A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood

Aubert-Broche, Bérengère; Fonov, Vladimir S.; García-Lorenzo, Daniel; Mouiha, Abderazzak; Guizard, Nicolas; Coupé, Pierrick; Eskildsen, Simon Fristed; Collins, D. Louis

doi:10.1016/j.neuroimage.2013.05.065

Cited by 158 publications

(161 citation statements)

References 21 publications

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“…This region displayed the highest gray matter volume in late childhood and early adolescence, and showed consistent decreases in gray matter volume (1.2-1.7% per year) across the teen years before decelerating in the early twenties. This finding is consistent with findings from other longitudinal samples, which have shown decreasing gray matter volume in the PFC between late childhood and early adulthood [5,29]. Comparing all three ROIs at a group level, these data lend support to a structural mismatch in developmental timing between the amygdala and the PFC, but do not provide evidence of a clear structural mismatch between the NAcc and the PFC during adolescence, since both regions continue to show volume change into early adulthood.…”

Section: Discussionsupporting

confidence: 93%

The Developmental Mismatch in Structural Brain Maturation during Adolescence

Mills

Goddings²,

Clasen³

et al. 2014

Dev Neurosci

322

231

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Regions of the human brain develop at different rates across the first two decades of life, with some maturing before others. It has been hypothesized that a mismatch in the timing of maturation between subcortical regions (involved in affect and reward processing) and prefrontal regions (involved in cognitive control) underlies the increase in risk-taking and sensation-seeking behaviors observed during adolescence. Most support for this ‘dual systems' hypothesis relies on cross-sectional data, and it is not known whether this pattern is present at an individual level. The current study utilizes longitudinal structural magnetic resonance imaging (MRI) data to describe the developmental trajectories of regions associated with risk-taking and sensation-seeking behaviors, namely, the amygdala, nucleus accumbens (NAcc) and prefrontal cortex (PFC). Structural trajectories of gray matter volumes were analyzed using FreeSurfer in 33 participants aged 7-30 years, each of whom had at least three high-quality MRI scans spanning three developmental periods: late childhood, adolescence and early adulthood (total 152 scans). The majority of individuals in our sample showed relatively earlier maturation in the amygdala and/or NAcc compared to the PFC, providing evidence for a mismatch in the timing of structural maturation between these structures. We then related individual developmental trajectories to retrospectively assessed self-reported risk-taking and sensation-seeking behaviors during adolescence in a subsample of 24 participants. Analysis of this smaller sample failed to find a relationship between the presence of a mismatch in brain maturation and risk-taking and sensation-seeking behaviors during adolescence. Taken together, it appears that the developmental mismatch in structural brain maturation is present in neurotypically developing individuals. This pattern of development did not directly relate to self-reported behaviors at an individual level in our sample, highlighting the need for prospective studies combining anatomical and behavioral measures.

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Section: Discussionsupporting

confidence: 93%

The Developmental Mismatch in Structural Brain Maturation during Adolescence

Mills

Goddings²,

Clasen³

et al. 2014

Dev Neurosci

322

231

View full text Add to dashboard Cite

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“…10 Evaluation of the normal control data demonstrates that females have higher thalamic volumes relative to brain size, also an important consideration for future studies, in which sex must be considered in brain volumetric analyses. We then demonstrate a marked difference in thalamic volume normalized by brain size, with both failure of ageexpected thalamic growth as well as loss of thalamic volumes.…”

Section: Results Longitudinal Analysis Longitudinal Measurementsmentioning

confidence: 99%

“…Comprehensive details of the longitudinal processing are described by Aubert-Broche et al 10 and summarized here.…”

mentioning

confidence: 99%

Onset of multiple sclerosis before adulthood leads to failure of age-expected brain growth

et al. 2014

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Objective: To determine the impact of pediatric-onset multiple sclerosis (MS) on age-expected brain growth.Methods: Whole brain and regional volumes of 36 patients with relapsing-remitting MS onset prior to 18 years of age were segmented in 185 longitudinal MRI scans (2-11 scans per participant, 3-month to 2-year scan intervals). MRI scans of 25 age-and sex-matched healthy normal controls (NC) were also acquired at baseline and 2 years later on the same scanner as the MS group. A total of 874 scans from 339 participants from the NIH-funded MRI study of normal brain development acquired at 2-year intervals were used as an age-expected healthy growth reference. All data were analyzed with an automatic image processing pipeline to estimate the volume of brain and brain substructures. Mixed-effect models were built using age, sex, and group as fixed effects.Results: Significant group and age interactions were found with the adjusted models fitting brain volumes and normalized thalamus volumes (p , 10 24 ). These findings indicate a failure of agenormative brain growth for the MS group, and an even greater failure of thalamic growth. In patients with MS, T2 lesion volume correlated with a greater reduction in age-expected thalamic volume. To exclude any scanner-related influence on our data, we confirmed no significant interaction of group in the adjusted models between the NC and NIH MRI Study of Normal Brain Development groups. Conclusions:Our results provide evidence that the onset of MS during childhood and adolescence limits age-expected primary brain growth and leads to subsequent brain atrophy, implicating an early onset of the neurodegenerative aspect of MS. Neurology ® 2014;83:2140-2146 GLOSSARY EDSS 5 Expanded Disability Status Scale; FOV 5 field of view; MS 5 multiple sclerosis; NC 5 normally developing controls; NIHPD 5 NIH MRI Study of Normal Brain Development; PDW 5 proton density-weighted; RF 5 radiofrequency; T1W 5 T1-weighted; T2W 5 T2-weighted; TE 5 echo time; TR 5 repetition time.In multiple sclerosis (MS), focal inflammatory white matter lesions are the most visible aspect of pathology but represent only one component of the disease. There is growing evidence that the disease is also characterized by a neurodegenerative component.1 In adult-onset MS, deep gray matter atrophy is measurable even within the first few years after the first attack. 2In cross-sectional analyses, patients with MS with disease onset prior to age 18 years have been shown to have reduced thalamic 3-5 and brain volumes 3,5,6 relative to age-and sexmatched healthy controls. As MS is a chronic progressive illness, and childhood and adolescence are key periods of brain growth, 7 longitudinal analysis is required to define the impact of MS disease on brain development, in order to determine whether these differences in brain volumes are due to failure of normal age-related brain growth or to progressive loss of volume, or both.In this study, we used longitudinal MRI data to compare the growth trajectory of the brain and ...

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“…Learning-induced plasticity might involve synaptic remodeling and changes in neuronal morphology (27,83), as well as non-neuronal processes such as angiogenesis and divisions of astrocytes and oligodendrocyte progenitor cells (84). Because the focus of the current study was on the thickness of the cortical mantle, further research should assess subcortical regions using methods developed to probe whole-brain gray matter (85) and white matter (86) changes.…”

Section: S C I E N C E a D V A N C E S | R E S E A R C H A R T I C L Ementioning

confidence: 99%

Structural plasticity of the social brain: Differential change after socio-affective and cognitive mental training

Valk¹,

Bernhardt²,

Trautwein³

et al. 2017

Preprint

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Although neuroscientific research has revealed experience-dependent brain changes across the life span in sensory, motor, and cognitive domains, plasticity relating to social capacities remains largely unknown. To investigate whether the targeted mental training of different cognitive and social skills can induce specific changes in brain morphology, we collected longitudinal magnetic resonance imaging (MRI) data throughout a 9-month mental training intervention from a large sample of adults between 20 and 55 years of age. By means of various daily mental exercises and weekly instructed group sessions, training protocols specifically addressed three functional domains: (i) mindfulness-based attention and interoception, (ii) socio-affective skills (compassion, dealing with difficult emotions, and prosocial motivation), and (iii) socio-cognitive skills (cognitive perspective-taking on self and others and metacognition). MRIbased cortical thickness analyses, contrasting the different training modules against each other, indicated spatially diverging changes in cortical morphology. Training of present-moment focused attention mostly led to increases in cortical thickness in prefrontal regions, socio-affective training induced plasticity in frontoinsular regions, and sociocognitive training included change in inferior frontal and lateral temporal cortices. Module-specific structural brain changes correlated with training-induced behavioral improvements in the same individuals in domain-specific measures of attention, compassion, and cognitive perspective-taking, respectively, and overlapped with task-relevant functional networks. Our longitudinal findings indicate structural plasticity in well-known socio-affective and socio-cognitive brain networks in healthy adults based on targeted short daily mental practices. These findings could promote the development of evidence-based mental training interventions in clinical, educational, and corporate settings aimed at cultivating social intelligence, prosocial motivation, and cooperation.

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A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood

Cited by 158 publications

References 21 publications

The Developmental Mismatch in Structural Brain Maturation during Adolescence

The Developmental Mismatch in Structural Brain Maturation during Adolescence

Onset of multiple sclerosis before adulthood leads to failure of age-expected brain growth

Structural plasticity of the social brain: Differential change after socio-affective and cognitive mental training

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