Changes of regional brain activity following Tuina therapy for patients with painful cervical spondylosis: a resting-state fMRI study

The brain's default mode network consists of discrete, bilateral and symmetrical cortical areas, in the medial and lateral parietal, medial prefrontal, and medial and lateral temporal cortices of the human, nonhuman primate, cat, and rodent brains. Its discovery was an unexpected consequence of brain-imaging studies first performed with positron emission tomography in which various novel, attention-demanding, and non-self-referential tasks were compared with quiet repose either with eyes closed or with simple visual fixation. The default mode network consistently decreases its activity when compared with activity during these relaxed nontask states. The discovery of the default mode network reignited a longstanding interest in the significance of the brain's ongoing or intrinsic activity. Presently, studies of the brain's intrinsic activity, popularly referred to as resting-state studies, have come to play a major role in studies of the human brain in health and disease. The brain's default mode network plays a central role in this work. Show more

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for “pipeline” data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for “pipeline” data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest. Show more

Kendall's coefficient concordance (KCC) can measure the similarity of a number of time series. It has been used for purifying a given cluster in functional MRI (fMRI). In the present study, a new method was developed based on the regional homogeneity (ReHo), in which KCC was used to measure the similarity of the time series of a given voxel to those of its nearest neighbors in a voxel-wise way. Six healthy subjects performed left and right finger movement tasks in event-related design; five of them were additionally scanned in a rest condition. KCC was compared among the three conditions (left finger movement, right finger movement, and the rest). Results show that bilateral primary motor cortex (M1) had higher KCC in either left or right finger movement condition than in rest condition. Contrary to prediction and to activation pattern, KCC of ipsilateral M1 is significantly higher than contralateral M1 in unilateral finger movement conditions. These results support the previous electrophysiologic findings of increasing ipsilateral M1 excitation during unilateral movement. ReHo can consider as a complementary method to model-driven method, and it could help reveal the complexity of the human brain function. More work is needed to understand the neural mechanism underlying ReHo. Show more