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Zhou Y, Zhang H, Zhang L, Cao X, Yang R, Feng Q, Yap PT, Shen D. Functional MRI registration with tissue-specific patch-based functional correlation tensors. Hum Brain Mapp 2018; 39:2303-2316. [PMID: 29504193 DOI: 10.1002/hbm.24021] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2017] [Accepted: 02/17/2018] [Indexed: 02/01/2023] Open
Abstract
Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods.
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Affiliation(s)
- Yujia Zhou
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina
| | - Lichi Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, China.,Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina
| | - Xiaohuan Cao
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina.,School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Ru Yang
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina
| | - Qianjin Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Pew-Thian Yap
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina.,Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
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152
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On Myelinated Axon Plasticity and Neuronal Circuit Formation and Function. J Neurosci 2017; 37:10023-10034. [PMID: 29046438 DOI: 10.1523/jneurosci.3185-16.2017] [Citation(s) in RCA: 128] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Revised: 08/31/2017] [Indexed: 12/28/2022] Open
Abstract
Studies of activity-driven nervous system plasticity have primarily focused on the gray matter. However, MRI-based imaging studies have shown that white matter, primarily composed of myelinated axons, can also be dynamically regulated by activity of the healthy brain. Myelination in the CNS is an ongoing process that starts around birth and continues throughout life. Myelin in the CNS is generated by oligodendrocytes and recent evidence has shown that many aspects of oligodendrocyte development and myelination can be modulated by extrinsic signals including neuronal activity. Because modulation of myelin can, in turn, affect several aspects of conduction, the concept has emerged that activity-regulated myelination represents an important form of nervous system plasticity. Here we review our increasing understanding of how neuronal activity regulates oligodendrocytes and myelinated axons in vivo, with a focus on the timing of relevant processes. We highlight the observations that neuronal activity can rapidly tune axonal diameter, promote re-entry of oligodendrocyte progenitor cells into the cell cycle, or drive their direct differentiation into oligodendrocytes. We suggest that activity-regulated myelin formation and remodeling that significantly change axonal conduction properties are most likely to occur over timescales of days to weeks. Finally, we propose that precise fine-tuning of conduction along already-myelinated axons may also be mediated by alterations to the axon itself. We conclude that future studies need to analyze activity-driven adaptations to both axons and their myelin sheaths to fully understand how myelinated axon plasticity contributes to neuronal circuit formation and function.
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