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.

Free Water Volume Fraction: An Imaging Biomarker to Characterize Moderate-to-Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is a major clinical and public health problem with few therapeutic interventions successfully translated to the clinic. Identifying imaging-based biomarkers characterizing injury severity and predicting long-term functional and cognitive outcomes in TBI patients is crucial for treatment. TBI results in white matter (WM) injuries, which can be detected using diffusion tensor imaging (DTI).

Analysis of Consistency in Structural and Functional Connectivity of Human Brain.

Analysis of structural and functional connectivity of brain has become a fundamental approach in neuroscientific research. Despite several studies reporting consistent similarities as well as differences for structural and resting state (rs) functional connectomes, a comparative investigation of connectomic consistency between the two modalities is still lacking. Nonetheless, connectomic analysis comprising both connectivity types necessitate extra attention as consistency of connectivity differs across modalities, possibly affecting the interpretation of the results.

Connectomic consistency: a systematic stability analysis of structural and functional connectivity.

Objective: Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated using different modalities such as diffusion MRI to capture structural organization of the brain or functional MRI to elaborate brain's functional organization. Understanding links between structural and functional organizations is crucial in explaining how observed behavior emerges from the underlying neurobiological mechanisms.

Graph Matching Based Connectomic Biomarker with Learning for Brain Disorders.

Advances in neuroimaging techniques such as diffusion MRI and functional MRI enabled evaluation of the brain as an information processing network that is called connectome. Connectomic analysis has led to numerous findings on the organization of the brain its pathological changes with diseases, providing imaging-based biomarkers that help in diagnosis and prognosis. A large majority of connectomic biomarkers benefit either from graph-theoretical measures that evaluate brain's network structure, or use standard metrics such as Euclidean distance or Pearson's correlation to show between-connectomes relations.

System-level matching of structural and functional connectomes in the human brain.

The brain can be considered as an information processing network, where complex behavior manifests as a result of communication between large-scale functional systems such as visual and default mode networks. As the communication between brain regions occurs through underlying anatomical pathways, it is important to define a "traffic pattern" that properly describes how the regions exchange information. Empirically, the choice of the traffic pattern can be made based on how well the functional connectivity between regions matches the structural pathways equipped with that traffic pattern.