GSP Analysis of Brain Imaging Data from Athletes with History of Multiple Concussions

Sihag, Saurabh; Naze, Sébastien; Taghdiri, Foad; Tartaglia, Maria Carmela; Kozloski, James

doi:10.1109/globalsip45357.2019.8969487

Cited by 2 publications

(2 citation statements)

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“…Therefore, two features were associated with every brain area for each subject leading to 132 GSP features (66 each from high and low graph frequency analysis) per subject. The group differences between the GSP features in this sample have been reported in our previous study 27 .…”

Section: Discussionsupporting

confidence: 81%

“…The components of the BOLD signal extracted from task-based functional magnetic resonance imaging (fMRI) that are less aligned with, or 'liberal' with respect to, the underlying white matter architecture have been linked with cognitive flexibility 24 . Furthermore, GSP tools have been used to find discriminating features from resting state fMRI and diffusion MRI (dMRI) in autism spectrum disorder 26 and traumatic brain injury 27 . GSP tools have also been used to evaluate the extent of structure-function decoupling for different brain regions 28 .…”

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confidence: 99%

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Functional brain activity constrained by structural connectivity reveals cohort-specific features for serum neurofilament light chain

et al. 2022

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Background Neuro-axonal brain damage releases neurofilament light chain (NfL) proteins, which enter the blood. Serum NfL has recently emerged as a promising biomarker for grading axonal damage, monitoring treatment responses, and prognosis in neurological diseases. Importantly, serum NfL levels also increase with aging, and the interpretation of serum NfL levels in neurological diseases is incomplete due to lack of a reliable model for age-related variation in serum NfL levels in healthy subjects. Methods Graph signal processing (GSP) provides analytical tools, such as graph Fourier transform (GFT), to produce measures from functional dynamics of brain activity constrained by white matter anatomy. Here, we leveraged a set of features using GFT that quantified the coupling between blood oxygen level dependent signals and structural connectome to investigate their associations with serum NfL levels collected from healthy subjects and former athletes with history of concussions. Results Here we show that GSP feature from isthmus cingulate in the right hemisphere (r-iCg) is strongly linked with serum NfL in healthy controls. In contrast, GSP features from temporal lobe and lingual areas in the left hemisphere and posterior cingulate in the right hemisphere are the most associated with serum NfL in former athletes. Additional analysis reveals that the GSP feature from r-iCg is associated with behavioral and structural measures that predict aggressive behavior in healthy controls and former athletes. Conclusions Our results suggest that GSP-derived brain features may be included in models of baseline variance when evaluating NfL as a biomarker of neurological diseases and studying their impact on personality traits.

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Section: Discussionsupporting

confidence: 81%

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confidence: 99%