How to extract high discriminative features that help classification from complex resting-state fMRI (rs-fMRI) data is the key to improving the accuracy of brain disease recognition such as schizophrenia. In this work, we use a weighted sparse model for brain network construction, and utilize the Kendall correlation coefficient (KCC) to extract the discriminative connectivity features for schizophrenia classification, which is conducted with the linear support vector machine. Experimental results based on the rs-fMRI of 57 schizophrenia patients and 64 healthy controls show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 81.82%) than other competing methods. Specifically, compared with the traditional network construction methods (Pearson’s correlation and sparse representation) and the commonly used feature selection methods (two-sample t-test and Least absolute shrinkage and selection operator (Lasso)), the algorithm proposed in this paper can more effectively extract the discriminative connectivity features between the schizophrenia patients and the healthy controls, and further improve the classification accuracy. At the same time, the discriminative connectivity features extracted in the work could be used as the potential clinical biomarkers to assist the identification of schizophrenia.
Amblyopia is a visual development deficit caused by abnormal visual experience in early life, mainly manifesting as defected visual acuity and binocular visual impairment, which is considered to reflect abnormal development of the brain rather than organic lesions of the eye. Previous studies have reported abnormal spontaneous brain activity in patients with amblyopia. However, the location of abnormal spontaneous activity in patients with amblyopia and the association between abnormal brain function activity and clinical deficits remain unclear. The purpose of this study is to analyze spontaneous brain functional activity abnormalities in patients with amblyopia and their associations with clinical defects using resting-state functional magnetic resonance imaging (fMRI) data. In this study, 31 patients with amblyopia and 31 healthy controls were enrolled for resting-state fMRI scanning. The results showed that spontaneous activity in the right angular gyrus, left posterior cerebellum, and left cingulate gyrus were significantly lower in patients with amblyopia than in controls, and spontaneous activity in the right middle temporal gyrus was significantly higher in patients with amblyopia. In addition, the spontaneous activity of the left cerebellum in patients with amblyopia was negatively associated with the best-corrected visual acuity of the amblyopic eye, and the spontaneous activity of the right middle temporal gyrus was positively associated with the stereoacuity. This study found that adult patients with amblyopia showed abnormal spontaneous activity in the angular gyrus, cerebellum, middle temporal gyrus, and cingulate gyrus. Furthermore, the functional abnormalities in the cerebellum and middle temporal gyrus may be associated with visual acuity defects and stereopsis deficiency in patients with amblyopia. These findings help explain the neural mechanism of amblyopia, thus promoting the improvement of the treatment strategy for amblyopia.
Myopia is a major problem of public health in China, and even in the world, and slowing down the progress of myopia has become a hot issue of concern. However, the effects of the current therapeutic and interventional modalities to myopia, including optical lenses, chemical drugs, and laser surgery, the effect of treatment and intervention is not very satisfactory, and these modalities may incur some side effects. This situation suggests that the pathogenic and regulatory mechanisms of myopia remain elusive, and the myopia treatments lack the accurate and effective targets to the etiology. A complete visual experience depends on the entire visual pathway from the retina to the visual cortex, in which any structural and functional defect can lead to visual abnormalities. In recent years, with the advances in the infrared spectroscopy and the magnetic resonance imaging technology, more and more evidence has shown that the progression of myopia is related to the visual cortex. Improving the functional connectivity and blood prefusion between different regions of the visual cortex may impede myopia profession. In-depth understanding of the interaction between myopia and the visual cortex is helpful to search for accurate and effective myopia treatment targets and novel intervention strategies.
The emergence of real-time functional magnetic resonance imaging (rt-fMRI) has provided foundations for neurofeedback based on brain hemodynamics and has given the new opportunity and challenge to cognitive neuroscience research. Along with the study of advanced brain neural mechanisms, the regulation goal of rt-fMRI neurofeedback develops from the early specific brain region activity to the brain network connectivity more accordant with the brain functional activities, and the study of the latter may be a trend in the area. Firstly, this paper introduces basic principle and development of rt-fMRI neurofeedback. Then, it specifically discusses the current research status of brain connectivity neurofeedback technology, including research approaches, experimental methods, conclusions, and so on. Finally, it discusses the problems in this field in the future development.
Migraine is the most common primary headache clinically, with high disability rate and heavy burden. Functional MRI (fMRI) plays a significant role in the study of migraine. This article reviews the main advances of migraine without aura (MwoA) based on resting-state fMRI in recent years, including the exploration of the mechanism of fMRI in the occurrence and development of MwoA in terms of regional functional activities and functional network connections, as well as the research progress of the potential clinical application of fMRI in aiding diagnosis and assessing treatment effect for MwoA. At last, this article summarizes the current distresses and prospects of fMRI research on MwoA.
We investigated the baseline brain activity level in patients with major depressive disorder (MDD) by amplitude of low-frequency fluctuation (ALFF) based on resting-state functional MRI (fMRI). We examined 13 patients in the MDD group and 14 healthy volunteers in the control group by resting-state fMRI on GE Signa 3.0T. We calculated and compared the ALFF values of the two groups. In the MDD group, ALFF values in the right medial prefrontal were higher than those in control group, with statistically significant differences (P<0.001). ALFF values in the left parietal in the MDD group were lower than those in control group with statistically significant differences (P<0.001). This resting-state fMRI study suggested that the alteration brain activity in the right medial prefrontal and left parietal ALFF contributed to the understanding of the pathophysiological mechanism of MDD patients.
Although a great number of studies have investigated the changes of resting-state functional connectivity (rsFC) in patients with mental disorders, such as depression and schizophrenia etc, little is known how stable the changes are, and whether temporal sad or happy mood can modulate the intrinsic rsFC. In our experiments, happy and sad video clips were used to induce temporally happy and sad mood states in 20 healthy young adults. We collected functional magnetic resonance imaging (fMRI) data while participants were watching happy or sad video clips, which were administrated in two consecutive days. Seed-based functional connectivity analyses were conducted using the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), and amygdala as seeds to investigate neural network related to executive function, attention, and emotion. We also investigated the association of the rsFC changes with emotional arousability level to understand individual differences. There is significantly stronger functional connectivity between the left DLPFC and posterior cingulate cortex (PCC) under sad mood than that under happy mood. The increased connectivity strength was positively correlated with subjects' emotional arousability. The increased positive correlation between the left DLPFC and PCC under sad relative to happy mood might reflect an increased processing of negative emotion-relevant stimuli. The easier one was induced by strong negative emotion (higher emotional arousability), the greater the left DLPFC-PCC connectivity was indicated, the greater the instability of the intrinsic rsFC was shown.