Hypertension and Correlation to Cerebrovascular Change: A Brief Overview
Ayman El-Baz, Jasjit S. Suri in Cardiovascular Imaging and Image Analysis, 2018
Arterial spin labeling (ASL) MRI uses pulse inversion to differentiate tissues moving into the imaging field from other tissues, which are subtracted (requires acquisition of two images) or uses background suppression single-shot ASL [42], [43]. ASL-MRI can be used to quantify blood flow using changes in magnetization of blood water to tissues. Functional MRI (fMRI) measures changes in blood flow and can be used to identify active areas in the brain. For many years, fMRI has been used to investigate correlations between hypertension and cognitive and related functions (e.g., working memory) [44]. fMRI is useful in the study of cerebral function and arteriopathies (e.g., Lewis bodies, cerebral amyloid angiopathy) to Alzheimer's, vascular dementia, etc. [45], [46]. Blood oxygen level dependent (BOLD) contrast imaging is used in fMRI to observe the active areas in the brain and other organs by measurement changes in oxyhemoglobin and deoxyhemoglobin (oxygen changes) [35]. Figure 16.8 presents a sample of fMRI data.
Consequences of Excessive Chronic Alcohol Consumption on Brain Structure and Function
John Brick in Handbook of the Medical Consequences of Alcohol and Drug Abuse, 2012
The techniques described previously—MRI, DTI, and MRS—all provide static representations of the brain. In contrast, fMRI describes the brain at work by measuring brain blood oxygen level as a proxy for the neural activity demanded by specific motor, sensory, or cognitive processes (Logothetis and Pfeuffer, 2004). fMRI locates changes in levels of oxygen in blood vessels, the hemodynamic response, occurring in response to experimental manipulations by measuring the difference between oxygenation time-locked to a specific cognitive or motor operation and oxygenation occurring during a rest period or neutral activity. The regions of the brain showing greatest difference between active and neutral conditions are believed to be those most involved in performing the operation under investigation (Hennig et al., 2003; Toma and Nakai, 2002).
Pharmacological MRI as a Molecular Imaging Technique
Michel M. J. Modo, Jeff W. M. Bulte in Molecular and Cellular MR Imaging, 2007
fMRI has turned out to be a great tool for investigation of brain function. However, its hemodynamic basis most accurately reflects neuronal activity at the level of changes in metabolism due to alterations in blood flow/volume and oxygen consumption. However, phMRI lacks detailed information on molecular events at the neuronal level. Under favorable circumstances, the indirect hemodynamic response can be utilized to reflect specific neurotransmitter function by using pharmacological ligands that selectively agonize or inhibit specific neurotransmitter systems. We have presented data above, specific for the dopamine system, demonstrating that there are numerous molecular events (such as dopamine cell loss, receptor upregulation and modulation) amenable to analysis using phMRI techniques. Clearly this is a field in its infancy, and future experiments can be expected to help ascertain the possibilities and limitations of this methodology. The existing literature shows that even now, although it still relies on hemodynamic measurements, phMRI can be a powerful molecular imaging tool for examination of brain function at the neurotransmitter level.
Sparse graphical models via calibrated concave convex procedure with application to fMRI data
Published in Journal of Applied Statistics, 2020
Sungtaek Son, Cheolwoo Park, Yongho Jeon
Graphical models are widely used in statistics, machine learning and probability theory, and applied to various fields such as medical research, computational biology, computer vision, and semantic analysis. The main application of our work is fMRI data where the construction of network in human brain is of great interest to explain human behavior. In fMRI studies, brain activities are often indirectly measured through the variations in blood flow throughout different regions of the brain by means of blood oxygen-level dependent (BOLD) contrast. One can construct a graphical model based on the strength of association in BOLD signals among different regions of brain. There is a rich set of literature on the application of graphical models to fMRI data. For example, see Bullmore and Bassett [3] for a thorough review of the issues on this topic. Also, more recent developments can be found in the following work and references therein. Lin et al. [12] propose a graphical model based on spectral matrix and Bayesian averaging network to analyze story comprehension task data. Ng et al. [16] jointly estimate intra-subject and group-level connectivity using a sparse Gaussian graphical model. Pircalabelu et al. [17] develop a neighborhood selection method for graphical model selection in a high-dimensional setting and apply it to resting state of fMRI data. Li and Solea [11] take a functional data analysis approach to nonparametrically build a graphical model in the reproducing kernel Hilbert space.
Altered brain activity and functional connectivity in migraine without aura during and outside attack
Published in Neurological Research, 2023
Luping Zhang, Wenjing Yu, Zhengxiang Zhang, Maosheng Xu, Feng Cui, Wenwen Song, Zhijian Cao
Functional magnetic resonance imaging (fMRI) is the most commonly used method for assessing brain activity. It indirectly measures neural activity by measuring the local changes in blood oxygenation. The amplitude low-frequency fluctuations (ALFF) derived from the resting-state fMRI signals can reflect the regional spontaneous neural activity [8,9]. Functional connectivity (FC) is a method to characterize the temporal neurophysiological activities interactions between brain regions that are spatially remote [10]. Thus, in this study, we used the resting-state functional magnetic resonance imaging (rs-fMRI) method to detect cortical excitability changes and abnormal FC in MWoA-DA and MWoA-DI groups to explore the pathophysiological mechanism of migraine. Additionally, we assessed the relationships between neuroimaging findings and clinical parameters to further explore the relationship between these parameters and the role of these changes in the migraine pathophysiology.
Comparison of Functional Connectivity during Visual-Motor Illusion, Observation, and Motor Execution
Published in Journal of Motor Behavior, 2022
Katsuya Sakai, Junpei Tanabe, Keisuke Goto, Ken Kumai, Yumi Ikeda
The present study has some limitations. First, we did not measure all the ROIs due to the small number of fNIRS probes, and their spatial resolution was wider than other devices (i.e., fMRI). These limitations can be solved by simultaneously including fMRI measurements in future studies. Second, in the OB group, subjects held their right hand in front of the monitor while watching the video image. We had to investigate subject own upper limb had to be considered for inclusion under the monitor using anatomically incongruent video. We speculated that future studies could add an anatomically incongruent video condition to clearly contrast with the IL group. Third, the assessment of degree of kinesthetic illusion and a sense of body ownership was one statement without control statements. Therefore, this assessment method increased the risk of the results being confounded by demand characteristics and suggestion. Finally, this study has a small number of subjects, we will increase the number of subjects in future studies.
Related Knowledge Centers
- Brain Mapping
- Diffusion Mri
- Resting State Fmri
- Spinal Cord
- Hemodynamics
- Brain
- Blood-Oxygen-Level-Dependent Imaging
- Neuron
- Haemodynamic Response
- Arterial Spin Labelling