Alappatt, J. A. | Search bioRxiv

bioRxiv2021

Connectomic Assessment of Injury Burden and Longitudinal Structural Network Alterations in Moderate-to-severe Traumatic Brain Injury

Traumatic brain injury (TBI) is a major public health problem. Caused by external mechanical forces, a major characteristic of TBI is the shearing of axons across the white matter, which causes structural connectivity disruptions between brain regions. This diffuse injury leads to cognitive deficits, frequently requiring rehabilitation. Heterogeneity is another characteristic of TBI as severity and cognitive sequelae of the disease have a wide variation across patients, posing a big challenge for treatment. Thus, measures assessing network-wide structural connectivity disruptions in TBI are necessary to quantify injury burden of individuals, which would help in achieving personalized treatment, patient monitoring, and rehabilitation planning. Despite TBI being a disconnectivity syndrome, connectomic assessment of structural disconnectivity has been very scarce. In this study, we propose a novel connectomic measure that we call network anomaly score (NAS) to capture the integrity of structural connectivity in TBI patients by leveraging two major characteristics of the disease: diffuseness of axonal injury and heterogeneity of the disease. Over a longitudinal cohort of moderate-to-severe TBI patients, we demonstrate that structural network topology of patients are more heterogeneous and are significantly different than that of healthy controls at 3 months post-injury, where dissimilarity further increases up to 12 months. We also show that NAS captures injury burden as quantified by post-traumatic amnesia and that alterations in the structural brain network is not related to cognitive recovery. Finally we compare NAS to major graph theory measures used in TBI literature and demonstrate the superiority of NAS in characterizing the disease.

neuroscience↗

bioRxiv2019

Connectomic consistency: a systematic stability analysisof structural and functional connectivity

Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated for different modalities such as using diffusion MRI to capture structural organization of the brain or using functional MRI to elaborate brains functional organization. Understanding links between structural and functional organizations is crucial in explaining how observed behavior emerges from the underlying neurobiological mechanisms. Many studies have investigated how these two organizations relate to each other; however, we still lack a proper understanding on how much variation should be expected on the two modalities, both between people cross-sectionally and within a single person longitudinally. Notably, connectomes of both modalities were shown to have significant differences depending on how they are generated. In this study, for both modalities, we systematically analyzed consistency of connectomes, that is the similarity between connectomes in terms of individual connections between brain regions or in terms of overall network topology. We present a comprehensive study of consistency in structural and resting-state functional connectomes both for a single subject examined longitudinally and across a large cohort of subjects cross-sectionally. We compared connectomes generated by different tracking algorithms, parcellations, edge weighting schemes, and edge pruning techniques. We evaluated consistency both at the levels of individual edges using correlation and at the level of network topology via graph matching accuracy. We also examined consistency of connectomes that are generated using most commonly applied communication schemes. Our results demonstrate varying degrees of consistency for the two modalities, with structural connectomes showing higher consistency than functional connectomes. Moreover, we observed a wide variation in consistency depending on how connectomes are generated. Our study sets a reference point for consistency of connectome types, which is especially important for structure-function coupling studies in evaluating mismatches between modalities.

neuroscience↗