Variability in blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals reflects the moment-by-moment fluctuations in resting-state fMRI (rs-fMRI) activity within specific areas of the brain. Regional BOLD signal variability was recently proposed to serve an important functional role in the efficacy of neural systems because of its relationship to behavioural performance in aging and cognition studies. We previously showed that individuals who better cope with pain have greater fluctuations in interregional functional connectivity, but it is not known whether regional brain signal variability is a mechanism underlying pain coping. We tested the hypothesis that individual pain sensitivity and coping is reflected by regional fMRI BOLD signal variability within dynamic pain connectome-brain systems implicated in the pain experience. We acquired resting-state fMRI and assessed pain threshold, suprathreshold temporal summation of pain, and the impact of pain on cognition in 80 healthy right-handed individuals. We found that regional BOLD signal variability: (1) inversely correlated with an individual's temporal summation of pain within the ascending nociceptive pathway (primary and secondary somatosensory cortex), default mode network, and salience network; (2) was correlated with an individual's ability to cope with pain during a cognitive interference task within the periaqueductal gray, a key opiate-rich brainstem structure for descending pain modulation; and (3) provided information not captured from interregional functional connectivity. Therefore, regional BOLD variability represents a pain metric with potential implications for prediction of chronic pain resilience vs vulnerability.
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Front Digit Health
January 2025
Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, United States.
Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.
View Article and Find Full Text PDFJ Pain Res
January 2025
Department of General Surgery, The 955th Hospital of Chinese People's Liberation Army, Tibet, 854000, People's Republic of China.
Fracture surgeries are frequently accompanied by severe pain, necessitating efficacious pain management strategies to enhance postoperative recovery. Nerve block techniques, which are critical in mitigating pain, involve the targeted administration of local anesthetics to disrupt nerve signal transmission, thereby achieving significant analgesia. Traditionally, these techniques rely on anatomical landmarks and the clinician's expertise, which can introduce variability and potential risks.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
School of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang China.
The increasing adoption of wearable technologies highlights the potential of electroencephalogram (EEG) signals for biometric recognition. However, the intrinsic variability in cross-session EEG data presents substantial challenges in maintaining model stability and reliability. Moreover, the diversity within single-task protocols complicates achieving consistent and generalized model performance.
View Article and Find Full Text PDFOncol Res
January 2025
Department of Urology, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Clear cell renal carcinoma (ccRCC), the leading histological subtype of RCC, lacks any targeted therapy options. Although some studies have shown that early growth response factor 1 (EGR1) has a significant role in cancer development and progression, its role and underlying mechanisms in ccRCC remain poorly understood.
Methods: The Cancer Genome Atlas (TCGA) database was utilized to examine the expression of EGR1 in ccRCC.
Purpose: T1-weighted signal intensity ratios (SIR) comparing pancreas to spleen (SIRps) or muscle (SIRpm) can semiquantitatively assess T1 signal change associated with pancreatitis. However, there is no standardized methodology for generating these ratios. We set out to determine the impact of MRI sequence as well as region of interest (ROI) location, shape, and size on T1 SIR.
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