کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6024486 1580887 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimating individual contribution from group-based structural correlation networks
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Estimating individual contribution from group-based structural correlation networks
چکیده انگلیسی


- Two novel methods to estimate individual differences in structural correlations.
- Proposed methods were applied to datasets from patient and control populations.
- Efficacy of proposed methods was demonstrated using behavioral correlations.
- Stability of proposed methods was established using three different datasets.

Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n = 100) consisting of individuals with fragile X syndrome (FXS; n = 50) and age-matched typically developing individuals (TD; n = 50). We tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 120, 15 October 2015, Pages 274-284
نویسندگان
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