Exploring the Brain Lateralization in ADHD Based on Variability of Resting-State fMRI Signal

2018 ◽  
Vol 25 (2) ◽  
pp. 258-264
Author(s):  
Hongliang Zou ◽  
Jian Yang
Keyword(s):  
Resting State ◽  
Inferior Frontal Gyrus ◽  
Resting State Fmri ◽  
Cerebellar Hemisphere ◽  
Brain Lateralization ◽  
Female Patients ◽  
Fmri Signal ◽  
Male Patients ◽  
The Difference ◽  
The Brain

Objective: In this study, we investigate the brain lateralization in ADHD patients. Furthermore, we also explore the difference between male and female patients, and the difference among distinct ADHD subtypes, that is, ADHD–inattentive (ADHD-IA) and ADHD–combined (ADHD-C). Method: We employed the standard deviation to quantify the variability of resting-state functional magnetic resonance imaging (fMRI) signal and measure the lateralization index (LI). Results: ADHD patients showed significantly increased rightward lateralization in the inferior frontal gyrus (opercular), precuneus, and paracentral lobule, and decreased rightward lateralization in the insula. Compared with male patients, female patients showed significantly rightward lateralization in the putamen and lobule VII of cerebellar hemisphere. ADHD-C patients exhibited increased rightward lateralization in the inferior frontal gyrus (opercular), and decreased rightward lateralization in the inferior temporal gyrus, as compared with ADHD-IA. The LI was also found to be related to inattentive and hyper/impulsive scores. Conclusion: These key findings may aid in understanding the pathology of ADHD.

scholarly journals Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Lv Han ◽  
Liu Zhaohui ◽  
Yan Fei ◽  
Li Ting ◽  
Zhao Pengfei ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Changes ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Pulsatile Tinnitus ◽  
Spontaneous Brain Activity ◽  
Fmri Study ◽  
The Brain

Numerous investigations studying the brain functional activity of the tinnitus patients have indicated that neurological changes are important findings of this kind of disease. However, the pulsatile tinnitus (PT) patients were excluded in previous studies because of the totally different mechanisms of the two subtype tinnitus. The aim of this study is to investigate whether altered baseline brain activity presents in patients with PT using resting-state functional magnetic resonance imaging (rs-fMRI) technique. The present study used unilateral PT patients (n=42) and age-, sex-, and education-matched normal control subjects (n=42) to investigate the changes in structural and amplitude of low-frequency (ALFF) of the brain. Also, we analyzed the relationships between these changes with clinical data of the PT patients. Compared with normal controls, PT patients did not show any structural changes. PT patients showed significant increased ALFF in the bilateral precuneus, and bilateral inferior frontal gyrus (IFG) and decreased ALFF in multiple occipital areas. Moreover, the increased THI score and PT duration was correlated with increased ALFF in precuneus and bilateral IFG. The abnormalities of spontaneous brain activity reflected by ALFF measurements in the absence of structural changes may provide insights into the neural reorganization in PT patients.

Functional MRI

2018 ◽  
Keyword(s):  
Functional Mri ◽  
Resting State ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Fmri Signal ◽  
The Brain

Functional MRI with BOLD (Blood Oxygen Level Dependent) imaging is one of the commonly used modalities for studying brain function in neuroscience. The underlying source of the BOLD fMRI signal is the variation in oxyhemoglobin to deoxyhemoglobin ratio at the site of neuronal activity in the brain. fMRI is mostly used to map out the location and intensity of brain activity that correlate with mental activities. In recent years, a new approach to fMRI was developed that is called resting-state fMRI. The fMRI signal from this method does not require the brain to perform any goal-directed task; it is acquired with the subject at rest. It was discovered that there are low-frequency fluctuations in the fMRI signal in the brain at rest. The signals originate from spatially distinct functionally related brain regions but exhibit coherent time-synchronous fluctuations. Several of the networks have been identified and are called resting-state networks. These networks represent the strength of the functional connectivity between distinct functionally related brain regions and have been used as imaging markers of various neurological and psychiatric diseases. Resting-state fMRI is also ideally suited for functional brain imaging in disorders of consciousness and in subjects under anesthesia. This book provides a review of the basic principles of fMRI (signal sources, acquisition methods, and data analysis) and its potential clinical applications.

Functional brain lateralization in schizophrenia based on the variability of resting-state fMRI signal

2018 ◽  
Vol 86 ◽  
pp. 114-121 ◽  
Author(s):  
Wanqing Xie ◽  
Chung-Kang Peng ◽  
Chu-Chung Huang ◽  
Ching-Po Lin ◽  
Shih-Jen Tsai ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Brain Lateralization ◽  
Functional Brain ◽  
Fmri Signal

Basic Principles of Functional MRI

2018 ◽  
pp. 20-29
Author(s):  
Cheuk Ying Tang
Keyword(s):  
Functional Mri ◽  
Resting State ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Basic Principles ◽  
Fmri Signal ◽  
The Brain

Blood oxygen level dependent (BOLD) MRI, also called functional MRI (fMRI), is one of the most widely used modalities for studying brain function. The underlying source of the fMRI signal is blood flow and the oxygenation state of hemoglobin. fMRI is mostly used to map out the location and intensity of brain activity that correlate with mental activities. In recent years, a new approach to fMRI has been developed that is called resting-state fMRI. The fMRI signal from this method does not require the brain to perform a goal-directed task; it is acquired with the subject at rest. It was discovered that there are low-frequency fluctuations in the fMRI signal in the brain at rest. These signals come from spatially distinct brain regions but exhibit coherent, time-synchronous fluctuations. Several of the networks have been identified and are called resting-state networks. The networks represent the strength of the functional connectivity between distinct brain regions and have been used as imaging biomarkers for various neurological and psychiatric diseases. Resting-state fMRI is also ideally suited for functional brain imaging in disorders of consciousness and in subjects under anesthesia. In this chapter, we provide an introductory review of the basic principles of fMRI: signal sources, acquisition methods, and data analysis.

scholarly journals Wrist and finger motor representations embedded in the cerebral and cerebellar resting-state activation

2021 ◽  
Author(s):  
Toshiki Kusano ◽  
Hiroki Kurashige ◽  
Isao Nambu ◽  
Yoshiya Moriguchi ◽  
Takashi Hanakawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Body Part ◽  
Resting State Fmri ◽  
Body Parts ◽  
Finger Movements ◽  
Multiple Components ◽  
Brain Activity Pattern ◽  
Motor Representations ◽  
The Brain

AbstractSeveral functional magnetic resonance imaging (fMRI) studies have demonstrated that resting-state brain activity consists of multiple components, each corresponding to the spatial pattern of brain activity induced by performing a task. Especially in a movement task, such components have been shown to correspond to the brain activity pattern of the relevant anatomical region, meaning that the voxels of pattern that are cooperatively activated while using a body part (e.g., foot, hand, and tongue) also behave cooperatively in the resting state. However, it is unclear whether the components involved in resting-state brain activity correspond to those induced by the movement of discrete body parts. To address this issue, in the present study, we focused on wrist and finger movements in the hand, and a cross-decoding technique trained to discriminate between the multi-voxel patterns induced by wrist and finger movement was applied to the resting-state fMRI. We found that the multi-voxel pattern in resting-state brain activity corresponds to either wrist or finger movements in the motor-related areas of each hemisphere of the cerebrum and cerebellum. These results suggest that resting-state brain activity in the motor-related areas consists of the components corresponding to the elementary movements of individual body parts. Therefore, the resting-state brain activity possibly has a finer structure than considered previously.

Peculiarities in Interaction of Independent Components of Resting-State fMRI Signal in Patients with Mild Depressions

2017 ◽  
Vol 163 (4) ◽  
pp. 497-499 ◽  
Author(s):  
M. E. Mel’nikov ◽  
D. D. Bezmaternykh ◽  
E. D. Petrovskii ◽  
L. I. Kozlova ◽  
M. B. Shtark ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Independent Components ◽  
Fmri Signal

scholarly journals Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Data Exchange ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

scholarly journals Vitamin E Level In Friedreich’s Ataxic Phenotype Patients In Four Major Hospitals In Baghdad

2019 ◽  
Vol 13 (1) ◽  
pp. 132-136
Author(s):  
Ahmed Hasan Ahmed
Keyword(s):  
Vitamin E ◽  
Teaching Hospital ◽  
Friedreich Ataxia ◽  
Control Group ◽  
Female Patients ◽  
Radical Trapping ◽  
Male Patients ◽  
The Difference ◽  
Classic Form ◽  
Age Range

Background: Friedreich ataxia (FRDA) is the most common form of inherited ataxia, comprising one-half of all hereditary ataxias with a carrier rate between 1 in 60 to 1 in 90 and with a disease prevalence of 1 per 29,000. It can occur in two forms the classic form or in association with a vitamin E dependent ataxia. The precise role of Vitamin E in the nervous system is unknown; An Oxidative attack is suspected to play a role in Ataxia with Vitamin E deficiency, as well as in Friedreich ataxia. Vitamin E is the major free-radical-trapping antioxidant. Objective: Theobjectives of the study is to asses vitamin E level in patients with Friedreichs ataxia phenotype in Iraqi patients. Type of the study:Cross-sectional study. Method: This study was conducted at the neuroscience hospital and Baghdad teaching hospital during the period from the 1st of November 2013 through November 2014. Forty patients with friedreich's ataxia attended in neuroscience hospital and Baghdad teaching hospital during this period; there was12 male, 20 female patients and their age range between (4-50) years. Results: Regarding the level of vitamin E in patients in the present study, The study revealed that mean level of vitamin E for Friedreich ataxia patients was (10.92 μg/ml) ranging from (8-18 μg/ml),while in the control group the mean was (28.06μg/ml) ranging from (22-36μg/ml), the difference in mean level was found to be statistically significant (p=0.0001.) Thirty percents of (FRDA) patients was (8-9.9μg/ml), while half of patients (50%) were within (10-11.9 μg/ml),and low percentage (15 %)of patients were within (12-13.9 μg/ml ). The rest (5%) were had vitamin E level equal or more than 14 μg/ml. these finding revealed that majority of Friedreich ataxia patients were found with low level of vitamin E (32 patients(80%)), and low percentage with normal level (8 patients(20%.)) Patients with Friedreich ataxia were found to have a comparable level 10.47±1.79(8.4-13.5),11.48±2.61(9.4-18) and 10.66±1.26(9-12.5) for those with less than 10 years, 10-19 years , equal or more than 20 years of age respectively (p=0.382), while it was found to have a significantly decreasing level with advance in the age for the control group, 30.57±4.61(24.5-36), 27.46±3.16(23.7-33.5), 25.50±3.03 (22.9-29) for those less than 10 years, 10-19 years, 20 years or more respectively (p=0.006.) Vitamin E level in relation to Gender showed that Friedriech ataxia male patients had significantly higher vitamin E level compared to females [12.05±2.66 (9.0-18.0) compared to 10.17±1.07 (8.4-12.0)] (p=0.003), while relation to gender in the control group was not of significant value statistically [27.08±2.90 (22.9-30.0) for male compared to 29.04±4.97 (23.7-36) for females] , p=0.136. Conclusion: In the light of the results of the present study, the following conclusions were made:  The level of vitamin E in friedreichs ataxic phenotype patients was subnormal than normal range representing 80% of the sample selected for the test.  The level of vitamin E in male patients of freidriechs ataxic phenotype patients was higher than female patients.  

scholarly journals Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

2021 ◽  
Author(s):  
Takashi Nakano ◽  
Masahiro Takamura ◽  
Haruki Nishimura ◽  
Maro Machizawa ◽  
Naho Ichikawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Fmri Data ◽  
Independent Test ◽  
The Individual ◽  
The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

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