Volumetric Analysis of Regional Variability in the Cerebellum of Children with Dyslexia

Fernandez, Vindia G.; Stuebing, Karla K.; Juranek, Jenifer; Fletcher, Jack Μ.

doi:10.1007/s12311-013-0504-9

Cited by 23 publications

(23 citation statements)

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“…This study was limited by lack of regional segmentation but it represents an important area for future research. Finally, Fernandez et al (2013) found less volume in the anterior lobe of the cerebellum bilaterally in a group of children with dyslexia relative to typical readers. This study aimed to examine the white matter integrity of cerebellar-cortical tracts in children and adolescents with specific deficits in decoding.…”

Section: Introductionmentioning

confidence: 80%

“…Studies of children and adults with dyslexia have reliably documented the contributions of left hemisphere regions typically associated with language and sensory processing: temporoparietal (TP), occipitotemporal (OT), inferior frontal (IF), and to a lesser extent subregions of the corpus callosum, in accurate and fluent word reading (Fletcher et al, 2007; Pugh et al, 2010). Despite the growing body of literature on the role of the cerebellum in speech and language (Ackermann, 2013), and reports of regional structural differences in the cerebellum of children with dyslexia (Fernandez et al, 2013; Eckert et al, 2003, 2005; Kibby & Hynd, 2008; Leonard, Eckert, Given, Berninger, & Eden, 2006), very little is known about the integrity of cerebellar-cortical white matter in individuals with dyslexia relative to typical readers. The lack of empirical data is especially noteworthy because a cerebellar theory of dyslexia has been proposed (Nicolson & Fawcett, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Fernandez et al (2013) investigated the role of regional variation in cerebellar anatomy in children with single-word decoding impairments ( N = 23), children with impairment in fluency alone ( N = 8), and typically developing children ( N = 16). Children with single-word decoding impairments demonstrated no statistically significant differences in overall gray and white matter volumes or cerebellar asymmetry; however, reduced volume bilaterally in the anterior lobe of the cerebellum relative to typical readers was observed.…”

Section: Introductionmentioning

confidence: 99%

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White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study

et al. 2016

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Little is known about the white matter integrity of cerebellar-cortical pathways in individuals with dyslexia. Building on previous findings of decreased volume in the anterior lobe of the cerebellum, we utilized novel cerebellar segmentation procedures and probabilistic tractography to examine tracts that connect the anterior lobe of the cerebellum and cortical regions typically associated with reading: the temporoparietal (TP), occipitotemporal (OT), and inferior frontal (IF) regions. The sample included 29 reading impaired children and 27 typical readers. We found greater fractional anisotropy (FA) for the poor readers in tracts connecting the cerebellum with TP and IF regions relative to typical readers. In the OT region, FA was greater for the older poor readers, but smaller for the younger ones. This study provides evidence for discrete, regionally-bound functions of the cerebellum and suggests that projections from the anterior cerebellum appear to have a regulatory effect on cortical pathways important for reading.

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Section: Introductionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study

et al. 2016

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“…3) show preserved motor learning, but impaired motor functions requiring predictive signals and precise calibration of the temporal features of movement (Dennis et al, 2010). Assessing motor prediction is important, even if not often done, because many disorders of the brain involve cerebellar pathology (e.g., Fernandez et al, 2013). …”

Section: What To Assessmentioning

confidence: 99%

Functional Plasticity in Childhood Brain Disorders: When, What, How, and Whom to Assess

et al. 2014

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At every point in the lifespan, the brain balances malleable processes representing neural plasticity that promote change with homeostatic processes that promote stability. Whether a child develops typically or with brain injury, his or her neural and behavioral outcome is constructed through transactions between plastic and homeostatic processes and the environment. In clinical research with children in whom the developing brain has been malformed or injured, behavioral outcomes provide an index of the result of plasticity, homeostasis, and environmental transactions. When should we assess outcome in relation to age at brain insult, time since brain insult, and age of the child at testing? What should we measure? Functions involving reacting to the past and predicting the future, as well as social-affective skills, are important. How should we assess outcome? Information from performance variability, direct measures and informants, overt and covert measures, and laboratory and ecological measures should be considered. In whom are we assessing outcome? Assessment should be cognizant of individual differences in gene, socio-economic status (SES), parenting, nutrition, and interpersonal supports, which are moderators that interact with other factors influencing functional outcome.

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“…Using these volumes, 72% of the dyslexic subjects and 88% of the controls were correctly classified. Correlated with these findings, Fernandez et al [191] also reported reduced volume of the anterior lobe of the cerebellum in dyslexic individuals based on manual tracing, which was aided by the cerebellar atlas published by Schmahmann et al [192]. Table 13 summarizes the current MRI-based systems for the detection of dyslexia-associated abnormalities in the planum temporale and cerebellum.…”

Section: The Grey Mattermentioning

confidence: 91%

Developing advanced mathematical models for detecting abnormalities in 2D/3D medical structures.

Elnakib¹

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DEDICATIONThis dissertation is dedicated to my mother, my father, and my wife for their love, patience, and support during the completion of this endeavor.iii ACKNOWLEDGMENTSIn the Name of Allah, the most beneficent, the most merciful. All deepest thanks are due to Allah, the compassionate for the uncountable gifts given to me.I would like to express my sincere gratitude to Professor El-Baz, my dissertation advisor, for the immeasurable amount of support and guidance he has provided throughout this study. He gave me the opportunity to work in his distinguished research group and provided me with an exciting working environment that facilitate many opportunities to develop new ideas and working on promising applications. Dr. El-Baz is always willing to give, share, and appreciate. I knew that I could always expect full credit for my accomplishments. He always supported me with novel ideas that helped me to publish my works in the top international conference and journal papers. It is worthy to mention that Professor El-Baz is a great advisor as well as a good friend who helps any Ph.D. student who works with him in high energy level. I cannot thank him enough, and shall remain grateful for all he has done. Detecting abnormalities in two-dimensional (2D) and three-dimensional (3D) medical structures is among the most interesting and challenging research areas in the medical imaging field. Obtaining the desired accurate automated quantification of abnormalities in medical structures is still very challenging. This is due to a large and constantly growing number of different objects of interest and associated abnormalities, large variations of their appearances and shapes in images, different medical imaging modalities, and associated changes of signal homogeneity and noise for each object. The main objective of this dissertation is to address these problems and to provide proper mathematical models and techniques that are capable of analyzing low and high resolution medical data and providing an accurate, automated analysis of the abnormalities in medical structures in terms of their area/volume, shape, and associated abnormal functionality.This dissertation presents different preliminary mathematical models and techniques that are applied in three case studies: (i) detecting abnormal tissue in vi the left ventricle (LV) wall of the heart from delayed contrast-enhanced cardiac magnetic resonance images (MRI), (ii) detecting local cardiac diseases based on estimating the functional strain metric from cardiac cine MRI, and (iii) identifying the abnormalities in the corpus callosum (CC) brain structure-the largest fiber bundle that connects the two hemispheres in the brain-for subjects that suffer from developmental brain disorders. For detecting the abnormal tissue in the heart, a graph-cut mathematical optimization model with a cost function that accounts for the object's visual appearance and shape is used to segment the the inner cavity. The model is further integrated with a geometric model (i.e., a fast marching...

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Volumetric Analysis of Regional Variability in the Cerebellum of Children with Dyslexia

Cited by 23 publications

References 40 publications

White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study

White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study

Functional Plasticity in Childhood Brain Disorders: When, What, How, and Whom to Assess

Developing advanced mathematical models for detecting abnormalities in 2D/3D medical structures.

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