Leonard Edward White
Associate Professor in Neurology
One important goal of neuroscience is to understand the fundamental principles that shape the developing brain. To achieve this goal, it is necessary to characterize the interactions between sensorimotor behavior, self-organization, and genetically programmed mechanisms of brain development. This interplay between intrinsic and experience-dependent factors is most dynamic during early life, at a time of explosive increase in the numbers and complexity of neural connections. It is precisely this increase in neural capacity that makes possible the rich repertoire of behavior associated with functional maturity. My primary interest is to understand how sensorimotor experience in early life influences — for better or worse — the formation and maturation of functional neural circuits in the cerebral cortex. My collaborators and I believe that our studies are providing insight into the nature of normal brain development and the consequences of disrupting the partnership between intrinsic developmental mechanisms and early sensorimotor experience.
The Development of Direction Selectivity in Visual Cortex awarded by National Institutes of Health (Co Investigator). 1996 to 2011
A probabilistic concept of sensory cortical function awarded by National Institutes of Health (Co Investigator). 2003 to 2006
Local Circuits and Direction Selectivity in Visual Cortex awarded by National Institutes of Health (Research Associate). 1996 to 2002
Direction Selectivity And Horizontal Connections In Vi awarded by National Institutes of Health (Principal Investigator). 1998 to 1999
Direction Selectivity And Horizontal Connections In V1 awarded by National Institutes of Health (Principal Investigator). 1997 to 1999
White, L. E. “A neuroproteomic approach to understanding visual cortical development.” Neuroproteomics, 2009, pp. 215–37.
Adil, Syed M., et al. “A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging.” Neuroimage, vol. 237, Aug. 2021, p. 118135. Pubmed, doi:10.1016/j.neuroimage.2021.118135. Full Text
Wang, Nian, et al. “Cytoarchitecture of the mouse brain by high resolution diffusion magnetic resonance imaging.” Neuroimage, vol. 216, Aug. 2020, p. 116876. Pubmed, doi:10.1016/j.neuroimage.2020.116876. Full Text
Wang, Nian, et al. “Neurite orientation dispersion and density imaging of mouse brain microstructure.” Brain Struct Funct, vol. 224, no. 5, June 2019, pp. 1797–813. Pubmed, doi:10.1007/s00429-019-01877-x. Full Text
Coppola, David M., and Leonard E. White. “Forever young: Neoteny, neurogenesis and a critique of critical periods in olfaction.” J Bioenerg Biomembr, vol. 51, no. 1, Feb. 2019, pp. 53–63. Pubmed, doi:10.1007/s10863-018-9778-4. Full Text
Li, Jonathan Y., et al. “Quantitative DTI metrics in a canine model of Krabbe disease: comparisons versus age-matched controls across multiple ages.” Neuroradiol J, vol. 31, no. 2, Apr. 2018, pp. 168–76. Pubmed, doi:10.1177/1971400917733431. Full Text
Middleton, Dana M., et al. “Diffusion tensor imaging findings suggestive of white matter alterations in a canine model of mucopolysaccharidosis type I.” Neuroradiol J, vol. 31, no. 1, Feb. 2018, pp. 90–94. Pubmed, doi:10.1177/1971400917715792. Full Text
Middleton, Dana M., et al. “Quantitative diffusion tensor imaging analysis does not distinguish pediatric canines with mucopolysaccharidosis I from control canines.” Neuroradiol J, vol. 30, no. 5, Oct. 2017, pp. 454–60. Pubmed, doi:10.1177/1971400917718844. Full Text
Li, Jonathan Y., et al. “Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.” Neuroradiol J, vol. 30, no. 4, Aug. 2017, pp. 339–46. Pubmed, doi:10.1177/1971400917709629. Full Text
Taylor, Andrea B., et al. “Body and Brain: Anatomy of team-based learning in a preclinical science course.” American Journal of Physical Anthropology, vol. 156, WILEY-BLACKWELL, 2015, pp. 301–301.
Bucur, B., et al. “Age-related decreases in cerebral white matter integrity: Implications for episodic and semantic retrieval processes.” Journal of Cognitive Neuroscience, M I T PRESS, 2005, pp. 234–234.