Changes in regional cerebral glucose metabolism with healthy aging

231

179

The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T1-weighted magnetic resonance (MR) images of 19 rhesus macaque (Macaca mulatta) animals. Combined with the comprehensive cortical and sub-cortical label map of the NeuroMaps atlas, the INIA19 is equally suitable for studies requiring both spatial normalization and atlas label propagation. Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for skull stripping of new images. This article describes the construction of the template using freely available software tools, as well as the template itself, which is being made available to the scientific community ().

Section: Applicationsmentioning

confidence: 99%

“…These template images can be used for aligning the atlas with new images for the purpose of normalizing observed data into common coordinate system (Ashburner and Friston, 2000). In addition, regions of interest can be outlined in the template images and propagated from these to the observed data (Gee et al, 1993; Fedorov et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

Rohlfing

Kroenke

Sullivan

et al. 2012

231

179

“…An undeniable landmark in this area is the statistical parametric mapping (SPM) software package (Friston et al, 2010), which provides a human average template and tissue priors of white matter, gray matter, and cerebrospinal fluid, as well as methods for spatial normalization and segmentation. The construction of this human template set can be found elsewhere (Mazziotta et al, 1995a,b, 2001) and its main applications are functional MRI (fMRI) localization, voxel-based morphometry (Ashburner and Friston, 2000) SPM (Friston et al, 2010), among others. To enrich the deliverables of the template set, various discrete digitalizations with finer parcellation of gray (Tzourio-Mazoyer et al, 2002; Rasser et al, 2008) and white matter (Hua et al, 2008; Mori et al, 2008), as well as their probabilistic versions (Shattuck et al, 2008), have been proposed.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, mouse templates have been built by means of hierarchical, multi-resolution non-linear registration schemes in order to achieve the highest possible spatial correspondence between all images of the sample. This means that the maximum possible information about the variability of the sample is stored in the deformation fields (Ashburner and Friston, 2000; Bookstein, 2001; Mechelli et al, 2005). Provided that the conditions for the warps are accomplished – i.e., the transformation is a diffeomorphism or a regularized enough to guarantee that the Jacobian is positive at every point of the region of interest – the higher the spatial match of the registered images the finer the details of the average image.…”

Section: Introductionmentioning

confidence: 99%

001 058 002 059 003 060 004 061 005 062 006 063 007 064 008 065 009 066 010 067 011 068 012 069 013 070 014 071 015 072 016 073 017 074 018 075 019 076 020 077 021 078 022 079 023 080 024 081 025 082 026 083 027 084 028 085 029 086 030 087 031 088 032 089 033 090 034 091 035 092 036 093 037 094 038 095 039 096 040 097 041 098 042 099 043 100 044 101 045 102 046 103 047 104 048 105 049 106 050 107 051 108 052 109 053 110 054 111 055 112 056 113 057 114 NEUROINFORMATICS METHODS ARTICLE published: xx November

Valdés-Hernández

Sumiyoshi

Nonaka

et al. 2011

203

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

“…Studies using VBM (Ashburner and Friston, 2000) have successfully addressed these inter-individual differences of adult brain structure and have given some insights into the complex relation to behavior and cognitive processing (Eckert, 2011; Kanai and Rees, 2011). Irrespective of their potential to separate age-related change and inter-individual differences, there is still a lack of studies addressing between-subjects neuroanatomical variability in repeated measurement designs.…”

Section: Analysis Of Inter-individual Variability In Aging Brain Strumentioning

confidence: 99%

Models of the aging brain structure and individual decline

Ziegler¹

2012

The aging brain’s structural development constitutes a spatiotemporal process that is accessible by MR-based computational morphometry. Here we introduce basic concepts and analytical approaches to quantify age-related differences and changes in neuroanatomical images of the human brain. The presented models first address the estimation of age trajectories, then we consider inter-individual variations of structural decline, using a repeated measures design. We concentrate our overview on preprocessed neuroanatomical images of the human brain to facilitate practical applications to diverse voxel- and surface-based structural markers. Together these methods afford analysis of aging brain structure in relation to behavioral, health, or cognitive parameters.