| Literature DB >> 35080703 |
Cui Ping Mao1, Hua Juan Yang2, Qiu Juan Zhang2, Quan Xin Yang2, Xiao Hui Li2.
Abstract
Dysfunction of the cingulo-frontal-parietal (CFP) cognitive attention network has been associated with the pathophysiology of chronic low back pain (cLBP). However, the direction of information processing within this network remains largely unknown. We aimed to study the effective connectivity among the CFP regions in 36 cLBP patients and 36 healthy controls by dynamic causal modeling (DCM). Both the resting-state and task-related (Multi-Source Interference Task, MSIT) functional magnetic resonance imaging (fMRI) data were collected and analyzed. The relationship between the effective connectivity of the CFP regions and clinical measures was also examined. Our results suggested that cLBP had significantly altered resting-state effective connectivity of the prefrontal cortex (PFC)-to-mid-cingulate cortex (MCC) (increased) and MCC-to-left superior parietal cortex (LPC) (decreased) pathways as compared with healthy controls. MSIT-related DCM suggested that the interference task could significantly increase the effective connectivity of the right superior parietal cortex (RPC)-to-PFC and RPC-to-MCC pathways in cLBP than that in healthy controls. The control task could significantly decrease the effective connectivity of the MCC-to-LPC and MCC-to-RPC pathways in cLBP than that in healthy controls. The endogenous connectivity of the PFC-to-RPC pathway in cLBP was significantly lower than that in healthy controls. No significant correlations were found between the effective connectivity within CFP networks and pain/depression scores in patients with cLBP. In summary, our findings suggested altered effective connectivity in multiple pathways within the CFP network in both resting-state and performing attention-demanding tasks in patients with cLBP, which extends our understanding of attention dysfunction in patients with cLBP.Entities:
Keywords: Attention; Chronic low back pain; Effective connectivity; Functional magnetic resonance imaging; Multi-source interference task
Mesh:
Year: 2022 PMID: 35080703 DOI: 10.1007/s11682-021-00623-4
Source DB: PubMed Journal: Brain Imaging Behav ISSN: 1931-7557 Impact factor: 3.224