In a project with investigators from the Nervous System Development and Plasticity Section, NICHD, and the Program on Pediatric Imaging and Tissue Sciences (PPITS), NICHD we study dynamic regulation of myelin by the surrounding glial cells and show that it is dependent on the level of activity present in an axon. We elucidated the biological mechanisms by which astrocytes regulate this process. Our role is to use a theoretical framework to predict how the changes in myelin thickness, as well as the increase in the nodal width, affects the propagation of the signals along a myelinated axon, and to experimentally measure conduction speeds using a data analysis framework we implemented. The theoretical and experimental results were in a very good agreement. A manuscript describing these methods and ultimately the mechanism of the dynamic myelin regulation is to be submitted to Science in September of 2016. We also developed different models of myelin plasticity, or generally, delay plasticity. We study the consequences of such adaptive time delays for two main cases: one where the plasticity is activity dependent and another where the plasticity depends on the temporal mismatch between presynaptic and postsynaptic action potentials. In the former case, we studied the effect of activity dependent adaptive time delays on the stability of the system of coupled oscillators, with implications to the stability of the oscillations and synchrony in the brain. Our work suggests that the myelin plasticity may be necessary to maintain normal oscillatory activity in the developing and adult brain. Newly proposed models of delay plasticity based on temporal mismatch were studied in the context of spiking neural networks. We show how the stability of the synchronized state in the network relies on having adaptive delay. This work was presented at the Annual Meeting of the Society for Neuroscience in Chicago, IL, in October of 2015. In a project with investigators of the Section on Behavioral Neurogenetics in the Intramural Research Program at NICHD, we study patterns of gene expression in developing zebrafish using supervised and unsupervised machine learning methods, and develop a framework for automated annotation of the zebrafish brain neuroanatomy. This work will allow the production of maps with increasingly fine-grained segmentation of distinct neuronal cell types, and will be presented at the Annual Meeting of the Society for Neuroscience in San Diego, CA, in November of 2016. In a project with investigators in the Program on Pediatric Imaging and Tissue Sciences (PPITS), NICHD and the section on Critical Brain Dynamics in the Intramural Research Program at NIMH, we conduct an experimental study aiming to answer questions about the possibility of detecting neural activity directly using MRI on NMR measurements. A new experimental test bed has been designed that enables simultaneous calcium fluorescence optical imaging and MR acquisition. A manuscript describing this work has been published in NMR in Biomedicine in December of 2015.

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4
Fiscal Year
2016
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Computer Research and Technology
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Gupta, Tripti; Marquart, Gregory D; Horstick, Eric J et al. (2018) Morphometric analysis and neuroanatomical mapping of the zebrafish brain. Methods 150:49-62
Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J (2017) Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments. SIAM J Imaging Sci 10:1511-1548
Bai, Ruiliang; Klaus, Andreas; Bellay, Tim et al. (2015) Simultaneous calcium fluorescence imaging and MR of ex vivo organotypic cortical cultures: a new test bed for functional MRI. NMR Biomed 28:1726-38
Salem, Ghadi H; Dennis, John U; Krynitsky, Jonathan et al. (2015) SCORHE: a novel and practical approach to video monitoring of laboratory mice housed in vivarium cage racks. Behav Res Methods 47:235-50
Pajevic, S; Basser, P J; Fields, R D (2014) Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience 276:135-47
Pajevic, Sinisa; Basser, Peter J (2013) An optimum principle predicts the distribution of axon diameters in normal white matter. PLoS One 8:e54095