Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment

Snook, Lindsay; Plewes, Chris; Beaulieu, Christian

doi:10.1016/j.neuroimage.2006.07.021

Cited by 210 publications

(192 citation statements)

References 36 publications

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“…Advantages and disadvantages of both procedures have been mentioned throughout this review, and there has been much debate about the use of voxel-based or ROI-based approaches (Good et al, 2001). Various studies have compared both methods (Furutani et al, 2005;Giuliani, Calhoun, Pearlson, Francis, & Buchanan, 2005;Kanaan et al, 2006;Kubicki et al, 2002;Snook et al, 2007;Suzuki et al, 2005;Tapp et al, 2006;Testa et al, 2004), finding, on the whole, similar results for both methods but some advantages for voxel-based over ROI-based analysis. Although VBM can overlook small differences (Saxe, Moran, Scholz, & Gabrieli, 2006), the ROI approach limits the chances of coming up with new, unexpected findings (Friston & Henson, 2006) making it difficult to expand and generalize the body of knowledge.…”

Section: Methodological Concerns and Recommendationsmentioning

confidence: 96%

“…In contrast, there is no such heterogeneity of methods in WM studies because -with the exception of only two studies that used a TOI approach, which suffers from the same shortcomings as the ROI approach (Furutani, Harada, Minato, Morita, & Nishitani, 2005;Kanaan et al, 2006;Snook, Plewes, & Beaulieu, 2007;Tapp et al, 2006) -the remaining studies follow a standardized method implemented in FSL to perform the TBSS approach on diffusion-derived measures. However, it is important take into account that the use of data acquired from different scanners (1.5T or 3.0T) and using different parameters for the acquisition of the images (see tables 1 and 2 for details of the different studies reviewed here) can produce important differences in the quality of the images across studies and also influence variability in the results.…”

Section: Methodological Concerns and Recommendationsmentioning

confidence: 99%

“…Although VBM can overlook small differences (Saxe, Moran, Scholz, & Gabrieli, 2006), the ROI approach limits the chances of coming up with new, unexpected findings (Friston & Henson, 2006) making it difficult to expand and generalize the body of knowledge. Ultimately, the two techniques are complementary and cannot be used separately (Snook et al, 2007). This is important because even when there is a prior hypothesis about particular regions, it is useful to get information about the whole brain since regions are unlikely to be working in isolation, making it crucial to perform a whole brain analysis in the first place.…”

Section: Methodological Concerns and Recommendationsmentioning

confidence: 99%

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The neuroanatomy of bilingualism: how to turn a hazy view into the full picture

García-Pentón

García

Costello

et al. 2015

Language, Cognition and Neuroscience

141

108

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Abstract:The neuroanatomical bases of bilingualism have recently received intensive attention.However, it is still a matter of debate how the brain structure changes due to bilingual experience since current findings are highly variable. The aim of this review is to examine these structural studies from a methodological perspective and to discuss two major methodological problems that could give rise to this variability. The first problem is sample selection, an issue directly related to the heterogeneous nature of bilingualism. The second problem is the inconsistency in the methods used for the analysis of brain imaging data. This review reveals that although structural changes related to bilingualism have been reported in regions comprising language/cognitive control and language processing, these results are not yet sufficiently numerous or consistent to allow important generalizations to be reached. Consequently, current evidence offers ambiguous support for neural models of bilingualism. This shortcoming in the field is exacerbated by critical methodological differences between studies that only further complicate the matter. We conclude by identifying issues that should be taken into consideration so that studies are more comparable and results are easier to aggregate and interpret. We also point out future directions that would allow for progress in the field.

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Section: Methodological Concerns and Recommendationsmentioning

confidence: 96%

Section: Methodological Concerns and Recommendationsmentioning

confidence: 99%

Section: Methodological Concerns and Recommendationsmentioning

confidence: 99%

See 1 more Smart Citation

The neuroanatomy of bilingualism: how to turn a hazy view into the full picture

García-Pentón

García

Costello

et al. 2015

Language, Cognition and Neuroscience

141

108

View full text Add to dashboard Cite

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“…These parameters where then applied to the FA and diffusivity images, resulting in accurate alignment of the CST in all subjects. For voxelwise analysis, a smoothing kernel of 8mm was chosen according to recommendations by Snook et al (2007). However, smoothing was omitted for ROI and slicewise analysis to avoid pollution by signal from neighbouring non-white matter voxels.…”

Section: Dti Data Acquisitionmentioning

confidence: 99%

White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study

et al. 2009

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With the advent of diffusion tensor imaging (DTI), the study of plastic changes in white matter architecture due to long-term practice has attracted increasing interest. Professional musicians provide an ideal model for investigating white matter plasticity because of their early onset of extensive auditory and sensorimotor training. We performed fiber tractography and subsequent voxelwise analysis, region of interest (ROI) analysis, and detailed slicewise analysis of diffusion parameters in the corticospinal tract (CST) on 26 professional musicians and a control group of 13 participants. All analyses resulted in significantly lower fractional anisotropy (FA) values in both the left and the right CST in the musician group. Furthermore, a right-greater-than-left asymmetry of FA was observed regardless of group. In the musician group, diffusivity was negatively correlated with the onset of musical training in childhood. A subsequent median split into an early and a late onset musician group (median=7 years) revealed increased diffusivity in the CST of the early onset group as compared to both the late onset group and the controls. In conclusion, these DTI-based findings might indicate plastic changes in white matter architecture of the CST in professional musicians. Our results imply that training-induced changes in diffusion characteristics of the axonal membrane may lead to increased radial diffusivity as reflected in decreased FA values. AbstractWith the advent of diffusion tensor imaging (DTI), the study of plastic changes in white matter architecture due to long-term practice has attracted increasing interest. Professional musicians provide an ideal model for investigating white matter plasticity because of their early onset of extensive auditory and sensorimotor training. We performed fiber tractography and subsequent voxelwise analysis, region of interest (ROI) analysis, and detailed slicewise analysis of diffusion parameters in the CST on 26 professional musicians and a control group of 13 participants. All analyses resulted in significantly lower FA values in both the left and the right CST in the musician group. Furthermore, a right-greater-than-left asymmetry of FA was observed regardless of group.In the musician group, diffusivity was negatively correlated with the onset of musical training in childhood. A subsequent median split into an early and a late onset musician group (median = 7 years) revealed increased diffusivity in the CST of the early onset group as compared with both the late onset group and the controls. In conclusion, these DTI-based findings might indicate plastic changes in white matter architecture of the CST in professional musicians. Our results imply that training-induced changes in diffusion characteristics of the axonal membrane may lead to increased radial diffusivity as reflected in decreased FA values.2

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“…DTI metrics have identified significant effects of adult aging that are now well described in regional white matter (for review, . Typically, with advancing age anisotropy declines and diffusivity increases more in anterior than posterior brain regions, whether measured with a region-ofinterest approach (Head et al, 2004;Madden et al, 2004;O'Sullivan et al, 2001;Pfefferbaum et al, 2005;Pfefferbaum et al, 2006;Pfefferbaum and Sullivan, 2003;Pfefferbaum et al, 2000;Salat et al, 2005;Sullivan et al, 2001), voxel-based analysis (Grieve et al, 2007;Kochunov et al, 2007;Snook et al, 2007), or quantitative fiber tracking (Pfefferbaum et al, 2007;Sullivan et al, , 2008. As observed postmortem, a predilection of age-related loss occurs for thin, unmyelinated fibers, which are in greatest abundance in the frontal lobes (Aboitiz et al, 1996;Bartzokis, 2004).…”

Section: Introductionmentioning

confidence: 99%

Diffusion tensor imaging of deep gray matter brain structures: Effects of age and iron concentration

Pfefferbaum

Adalsteinsson

Rohlfing

et al. 2010

Neurobiology of Aging

168

169

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Diffusion tensor imaging (DTI) of the brain has become a mainstay in the study of normal aging of white matter, and only recently has attention turned to the use of DTI to examine aging effects in gray matter structures. Of the many changes in the brain that occur with advancing age is increased presence of iron, notable in selective deep gray matter structures. In vivo detection and measurement of iron deposition is possible with magnetic resonance imaging (MRI) because of iron's effect on signal intensity. In the process of a DTI study, a series of diffusion-weighted images (DWI) is collected, and while not normally considered as a major dependent variable in research studies, they are used clinically and they reveal striking conspicuity of the globus pallidus and putamen caused by signal loss in these structures, presumably due to iron accumulation with age. These iron deposits may in turn influence DTI metrics, especially of deep gray matter structures. The combined imaging modality approach has not been previously used in the study of normal aging. The present study used legacy DTI data collected in 10 younger (22-37 years) and 10 older (65-79 years) men and women at 3.0 T and fast spin-echo (FSE) data collected at 1.5 T and 3.0 T to derive an estimate of the fielddependent relaxation rate increase (the "FDRI estimate") in the putamen, caudate nucleus, globus pallidus, thalamus, and a frontal white matter sample comparison region. The effect of age on the diffusion measures in the deep gray matter structures was distinctly different from that reported in white matter. In contrast to lower anisotropy and higher diffusivity typical in white matter of older relative to younger adults observed with DTI, both anisotropy and diffusivity were higher in the older than younger group in the caudate nucleus and putamen; the thalamus showed little effect of age on anisotropy or diffusivity. Signal intensity measured with DWI was lower in the putamen of elderly than young adults, whereas the opposite was observed for the white matter region and thalamus. As a retrospective study based on legacy data, the FDRI estimates were based on FSE sequences, which underestimated the classical FDRI index of brain iron. Nonetheless, the differential effects of age on DTI metrics in subcortical gray matter structures compared with white matter tracts appears to be related, at least in part, to local iron content, which in the elderly of the present study was prominent

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Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment

Cited by 210 publications

References 36 publications

The neuroanatomy of bilingualism: how to turn a hazy view into the full picture

The neuroanatomy of bilingualism: how to turn a hazy view into the full picture

White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study

Diffusion tensor imaging of deep gray matter brain structures: Effects of age and iron concentration

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