Neuroimaging of Brain Networks and Function

Hengyi Rao, Danny Jiongjiong Wang, Yihong Yang, Yong He
2015 BioMed Research International  
The human brain consists of multiple interconnected large scale networks. Recent advances in structural and functional neuroimaging techniques have introduced new concepts and approaches to noninvasively assess brain networks, which has attracted enormous research interest. To examine human brain function, traditional neuroimaging research typically focuses on localizing neural responses to varying external stimuli or task demands. However, task-induced phasic neuronal responses account for
more » ... than 5% of the brain's energy budget, while the majority of the brain's energy is used for intrinsic spontaneous brain activities. Although the number of human brain imaging studies and the knowledge obtained from these studies are growing exponentially, there are many more unanswered questions regarding the structural organization and the function of brain networks. In this special issue, we have invited a few papers that studied structural and functional brain networks using various neuroimaging methods including resting-state fMRI, diffusion tensor imaging (DTI), arterial spin labeling (ASL) perfusion MRI, functional near-infrared spectroscopy (f NIRS), magnetoencephalogram (MEG), and imaging genetics. These studies involve healthy populations as well as multiple clinical populations, including patients with cirrhosis, mild cognitive impairment (MCI) and Alzheimer's disease (AD), attention deficit hyperactivity disorder (ADHD), and epilepsy. This specific issue includes several studies focusing on clinical populations. In one study by G. Zheng and colleagues, resting-state fMRI was used to examine functional connectivity changes in the progression of minimal hepatic encephalopathy and found continuously impaired intraand intermodular connectivity in patients with cirrhosis. In another study, Y.-Y. Wai and colleagues used tractbased spatial statistics of DTI to characterize white matter integrity in different subtypes of MCI, including amnestic MCI, dysexecutive MCI, AD, and healthy controls. They found that amnestic MCI and AD patients share significant white matter damage, whereas dysexecutive MCI patients appear to have a distinct pathogenesis. In the third study, A. dos Santos Siqueira and colleagues used graph theory and analyzed a resting-state fMRI data set from healthy children and ADHD patients in the ADHD-200 database. Distinct patterns of network dysfunction were evident for both inattentive and combined ADHD subtypes. However, the authors observed that the classification scores for discriminating between ADHD and healthy subjects were close to chance and that functional connectivity estimations were strongly dependent on the sample characteristics. In the final study, H. Zhu and colleagues used resting-state MEG to identify the epileptogenic and other abnormal regions in patients with left temporal lobe epilepsy (TLE) and provided further evidence supporting the notion that TLE is not a focal focus but a multifocus disease. A few other studies in this specific issue examined brain networks and function in normal population. In one study by H. Lei and colleagues, resting-state fMRI was integrated with genetics to examine the effect of genetic variation of the
doi:10.1155/2015/509141 pmid:25685794 pmcid:PMC4313066 fatcat:576dv5eoune6rdsqkqkb6sd764