@article {1786,
	title = {The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density},
	journal = {Magnetic Resonance in Medicine},
	volume = {79},
	year = {2018},
	pages = {2738{\textendash}2744},
	keywords = {Brain, cortex, Diffusion MRI, fiber orientation distribution, myeloarchitecture, parcellation},
	issn = {1522-2594},
	doi = {10.1002/mrm.26917},
	url = {http://dx.doi.org/10.1002/mrm.26917},
	author = {Fernando Calamante and Ben Jeurissen and Robert Elton Smith and Tournier, Jacques-Donald and Connelly, Alan}
}
@article {1547,
	title = {Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data.},
	journal = {NeuroImage},
	volume = {86},
	year = {2014},
	month = {2014 Feb 1},
	pages = {67-80},
	abstract = {There is accumulating evidence that at current acquisition resolutions for diffusion-weighted (DW) MRI, the vast majority of white matter voxels contains "crossing fibers", referring to complex fiber configurations in which multiple and distinctly differently oriented fiber populations exist. Spherical deconvolution based techniques are appealing to characterize this DW intra-voxel signal heterogeneity, as they provide a balanced trade-off between constraints on the required hardware performance and acquisition time on the one hand, and the reliability of the reconstructed fiber orientation distribution function (fODF) on the other hand. Recent findings, however, suggest that an inaccurate calibration of the response function (RF), which represents the DW signal profile of a single fiber orientation, can lead to the detection of spurious fODF peaks which, in turn, can have a severe impact on tractography results. Currently, the computation of this RF is either model-based or estimated from selected voxels that have a fractional anisotropy (FA) value above a predefined threshold. For both approaches, however, there are user-defined settings that affect the RF and, consequently, fODF estimation and tractography. Moreover, these settings still rely on the second-rank diffusion tensor, which may not be the appropriate model, especially at high b-values. In this work, we circumvent these issues for RF calibration by excluding "crossing fibers" voxels in a recursive framework. Our approach is evaluated with simulations and applied to in vivo and ex vivo data sets with different acquisition settings. The results demonstrate that with the proposed method the RF can be calibrated in a robust and automated way without needing to define ad-hoc FA threshold settings. Our framework facilitates the use of spherical deconvolution approaches in data sets in which it is not straightforward to define RF settings a priori.},
	keywords = {Adult, Algorithms, Brain, Calibration, diffusion tensor imaging, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Male, Nerve Fibers, Myelinated, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2013.07.067},
	author = {Chantal M W Tax and Ben Jeurissen and Vos, Sjoerd B. and Viergever, Max A. and Alexander Leemans}
}
@article {1546,
	title = {Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism.},
	journal = {NeuroImage},
	volume = {90},
	year = {2014},
	month = {2014 Apr 15},
	pages = {280-9},
	abstract = {BACKGROUND: The brain-derived neurotrophic factor (BDNF) val66met polymorphism is associated with altered activity dependent secretion of BDNF and a variable influence on brain morphology and cognition. Although a met-dose effect is generally assumed, to date the paucity of met-homozygotes have limited our understanding of the role of the met-allele on brain structure.

METHODS: To investigate this phenomenon, we recruited sixty normal healthy subjects, twenty in each genotypic group (val/val, val/met and met/met). Global and local morphology were assessed using voxel based morphometry and surface reconstruction methods. White matter organisation was also investigated using tract-based spatial statistics and constrained spherical deconvolution tractography.

RESULTS: Morphological analysis revealed an "inverted-U" shaped profile of cortical changes, with val/met heterozygotes most different relative to the two homozygous groups. These results were evident at a global and local level as well as in tractography analysis of white matter fibre bundles.

CONCLUSION: In contrast to our expectations, we found no evidence of a linear met-dose effect on brain structure, rather our results support the view that the heterozygotic BDNF val66met genotype is associated with cortical morphology that is more distinct from the BDNF val66met homozygotes. These results may prove significant in furthering our understanding of the role of the BDNF met-allele in disorders such as Alzheimer{\textquoteright}s disease and depression.},
	keywords = {Adolescent, Adult, Alleles, Brain, Brain-Derived Neurotrophic Factor, diffusion tensor imaging, Female, Genotype, Heterozygote, Homozygote, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Polymorphism, Single Nucleotide, Young Adult},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2013.12.050},
	author = {Forde, Natalie J and Ronan, Lisa and Suckling, John and Scanlon, Cathy and Neary, Simon and Holleran, Laurena and Alexander Leemans and Tait, Roger and Rua, Catarina and Fletcher, Paul C and Ben Jeurissen and Dodds, Chris M and Miller, Sam R and Bullmore, Edward T and Colm McDonald and Nathan, Pradeep J and Dara M. Cannon}
}
