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Brain Insulin Action in the Control of Metabolism in Humans
Published in André Kleinridders, Physiological Consequences of Brain Insulin Action, 2023
Thanks to neuroimaging techniques, brain insulin action can be spatially localized by evaluating the brain’s response to cognitive demanding tasks such as, for example, the investigation of the role of insulin in memory or reward-related processes. Since the brain is active even in the absence of external cues, spontaneous BOLD fluctuations are located in all brain regions. Brain activity can therefore be evaluated under the so-called “resting-state” or “intrinsic condition”. To this end, subjects lie in the MRI scanner with their eyes open or closed without performing any task. Resting-state fMRI thus greatly enhances the translation of fMRI into clinical care (for review, see (59)).
Neuroimaging in concussion
Published in Brian Sindelar, Julian E. Bailes, Sports-Related Concussion, 2017
Matthew T. Walker, Monther Qandeel
Functional MRI (fMRI) is a noninvasive study that can assess regional brain activity while performing or not performing a specific task (resting state fMRI or task-based fMRI), which is achieved indirectly by imaging the regional differences in cerebral blood flow using blood oxygenation level dependent (BOLD) imaging. Under normal physiologic conditions, regional blood flow in the brain is tightly linked to oxygen and carbon dioxide. When a specific part of the brain cortex is activated, the increased metabolic need leads to increased extraction of oxygen from the local capillaries with an initial drop in oxyhemoglobin levels. After a short lag of 26 seconds, the regional blood flow increases providing a surplus of oxyhemoglobin and leading to deoxyhemoglobin washout. This physiologic response of decreased levels of deoxyhemoglobin is what is imaged in fMRI. Because deoxygenated hemoglobin is paramagnetic whereas oxygenated hemoglobin is not, the relative decrease in the deoxyhemoglobin in the activated cortex leads to proton dephasing by inducing local magnetic field inhomogeneities and a net minimal but measurable decrease in signal on a heavily T2* weighted sequence such as BOLD imaging.
Mapping the Injured Brain
Published in Yu Chen, Babak Kateb, Neurophotonics and Brain Mapping, 2017
Chandler Sours, Jiachen Zhuo, Rao P. Gullapalli
Functional MRI (fMRI) is a valuable tool as it can identify the deficits in neural networks associated with various cognitive processes. Specifically, fMRI provides an indirect measure of large-scale neural activation and is based on the MR signal differences between deoxygenated blood and oxygenated blood. When individual neurons that are recruited for a given task produce an axon potential, there is an increase in freshly oxygenated blood to the local tissue to keep up with the increased neuronal demand. This change in the ratio of deoxygenated blood to oxygenated blood in the activated region causes a change in the tissue signal as the local tissue changes from a predominantly paramagnetic state to diamagnetic state. It is this MR signal change that is measured in fMRI and is called the blood-oxygen-level-dependent (BOLD) signal (Figure 14.3a). Currently fMRI data are acquired in one of two ways using a task-based fMRI paradigm and a resting-state fMRI (rs-fMRI) paradigm (Figure 14.3b and c).
Altered resting-state cerebellar-cerebral functional connectivity in patients with end-stage renal disease
Published in Renal Failure, 2023
Jie Fang, Yingying Miao, Fan Zou, Yarui Liu, Jiangle Zuo, Xiangming Qi, Haibao Wang
Resting-state fMRI is a method that indirectly infers information about brain activity by measuring Blood-Oxygen-Level Dependent (BOLD) signal. The temporal correlations of BOLD signals in different brain regions can be used to reflect brain FC [30]. The abnormalities in resting-state fMRI connectivity reflect alterations in the interactions among different brain regions [31]. Considering that DMN, ECN, ALN, and SMN are abnormal in ESRD, and that cerebellar sub-regions can identify the cerebellar-cerebral DMN, ECN, ALN, and SMN, we hypothesized that the cerebellum-cerebral FC is abnormal and related to cognitive impairment in ESRD patients. Therefore, the present study aimed to explore whether the cerebellar-cerebral FC is altered in ESRD patients with cerebellar sub-regions as seeds using resting-state fMRI, and further investigate the relationship between the altered FC, neuropsychological function, and clinical parameters in patients with ESRD.
Global and regional connectivity analysis of resting-state function MRI brain images using graph theory in Parkinson’s disease
Published in International Journal of Neuroscience, 2021
Rutvi Prajapati, Isaac Arnold Emerson
This work aims to explore the global and local measures of functional connectivity of the brain using resting-state fMRI. The specific interest of this study is to find how these measures of connectivity would help in differentiating PD patients from healthy controls (HCs). The fMRI data were analyzed for the partial correlations between 160 cortical and sub-cortical regions. In this study, we constructed the brain network using graph theoretical approaches that provide a powerful way of quantifying the brain’s functional connectivity. Further, we determined the interface between the neuroscience of Parkinson’s disease and whole-brain network topology. On analyzing the functional connectivity of brain regions, we found significant variations between PD and HCs from a network perspective. The novelty of the present study extends in the notion of brain network using fMRI images for Parkinson’s disease. The identified brain regions in PD have a unique link between the functional connectivity, and there are dynamic functional relationships among those regions that can be represented by a network. The rest of the paper is organized as follows. Chapter 2 describes the materials and methods to represent the detailed framework where chapter 3 combines results from the individual stages of the framework. A comprehensive discussion about this study presents in chapter 4, and lastly, the outcome of this study is depicted in chapter 5.
Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity
Published in Gut Microbes, 2021
N. Kohn, J. Szopinska-Tokov, A. Llera Arenas, C.F. Beckmann, A. Arias-Vasquez, E Aarts
Participants were screened for compatibility with magnetic resonance imaging (MRI). MRI data were acquired using a 3 T MAGNETOM Prisma system, equipped with a 32-channel head coil. After three short task-related fMRI scans (see Papalini et al.), 9 min of resting state fMRI was acquired. 3D echo planar imaging (EPI) scans using a T2*weighted gradient echo multi-echo sequence (Poser, Versluis et al. 2006) were acquired (voxel size 3.5 × 3.5 × 3 mm isotropic, TR = 2070 ms, TE = 9 ms; 19.25 ms; 29.5 ms; 39.75 ms, FoV = 224 mm). The slab positioning and rotation (average angle of 14 degrees to AC axis) optimally covered both prefrontal and deep brain regions. Subjects were instructed to lie still with their eyes open and refrain from directed thought. A whole-brain high-resolution T1-weighted anatomical scan was acquired using a MPRAGE sequence (voxel size 1.0 × 1.0 × 1.0 isotropic, TR = 2300 ms, TE = 3.03 ms, 192 slices).