubMed
Colon-Perez, L.M., Spindler, C., Goicochea, S., Triplett, W., Parekh, M., Montie, E., … Mareci, T.H. (2015). Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks. Plos One, 10(7), 1–29. doi: 10.1371/journal.pone.0131493 CrossRefGoogle Scholar
Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan (D-KEFS) Executive Function System Technical Manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Dennis, M., Francis, D.J., Cirino, P.T., Schachar, R., Barnes, M.A., & Fletcher, J.M. (2009). Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders. Journal of the International Neuropsychology Society, 15(3), 331–343. doi: 10.1017/S1355617709090481 CrossRefGoogle Scholar
Desikan, R.S., Segonne, F., Fischl, B., Quinn, B.T., Dickerson, B.C., Blacker, D., … Killiany, R.J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3), 968–980. doi: 10.1016/j.neuroimage.2006.01.021 CrossRefGoogle ScholarPubMed
Desmond, J., Gabrieli, J., Wagner, A., Ginier, B., & Glover, G. (1997). Lobular patterns of cerebellar activation in verbal working-memory and finger-tapping tasks as revealed by functional MRI. The Journal of Neuroscience, 17(24), 9675–9685.CrossRefGoogle ScholarPubMed
Doricchi, F & Tomaiuolo, F. (2003). The anatomy of neglect without hemianopia: a key role for parietal–frontal disconnection? NeuroReport, 14, 2239–2243.CrossRefGoogle Scholar
Doricchi, F., Thiebaut de Schotten, M., Tomaiuolo, F., & Bartolomeo, P. (2008). White matter (dis)connections and gray matter (dys)functions in visual neglect: gaining insights into the brain networks of spatial awareness. Cortex, 44(8), 983–995. doi: 10.1016/j.cortex.2008.03.006 CrossRefGoogle ScholarPubMed
Ford, A., Colon-Perez, L., Triplett, W.T., Gullett, J.M., Mareci, T.H., & Fitzgerald, D.B. (2013). Imaging white matter in human brainstem. Frontiers in Human Neuroscience, 7(July), 400. doi: 10.3389/fnhum.2013.00400 CrossRefGoogle ScholarPubMed
Friederici, A.D., Hahne, A., & von Cramon, D.Y. (1998). First-pass versus second-pass parsing processes in a Wernicke’s and a Broca’s aphasic: electrophysiological evidence for a double dissociation. Brain and Language, 62(3), 311–341. https://doi.org/10.1006/brln.1997.1906 CrossRefGoogle Scholar
Gerton, B.K., Brown, T.T., Meyer-Lindenberg, A., Kohn, P., Holt, J.L., Olsen, R.K., & Berman, K.F. (2004). Shared and distinct neurophysiological components of the digits forward and backward tasks as revealed by functional neuroimaging. Neuropsychologia, 42(13), 1781–1787. doi: 10.1016/j.neuropsychologia.2004.04.023 CrossRefGoogle ScholarPubMed
Hoaglin, D.C. & Iglewicz, B. (1987). Fine tuning some resistant rules for outlier labeling. Journal of American Statistical Association, 82, 1147–1149.CrossRefGoogle Scholar
Hoeft, F., Barnea-Goraly, N., Haas, B.W., Golarai, G., Ng, D., Mills, D., … Reiss, A.L. (2007). More is not always better: increased fractional anisotropy of superior longitudinal fasciculus associated with poor visuospatial abilities in Williams syndrome. Journal of Neuroscience, 27(44), 11960–11965. doi: 10.1523/jneurosci.3591-07.2007 CrossRefGoogle Scholar
Jayakar, R., King, T.Z., Morris, R., & Na, S. (2015). Hippocampal volume and auditory attention on a verbal memory task with adult survivors of pediatric brain tumor. Neuropsychology, 29(2), 303–319.CrossRefGoogle ScholarPubMed
Jian, B. & Vemuri, B.C. (2007a). A unified computational framework for deconvolution to reconstruct multiple fibers from diffusion weighted MRI. IEEE Transactions on Medical Imaging, 26(11), 1464–71. doi: 10.1109/TMI.2007.907552 CrossRefGoogle ScholarPubMed
Jian, B. & Vemuri, B.C. (2007b). Multi-fiber reconstruction from diffusion mri using mixture of Wisharts and Sparse Deconvolution. Information Processing in Medical Imaging, 20, 384–395.CrossRefGoogle ScholarPubMed
Jian, B., Vemuri, B.C., Özarslan, E., Carney, P.R., & Mareci, T.H. (2007). A novel tensor distribution model for the diffusion-weighted MR signal. NeuroImage, 37(1), 164–76. doi: 10.1016/j.neuroimage.2007.03.074 CrossRefGoogle ScholarPubMed
Jissendi, P, Baudry, S, & Baleriaux, D (2008). Diffusion tensor imaging (DTI) and tractography of the cerebellar projections to prefrontal and posterior parietal cortices: A study at 3T. Journal of Neuroradiology, 35, 42–50.CrossRefGoogle Scholar
Kamali, A., Flanders, A.E., Brody, J., Hunter, J.V., & Hasan, K.M. (2014). Tracing superior longitudinal fasciculus connectivity in the human brain using high resolution diffusion tensor tractography. Brain Structure and Function, 219(1), 269–281. doi: 10.1007/s00429-012-0498-y CrossRefGoogle ScholarPubMed
Karlsgodt, K.H., van Erp, T.G., Poldrack, R.A., Bearden, C.E., Nuechterlein, K.H., & Cannon, T.D. (2008). Diffusion tensor imaging of the superior longitudinal fasciculus and working memory in recent-onset schizophrenia. Biological Psychiatry, 63(5), 512–518. doi: 10.1016/j.biopsych.2007.06.017 CrossRefGoogle ScholarPubMed
Kelly, R.M. & Strick, P.L. (2003). Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. The Journal of neuroscience: The official journal of the Society for Neuroscience, 23, 8432–8444.CrossRefGoogle ScholarPubMed
Khong, P.L., Kwong, D.L., Chan, G.C., Sham, J.S., Chan, F.L., & Ooi, G.C. (2003). Diffusion-tensor imaging for the detection and quantification of treatment-induced white matter injury in children with medulloblastoma: A pilot study. AJNR. American Journal of Neuroradiology, 24(4), 734–740.Google ScholarPubMed
Kiefer, M., Apel, A., & Weisbrod, M. (2002). Arithmetic fact retrieval and working memory in schizophrenia. Schizophrenia Research, 53(3), 219–227.CrossRefGoogle Scholar
King, T.Z., Ailion, A.S., Fox, M.E., & Hufstetler, S.M. (2017). Neurodevelopmental model of long-term outcomes of adult survivors of childhood brain tumors. Child Neuropsychology, 1–21. doi: 10.1080/09297049.2017.1380178 Google ScholarPubMed
King, T.Z. & Na., S. (2016). Cumulative Neurological Factors Predict Long-term Outcomes in Adult Survivors of Childhood Brain Tumors. Child Neuropsychology, 22(6), 748–760. doi: 10.1080/09297049.2015.1049591 CrossRefGoogle Scholar
King, T.Z., Na, S., & Mao, H. (2015a). Neural underpinnings of working memory in adult survivors of childhood brain tumors. Journal of the International Neuropsychological Society, 21(7), 494–505. doi: 10.1017/S135561771500051X CrossRefGoogle ScholarPubMed
King, T.Z., Wang, L., & Mao, H. (2015b). Disruption of white matter integrity in adult survivors of childhood brain tumors: Correlates with long-term intellectual outcomes. PLOS One, 10(7), e0131744. doi: 10.1371/journal.pone.0131744 CrossRefGoogle ScholarPubMed
Law, N., Bouffet, E., Laughlin, S., Laperriere, N., Briere, M.E., Strother, D., … Mabbott, D. (2011). Cerebello-thalamo-cerebral connections in pediatric brain tumor patients: impact on working memory. NeuroImage, 56(4), 2238–2248. doi: 10.1016/j.neuroimage.2011.03.065 CrossRefGoogle ScholarPubMed
Law, N., Greenberg, M., Bouffet, E., Laughlin, S., Taylor, M.D., Malkin, D., … Mabbott, D. (2015a). Visualization and segmentation of reciprocal cerebrocerebellar pathways in the healthy and injured brain. Human Brain Mapping, 36(7), 2615–2628. doi: 10.1002/hbm.22795 CrossRefGoogle ScholarPubMed
Law, N., Greenberg, M., Bouffet, E., Taylor, M.D., Laughlin, S., Strother, D., … Mabbott, D.J. (2012). Clinical and neuroanatomical predictors of cerebellar mutism syndrome. Neuro-Oncology, 14(10), 1294–1303. doi: 10.1093/neuonc/nos160 CrossRefGoogle ScholarPubMed
Law, N., Smith, M.L., Greenberg, M., Bouffet, E., Taylor, M.D., Laughlin, S., … Mabbott, D. (2015b). Executive function in paediatric medulloblastoma: The role of cerebrocerebellar connections. Journal of Neuropsychology. doi: 10.1111/jnp.12082 Google ScholarPubMed
Lezak, M.D., Howieson, D.B., Bigler, E., & Tranel, D. (2012) Neuropsychological Assessment, 5th Edition. New York: Oxford University Press.Google Scholar
Makris, N., Kennedy, D.N., McInerney, S., Sorensen, A.G., Wang, R., Caviness, V.S. Jr, & Pandya, D.N. (2005). Segmentation of subcomponents within the superior longitudinal fascicle in humans: A quantitative, invivo, DT-MRI study. Cerebral Cortex 15, 854–869.CrossRefGoogle Scholar
Marvel, C.L. & Desmond, J.E. (2010). The contributions of cerebro-cerebellar circuitry to executive verbal working memory. Cortex, 46(7), 880–895. doi: 10.1016/j.cortex.2009.08.017 CrossRefGoogle ScholarPubMed
Merchant, T.E., Hua, C.H., Shukla, H., Ying, X., Nill, S., & Oelfke, U. (2008). Proton versus photon radiotherapy for common pediatric brain tumors: Comparison of models of dose characteristics and their relationship to cognitive function. Pediatric Blood & Cancer, 51(1), 110–117. doi: 10.1002/pbc.21530 CrossRefGoogle ScholarPubMed
Mesulam, M.M. (1981). A cortical network for directed attention and unilateral neglect. Annals of Neurology, 10, 309–325.CrossRefGoogle ScholarPubMed
Micklewright, J.L., King, T.Z., Morris, R.D., & Krawiecki, N. (2008). Quantifying pediatric neuro-oncology risk factors: development of the neurological predictor scale. Journal of Child Neurology, 23(4), 455–458. doi: 10.1177/0883073807309241 CrossRefGoogle ScholarPubMed
Miller, G.A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. doi: 10.1037/h0043158 CrossRefGoogle ScholarPubMed
Miller, D.C. (2013). Essentials of School Neuropsychological Assessment (2nd ed.). Hoboken, NJ: John Wiley & Sons, Inc.Google Scholar
Mukherjee, P., Berman, J.I., Chung, S.W., Hess, C.P., & Henry, R.G. (2008). Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. AJNR American Journal of Neuroradiology, 29(4), 632–641. doi: 10.3174/ajnr.A1051 CrossRefGoogle ScholarPubMed
Mulhern, R.K., Palmer, S.L., Reddick, W.E., Glass, J.O., Kun, L.E., Taylor, J., … Gajjar, A. (2001). Risks of young age for selected neurocognitive deficits in medulloblastoma are associated with white matter loss. Journal of Clinical Oncology, 19(2), 472–479.CrossRefGoogle ScholarPubMed
Naidich, T.P., Duvernoy, H.M., Delman, B.N., Sorensen, A.G., Kollias, S.S., & Haacke, E.M. (2009). Duvernoy’s Atlas of the Human Brain Stem and Cerebellum High-Field MRI: Surface Anatomy, Internal Structure, Vascularization and 3D Sectional Anatomy. Wien, Austria: Springer CrossRefGoogle Scholar
Nomura, E.M., Gratton, C., Visser, R.M., Kayser, A., Perez, F., & D’Esposito, M. (2010). Double dissociation of two cognitive control networks in patients with focal brain lesions. Proceedings of the National Academy of Sciences of the United States of America, 107(26), 12017–12022. doi: 10.1073/pnas.1002431107 CrossRefGoogle ScholarPubMed
Ono, M., Kubik, S., & Abernathey, C.D. (1990). Atlas of the Cerebral Sulci. New York: Thieme.Google Scholar
Osborne, J.W. & Overbay, A. (2004). The power of outliers (and why researchers should always check for them). Practical Assessment, Research & Evaluation, 9(6), 1–8.Google Scholar
Ostrom, Q.T., de Blank, P.M., Kruchko, C., Petersen, C.M., Liao, P., Finlay, J.L., … Barnholtz-Sloan, J.S. (2015). Alex’s lemonade stand foundation infant and childhood primary brain and central nervous system tumors diagnosed in the United States in 2007-2011. Neuro-oncology, 16(Suppl 10), x1–x36. doi: 10.1093/neuonc/nou327 CrossRefGoogle ScholarPubMed
Palmer, S.L. (2008). Neurodevelopmental impact on children treated for medulloblastoma: a review and proposed conceptual model. Developmental Disabilities Research Reviews, 14(3), 203–210. doi: 10.1002/ddrr.32 CrossRefGoogle ScholarPubMed
Palmer, S.L., Glass, J.O., Li, Y., Ogg, R., Qaddoumi, I., Armstrong, G.T., … Reddick, W.E. (2012). White matter integrity is associated with cognitive processing in patients treated for a posterior fossa brain tumor. Neuro-oncology, 14(9), 1185–1193. doi: 10.1093/neuonc/nos154 CrossRefGoogle ScholarPubMed
Palmer, S.L., Reddick, W.E., Glass, J.O., Gajjar, A., Goloubeva, O., & Mulhern, R.K. (2002). Decline in corpus callosum volume among pediatric patients with medulloblastoma: longitudinal MR imaging study. AJNR American Journal of Neuroradiology, 23(7), 1088–1094.Google ScholarPubMed
Peterson, L.R. & Peterson, M.J. (1959). Short-term retention of individual verbal items. Mulhern. doi: 10.1037/h0049234. PMID 14432252.Google ScholarPubMed
Reddick, W.E., Russell, J.M., Glass, J.O., et al. (2000). Subtle white matter volume differences in children treated for medulloblastoma with conventional or reduced-dose cranial-spinal irradiation. Magnetic Resonance Imaging, 18, 787–793.CrossRefGoogle ScholarPubMed
Reddick, W.E., Glass, J.O., Palmer, S.L., Wu, S., Gajjar, A., Langston, J.W., … Mulhern, R.K. (2005). Atypical white matter volume development in children following craniospinal irradiation. Neuro-oncology, 7(1), 12–19. doi: 10.1215/S1152851704000079 CrossRefGoogle ScholarPubMed
Reinhold, H.S., Calvo, W., Hopewell, J.W., & Van Den Breg, A.P. (1990). Development of blood vessel-related radiation damage in the fimbria of the central nervous system. International Journal of Radiation Oncology Biology Physics, 18, 37–42.CrossRefGoogle ScholarPubMed
Riggs, L., Bouffet, E., Laughlin, S., Laperriere, N., Liu, F., Skocic, J., … 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. doi: 10.1017/s135561771300129x CrossRefGoogle ScholarPubMed
Roberts, S.R. (2017). The left hemisphere’s structural connectivity for the inferior frontal gyrus, striatum, and thalamus, and intra-thalamic topography. (Master’s thesis). Georgia State University, Atlanta, GA.Google Scholar
Rueckriegel, S.M., Bruhn, H., Thomale, U.W., & Hernaiz Driever, P. (2015). Cerebral white matter fractional anisotropy and tract volume as measured by MR imaging are associated with impaired cognitive and motor function in pediatric posterior fossa tumor survivors. Pediatric Blood & Cancer, 62(7), 1252–1258. doi: 10.1002/pbc.25485 CrossRefGoogle ScholarPubMed
Shan, Z.Y., Liu, J.Z., Glass, J.O., Gajjar, A., Li, C.S., & Reddick, W.E. (2006). Quantitative morphologic evaluation of white matter in survivors of childhood medulloblastoma. Magnetic Resonance Imaging, 24(8), 1015–1022. doi: 10.1016/j.mri.2006.04.015 CrossRefGoogle ScholarPubMed
Shiffrin, R.M. & Nosofsky, R.M. (1994). Seven plus or minus two: A commentary on capacity limitations. Psychological Review, 101, 357–361.CrossRefGoogle ScholarPubMed
Smith, A. (1982). Symbol Digit Modality Test. Los Angeles, CA: Western Psychological Services.Google Scholar
Smith, K.M. (2016). Corpus callosum and word reading in adult survivors of childhood posterior fossa tumors. (Doctoral dissertation). Georgia State University, Atlanta, GA.Google Scholar
Song, S.K., Yoshino, J., Le, T.Q., Lin, S.J., Sun, S.W., Cross, A.H., & Armstrong, R.C. (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage, 26, 132–140.CrossRefGoogle ScholarPubMed
Spreen, O. & Strauss, E. (1998). A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary (2nd ed.). New York, NY: Oxford University Press.Google Scholar
Stuss, D., Stethem, L., & Pelchat, G. (1988). Three tests of attention and rapid information processing: An extension. Clinical Neuropsychologist, 2(3), 246–250.CrossRefGoogle Scholar
Taiwo, Z., Na, S., & King, T.Z. (2017) The Neurological Predictor Scale: A predictive tool for neurocognitive late effects in survivors of childhood brain tumors. Pediatric Blood and Cancer, 64(1), 172–179. doi: 10.1002/pbc.26203 CrossRefGoogle Scholar
Thiebaut de Schotten, M., Dell’Acqua, F., Forkel, S.J., Simmons, A., Vergani, F., Murphy, D.G., & Catani, M. (2011). A lateralized brain network for visuospatial attention. Natural Neuroscience, 14(10), 1245–1246. doi: 10.1038/nn.2905 CrossRefGoogle ScholarPubMed
Turken, A.U. & Dronkers, N.F. (2011). The neural architecture of the language comprehension network: Converging evidence from lesion and connectivity analyses. Frontiers Systems Neuroscience, 5, 1. doi: 10.3389/fnsys.2011.00001 CrossRefGoogle ScholarPubMed
Urbanski, M., Thiebaut de Schotten, M., Rodrigo, S., Catani, M., Oppenheim, C., Touze, E., Chokron, S., Meder, J.-F., Levy, R., Dubois, B., & Bartolomeo, P. (2008). Brain networks of spatial awareness: Evidence from diffusion tensor imaging tractography. Journal of Neurology, Neurosurgery and Psychiatry, 79, 598–601.CrossRefGoogle ScholarPubMed
Viallon, M., Cuvinciuc, V., Delattre, B., Merlini, L., Barnaure-Nachbar, I., Toso-Patel, S., … Haller, S. (2015). State-of-the-art MRI techniques in neuroradiology: Principles, pitfalls, and clinical applications. Neuroradiology, 57(5), 441–467. doi: 10.1007/s00234-015-1500-1 CrossRefGoogle ScholarPubMed
Waxman, S.G. (2009). Clinical Neuroanatomy. New York: McGraw-Hill Education.Google Scholar
Wechsler, D. (1997). Wechsler Memory Scale - Third Edition. Manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1999). WASI Manual. San Antonio: Psychological Corporation.Google Scholar
Weinberg, J., Diller, L., Gerstman, L., & Schulman, P. (1972). Digit span in right and left hemiplegics. Journal of Clinical Psychology, 28(3), 361.3.0.CO;2-5>CrossRefGoogle ScholarPubMed
Wolfe, K.R., Madan-Swain, A., & Kana, R.K. (2012). Executive dysfunction in pediatric posterior fossa tumor survivors: a systematic literature review of neurocognitive deficits and interventions. Development Neuropsychology, 37(2), 153–175. doi: 10.1080/87565641.2011.632462 CrossRefGoogle ScholarPubMed
Woods, R.P., Grafton, S.T., Holmes, C.J., Cherry, S.R., & Mazziotta, J.C. (1998). Automated image registration: I. General methods and intrasubject, intramodality validation. Journal of Computer Assisted Tomography, 22, 139–152.CrossRefGoogle ScholarPubMed
Zhang, J.X., Leung, H.C., & Johnson, M.K. (2003). Frontal activations associated with accessing and evaluating information in working memory: An fMRI study. Neuroimage, 20(3), 1531–1539.CrossRefGoogle Scholar
Supplementary material: File

Ailion et al. supplementary material

Ailion et al. supplementary material

Download Ailion et al. supplementary material(File)
File 23.8 KB