Current Morse Scholars
The emphasis of my research is on characterizing the microstructural organization of the human brain using Magnetic Resonance Imaging. More specifically, I am focused on using diffusion-weighted MRI (dMRI) to study microstructural connectivity patterns in brain regions.
I am currently working on the optimization and implementation of dMRI methods that go beyond diffusion tensor imaging (DTI) such us neurite orientation dispersion and density imaging. I am also working on the development of novel approaches for the analysis of dMRI quantitative measures as well as on the development of novel tools for quality assurance of dMRI data acquisition.
Such techniques are to be used for investigating the brain of typically developing individuals as well as the brain of individuals suffering from neurological conditions such as traumatic brain injury and developmental disorders like autism.
Home Departments: Medical Physics
Major Professor: Andy Alexander, PhD
Disciplines that I pull from in my research include: Physics, Mathematics, Computer Science, Neuroscience, Engineering.
Articles That Influenced My Research:
Alexander AL, Lee JE, Lazar M, Field AS. (2007). Diffusion tensor imaging of the brain. Neurotherapeutics: The Journal of the American Society for Experimental NeuroTherapeutics, 4(3), 316–329. https://doi.org/10.1016/j.nurt.2007.05.011. PMCID: PMC2041910
Alexander DC. (2008). A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features. Magnetic Resonance in Medicine, 60(2), 439–448. https://doi.org/10.1002/mrm.21646
Dean DC, Lange N, Travers BG, Prigge MB, Matsunami N, Kellett KA, … Alexander AL. (2017). Multivariate characterization of white matter heterogeneity in autism spectrum disorder. NeuroImage. Clinical, 14, 54–66. https://doi.org/10.1016/j.nicl.2017.01.002. PMCID: PMC5257193
Jelescu IO, Veraart J, Fieremans E, Novikov DS. (2016). Degeneracy in model parameter estimation for multi-compartmental diffusion in neuronal tissue: Degeneracy in Model Parameter Estimation of Diffusion in Neural Tissue. NMR in Biomedicine, 29(1), 33–47. https://doi.org/10.1002/nbm.3450. PMCID: PMC4920129
Jones DK, Cercignani M. (2010). Twenty-five pitfalls in the analysis of diffusion MRI data. NMR in Biomedicine, 23(7), 803–820. https://doi.org/10.1002/nbm.1543
Jones DK, Knösche TR, Turner R. (2013). White matter integrity, fiber count, and other fallacies: The do’s and don’ts of diffusion MRI. NeuroImage, 73, 239–254. https://doi.org/10.1016/j.neuroimage.2012.06.081
Kiselev VG. (2010). The Cumulant Expansion: An Overarching Mathematical Framework For Understanding Diffusion NMR. In D. K. Jones, PhD (Ed.), Diffusion MRI (pp. 152–168). Oxford University Press. https://doi.org/10.1093/med/9780195369779.003.0010
Lipton ML, Kim N, Park YK, Hulkower MB, Gardin TM, Shifteh K, … Branch CA. (2012). Robust detection of traumatic axonal injury in individual mild traumatic brain injury patients: Intersubject variation, change over time and bidirectional changes in anisotropy. Brain Imaging and Behavior, 6(2), 329–342. https://doi.org/10.1007/s11682-012-9175-2
Malyarenko D, Galbán CJ, Londy FJ, Meyer CR, Johnson TD, Rehemtulla A, … Chenevert TL. (2013). Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom. Journal of Magnetic Resonance Imaging: JMRI, 37(5), 1238–1246. https://doi.org/10.1002/jmri.23825. PMCID: PMC3548033
Tofts PS, Lloyd D, Clark CA, Barker GJ, Parker GJ, McConville P, … Pope JM. (2000). Test liquids for quantitative MRI measurements of self-diffusion coefficient in vivo. Magnetic Resonance in Medicine, 43(3), 368–374.
Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage, 61(4), 1000–1016. https://doi.org/10.1016/j.neuroimage.2012.03.072
My research focuses on intrinsic and extrinsic factors that contribute to language learning in young children with developmental disabilities, including children with Down syndrome, fragile X syndrome, and autism spectrum disorders. Specifically, my research investigates the relationships between parent and child factors during naturalistic parent-child interactions. By including both mothers and fathers, we can better understand similarities and differences in parent behaviors, which may shed light on ways in which parents may need different supports during parent-coached interventions. In addition, I am particularly interested in how we can gain additional insight into interactions and child language development through the use of multiple methods, including standardized measures, behavioral coding, parent report, physiological measures of parent-child synchrony, and Language ENvironment Analysis (LENA).
Home Departments: Communication Sciences and Disorders
Major Professor: Audra Sterling, PhD
Disciplines that I pull from in my research include: Communication Sciences and Disorders, Human Development and Family Studies, Developmental Psychology, Linguistics
Articles That Influenced My Research:
Adamson LB, Bakeman R, Deckner DF, Romski M. (2009). Joint engagement and the emergence of language in children with autism and Down syndrome. Journal of Autism and Developmental Disorders, 39, 84–96. PMCID: PMC2640949
Brady N, Warren SF, Fleming K, Keller J, Sterling A. (2014). Effect of sustained maternal responsivity on later vocabulary development in children with fragile X syndrome. Journal of Speech, Language, and Hearing Research, 57, 212–226. PMCID: PMC3864610
de Falco S, Esposito G, Venuti P, Bornstein MH. (2010). Mothers and fathers at play with their children with Down syndrome: Influence on child exploratory and symbolic activity. Journal of Applied Research in Intellectual Disabilities, 23, 597–605. PMCID: PMC3530190
Sterling A, Warren SF. (2014). Maternal responsivity in mothers of young children with Down syndrome. Developmental Neurorehabilitation, 17, 306–317. PMCID: PMC4113603
My methodological research interests lies in the area of experimental design and longitudinal data, including under situations with biased sampling schemes, such as outcome dependent sampling. Current areas of application include communication sciences and language and speech development. In past, I have worked on non-parametric regression methods and on the analysis of brain imaging data. Personal webpage: https://jmmaronge.github.io
Home Departments: Statistics/Biostatistics and Medical Informatics
Major Professor: Paul J. Rathouz, PhD
Disciplines that I pull from in my research include: Statistics, Biostatistics, Epidemiology, Communication Sciences.
Articles That Influenced My Research:
Hustad, KD, Allison, KM, Sakash, A, McFadd E, Broman AT, Rathouz PJ. (2017). Longitudinal development of communication in children with cerebral palsy between 24 and 53 months: predicting speech outcomes. Developmental Rehabilitation, 20(6), 323-330. PMCID: PMC5409890
Rathouz, PJ, Gao, L. (2008). Generalized linear models with unspecified reference distribution. Biostatistics, 10(2), 205-218. PMCID: PMC2733172
Schildcrout, JS, Rathouz, PJ. (2010). Longitudinal studies of binary response data following case-control and stratified case-control sampling: design and analysis. Biometrics, 66, 365-373. PMCID: PMC3051172
My research focuses broadly on sensorimotor integration in children with Autism Spectrum Disorder (ASD). I am particularly interested in the neural mechanisms of motor modulation in response to sensory feedback from the environment and how these mechanisms may be different in individuals with ASD compared to those with typical development or other developmental disorders. In order to further characterize these neural mechanisms of sensorimotor integration, I am to use behavioral measures of sensory and motor function along with innovative structural and functional neuroimaging techniques.
Home Department: Neuroscience (Neuroscience Training Program)
Major Professors: Brittany Travers, PhD and Brendon Nacewicz, MD, PhD
Disciplines that I pull from in my research include: Neuroscience, Psychology, Chemistry, Biochemistry, and Computer Science.
Articles that influenced my research:
Cascio, C. J., Woynaroski, T., Baranek, G. T., & Wallace, M. T. (2016). Toward an interdisciplinary approach to understanding sensory function in autism spectrum disorder: Toward an interdisciplinary approach. Autism Research, 9(9), 920–925. doi:10.1002/aur.1612
Nacewicz, B. M., Angelos, L., Dalton, K. M., Fischer, R., Anderle, M. J., Alexander, A. L., & Davidson, R. J. (2012). Reliable non-invasive measurement of human neurochemistry using proton spectroscopy with an anatomically defined amygdala-specific voxel. NeuroImage, 59(3), 2548–2559. doi:10.1016/j.neuroimage.2011.08.090
Robertson, C. E., & Baron-Cohen, S. (2017). Sensory perception in autism. Nature Reviews Neuroscience, 18(11), 671–684. doi:10.1038/nrn.2017.112
Travers, B. G., Bigler, E. D., Tromp, D. P. M., Adluru, N., Destiche, D., Samsin, D., Froehlich, A., Prigge, M. D. B., Duffield, T. C., Lange, N., Alexander, A., Lainhart, J. (2015). Brainstem White Matter Predicts Individual Differences in Manual Motor Difficulties and Symptom Severity in Autism. Journal of Autism and Developmental Disorders, 45(9), 3030–3040. doi:10.1007/s10803-015-2467-9
Morse Scholars Reunion 2018
