Dataset Information

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals.

ABSTRACT: We describe and apply novel methodology for whole-brain analysis of resting state fMRI functional connectivity data, combining conventional multi-channel Pearson correlation with covariance analysis. Unlike correlation, covariance analysis preserves signal amplitude information, which feature of fMRI time series may carry physiological significance. Additionally, we demonstrate that dimensionality reduction of the fMRI data offers several computational advantages including projection onto a space of manageable dimension, enabling linear operations on functional connectivity measures and exclusion of variance unrelated to resting state network structure. We show that group-averaged, dimensionality reduced, covariance and correlation matrices are related, to reasonable approximation, by a single scalar factor. We apply this methodology to the analysis of a large, resting state fMRI data set acquired in a prospective, controlled study of mindfulness training and exercise in older, sedentary participants at risk for developing cognitive decline. Results show marginally significant effects of both mindfulness training and exercise in both covariance and correlation measures of functional connectivity.

SUBMITTER: Snyder AZ

PROVIDER: S-EPMC8971902 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals.

Snyder Abraham Z AZ Nishino Tomoyuki T Shimony Joshua S JS Lenze Eric J EJ Wetherell Julie Loebach JL Voegtle Michelle M Miller J Philip JP Yingling Michael D MD Marcus Daniel D Gurney Jenny J Rutlin Jerrel J Scott Drew D Eyler Lisa L Barch Deanna D

Frontiers in neuroscience 20220318

We describe and apply novel methodology for whole-brain analysis of resting state fMRI functional connectivity data, combining conventional multi-channel Pearson correlation with covariance analysis. Unlike correlation, covariance analysis preserves signal amplitude information, which feature of fMRI time series may carry physiological significance. Additionally, we demonstrate that dimensionality reduction of the fMRI data offers several computational advantages including projection onto a spac ...[more]

PMID: 35368291

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Project description:IntroductionPreoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood-oxygen-level-dependent (BOLD) analysis to identify brain language areas. Task-based fMRI studies the BOLD signal increase in brain areas during a language task to identify brain language areas, which requires patients' cooperation, whereas resting-state fMRI (rsfMRI) allows identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas. The aim of this study was to compare preoperative language mapping using rsfMRI and task fMRI to cortical mapping (CM) during awake craniotomies.MethodsFifty adult patients surgically treated for a brain lesion were enrolled. All patients had a presurgical language mapping with both task fMRI and rsfMRI. Identified language networks were compared to perioperative language mapping using electric cortical stimulation.ResultsResting-state fMRI was able to detect brain language areas during CM with a sensitivity of 100% compared to 65.6% with task fMRI. However, we were not able to perform a specificity analysis and compare task-based and rest fMRI with our perioperative setting in the current study. In second-order analysis, task fMRI imaging included main nodes of the SN and main areas involved in semantics were identified in rsfMRI.ConclusionResting-state fMRI for presurgical language mapping is easy to implement, allowing the identification of functional brain language network with a greater sensitivity than task-based fMRI, at the cost of some precautions and a lower specificity. Further study is required to compare both the sensitivity and the specificity of the two methods and to evaluate the clinical value of rsfMRI as an alternative tool for the presurgical identification of brain language areas.

Project description:The aim of this research was developed to provide a scientific basis for individualized prevention, clinical diagnosis, and corrective treatment of nicotine addiction. The objects were 214 cases in the smoke group and 43 cases in the control group. According to the Fagerstrom Nicotine Dependence Test (FTND), the smokers were divided into mild nicotine dependence group (FTND < 6 points, 138 cases) and nicotine severe dependence group (≥6 points, 76 cases). The brain structure in long-term smokers was evaluated by using magnetic resonance imaging (MRI). The nicotine dependence was further analyzed by grouping the included individuals, and some candidate genes related to nicotine addiction were screened by combining with bioinformatics analysis. The family research strategy was adopted to detect nicotine addiction susceptibility genes and their polymorphisms. The MRI imaging results showed that the bilateral thalamus, right parietal, and left lens gram-molecule volume (GMV) were negatively correlated with smoking index and smoking years in the smoking group. The GMV of the posterior cingulate cortex in the severe nicotine dependence group was lower than that of the control group, and the GMVs of bilateral thalamus and bilateral superior limbic gyrus in the mild nicotine dependence group were lower than those of the control group. The gene polymorphism detection showed that rs6275 was highly polymorphic in the target population and the frequency of rs6275-C allele was 53.26%. Therefore, the MRI imaging characteristics suggested that the affected brain regions of smokers and people with varying degrees of nicotine dependence were mainly concentrated in response-related pathways and the limbic system and had cumulative effects on the central nervous system. In addition, the M6275 polymorphism of DRD2 gene was associated with susceptibility to nicotine addiction in Chinese population, and the M6275-C allele had a protective effect on susceptibility to nicotine addiction and smoking initiation.

Project description:BackgroundPsychological distress and comorbid psychopathology contribute to exacerbation risk in patients with asthma. Thus, interventions designed to reduce stress and improve emotion regulation, such as Mindfulness-Based Stress Reduction (MBSR), may augment standard care. Few studies have addressed this question and a paucity of data exists to determine the ability of MBSR to impact clinical outcomes in asthma.MethodsThis randomized controlled trial investigated effects of MBSR training on asthma control and airway inflammation, in relation to psychological symptoms, in adults with asthma. Participants were randomized to an 8-week MBSR training (n = 35) or wait-list control group (n = 34). Clinically relevant asthma assessments, including Asthma Control Questionnaire and inflammatory biomarkers, were collected at baseline and six approximately-monthly follow-ups. Self-reported mindfulness, distress, depression, and anxiety symptoms were assessed at baseline, post-intervention, and study completion. Chronic stress level was determined at baseline only.ResultsAsthma control improved significantly in individuals randomized to MBSR, relative to wait-list controls (p = .01; effect size d = 0.76), which was maintained at 4mo post-intervention. 32% of MBSR participants achieved a clinically significant improvement, based on the ACQ6 Minimally Important Difference, relative to 12% of wait-list participants. Moreover, MBSR-related improvement in asthma control was associated with a reduction in distress (p = .043) and the intervention was most efficacious for those with the highest baseline depressive symptoms (p = .023). Importantly, MBSR also reduced levels of exhaled nitric oxide, a biomarker of airway inflammation, relative to wait-list controls (p < .05).ConclusionSupporting and extending extant evidence of mind-body relationships in asthma and the benefits of stress reduction for these patients, this is, to the best of our knowledge, the first RCT to demonstrate that training in MBSR improves clinically relevant asthma outcomes. MBSR may thus be a valuable addition to optimal asthma management, particularly for those with comorbid psychopathology.Clinical trial registrationNCT02157766.

Dataset Information

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals.

Publications

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals.

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