Ruwei Dai

A longitudinal study of hand motor recovery after sub-acute stroke: a study combined FMRI with diffusion tensor imaging.

Previous studies have shown that motor recovery of stroke can be assessed by the cortical activity and the structural integrity of the corticospinal tract (CST), but little is known about the relation between the cortical activity and the structural integrity during motor recovery. In the present study, we investigated the changes in brain activities evoked by twenty days’ functional electrical stimulation (FES) training in twelve sub-acute stroke patients with unilateral upper-limb disability. We compared cortex activity evoked by wrist movement of eleven stroke patients to that of eleven age-matched healthy subjects to figure out how cortex activity changed after stroke. We also measured the structural integrity represented by the fractional anisotropy (FA) asymmetry of the posterior limb of the internal capsule (PLIC) to find the relationship between the brain activity and the structure integrity. In our study, we found that patients with sub-acute stroke have shown greater activity in the contralesional primary motor cortex (M1) during the affected hand’s movement compared with healthy group, while the activity in ipsilesional M1 was decreased after the therapy compared to that before therapy, and the contralesional non-primary motor cortex showed greater activity after therapy. At the baseline we found that the positive correlation between the FA asymmetry of PLIC and the contralesional non-primary motor cortex activity showed that the greater damaged CST, the greater contralesional non-primary motor cortex recruited. While the negative correlation between them after the FES training indicates that after recovery the non-primary motor cortex plays different role in different stroke phases. Our study demonstrates that functional organization of a residual distributed motor system is related to the degree of disruption to the CST, and the non-primary motor areas plays an important role in motor recovery.

Altered topological patterns of brain networks in mild cognitive impairment and Alzheimer's disease: A resting-state fMRI study

Recent studies have shown that cognitive and memory decline in patients with Alzheimers disease (AD) is coupled with losses of small-world attributes. However, few studies have investigated the characteristics of the whole brain networks in individuals with mild cognitive impairment (MCI). In this functional magnetic resonance imaging (fMRI) study, we investigated the topological properties of the whole brain networks in 18 AD patients, 16 MCI patients, and 18 age-matched healthy subjects. Among the three groups, AD patients showed the longest characteristic path lengths and the largest clustering coefficients, while the small-world measures of MCI networks exhibited intermediate values. The finding was not surprising, given that MCI is considered to be the prodromal stage of AD. Compared with normal controls, MCI patients showed decreased nodal centrality mainly in the medial temporal lobe as well as increased nodal centrality in the occipital regions. In addition, we detected increased nodal centrality in the medial temporal lobe and frontal gyrus, and decreased nodal centrality mainly in the amygdala in MCI patients compared with AD patients. The results suggested a widespread rewiring in AD and MCI patients. These findings concerning AD and MCI may be an integrated reflection of reorganization of the brain networks accompanied with the cognitive decline that may lead to AD.

Multi-scale local binary pattern with filters for spoof fingerprint detection

Fingerprint recognition systems are being increasingly deployed in both government and civilian applications. But the emergence of fake fingerprints brings on a new challenge. Among the numerous fingerprint vitality detection methods, local binary pattern (LBP) is considered as one of the best operators. But the original LBP operator has the limitation of its small spatial support area. So we proposed a novel spoof fingerprint detection method based on multi-scale local binary pattern (MSLBP). Generally speaking, the MSLBP can be realized in two different ways. We implemented both types of MSLBP. Each MSLBP was combined with a set of filters. In this way, each sample in the LBP circle could be made to collect intensity information from a large area rather than a single pixel. The experimental results in the database of the Liveness Detection Competition 2011 (LivDet2011) have shown that both types of MSLBP are effective and superior in spoof fingerprint detection.

Investigation of the effective connectivity of resting state networks in Alzheimer's disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis.

Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimers disease (AD) is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses in small‐world attributes. However, the causal interactions among the spatially isolated, but functionally related, resting state networks (RSNs) are still largely unexplored. In this study, we first identified eight RSNs by independent components analysis from resting state functional MRI data of 18 patients with AD and 18 age‐matched healthy subjects. We then performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that patients with AD exhibited decreased causal interactions among the RSNs in both intensity and quantity relative to normal controls. Results from mGCA indicated that the causal interactions involving the default mode network and auditory network were weaker in patients with AD, whereas stronger causal connectivity emerged in relation to the memory network and executive control network. Our findings suggest that the default mode network plays a less important role in patients with AD. Increased causal connectivity of the memory network and self‐referential network may elucidate the dysfunctional and compensatory processes in the brain networks of patients with AD. These preliminary findings may provide a new pathway towards the determination of the neurophysiological mechanisms of AD. Copyright

Modulatory effects of acupuncture on resting-state networks: a functional MRI study combining independent component analysis and multivariate Granger causality analysis.

To investigate acupuncture specificity by exploring causal relationships of brain networks following acupuncture at GB40 (Qiuxu), with the acupoint KI3 (Taixi) as a control (belonging to the same nerve segment but different meridians).

Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images

The aim of the study is to assess the staging value of the tumor heterogeneity characterized by texture features and other commonly used semi-quantitative indices extracted from (18)F-FDG PET images of cervical cancer (CC) patients. Forty-two patients suffering CC at different stages were enrolled in this study. Firstly, we proposed a new tumor segmentation method by combining the intensity and gradient field information in a level set framework. Secondly, fifty-four 3D texture features were studied besides of SUVs (SUVmax, SUVmean, SUVpeak) and metabolic tumor volume (MTV). Through correlation analysis, receiver-operating-characteristic (ROC) curves analysis, some independent indices showed statistically significant differences between the early stage (ES, stages I and II) and the advanced stage (AS, stages III and IV). Then the tumors represented by those independent indices could be automatically classified into ES and AS, and the most discriminative feature could be chosen. Finally, the robustness of the optimal index with respect to sampling schemes and the quality of the PET images were validated. Using the proposed segmentation method, the dice similarity coefficient and Hausdorff distance were 91.78   ±   1.66% and 7.94   ±   1.99 mm, respectively. According to the correlation analysis, all the fifty-eight indices could be divided into 20 groups. Six independent indices were selected for their highest areas under the ROC curves (AUROC), and showed significant differences between ES and AS (P  <  0.05). Through automatic classification with the support vector machine (SVM) Classifier, run percentage (RP) was the most discriminative index with the higher accuracy (88.10%) and larger AUROC (0.88). The Pearson correlation of RP under different sampling schemes is 0.9991   ±   0.0011. RP is a highly stable feature and well correlated with tumor stage in CC, which suggests it could differentiate ES and AS with high accuracy.

Altered Hub Configurations within Default Mode Network following Acupuncture at ST36: A Multimodal Investigation Combining fMRI and MEG

Acupuncture, an externally somatosensory stimulation in the Traditional Chinese Medicine, has been proposed about its modulations on the brains default mode network (DMN). However, it is still unknown on how the internal brain resting networks are modulated and what inferences can be made about the physiological processes underlying these changes. Combining high spatial resolution of functional magnetic resonance imaging (fMRI) with high temporal resolution of magnetoencephalography (MEG), in the current multimodal study, we sought to explore spatiotemporally whether or not band-specific DMN hub configurations would be induced by verum acupuncture, compared with sham control. Spatial independent component analysis was applied to fMRI data, followed by the discrete regional sources seeded into MEG data. Partial correlation analysis was further adopted to estimate the intrinsic functional connectivity and network hub configurations. One of the most striking findings is that the posterior cingulate cortex is not only validated as a robust DMN hub, but served as a hub only within the delta and gamma bands following the verum acupuncture, compared with its consistently being a DMN hub in sham control group. Our preliminary results may provide a new perspective to lend support for the specificity of neural mechanism underlying acupuncture.

Multi-scale block local ternary patterns for fingerprints vitality detection

Fingerprint recognition systems are widely deployed in both government and civilian applications. But the emergence of fake fingerprints poses a new threat to privacy security. Among the numerous fingerprint vitality detection methods, the local binary pattern (LBP) is considered as one of the state-of-the-art operators. However, the local binary pattern tends to be sensitive to noise, as there are no types of filters involved in the LBP operator. Worse still, the LBP operator can not reflect these difference whether the pixel value is bigger than the threshold or equal to the threshold. So we proposed a novel fingerprint vitality detection method based on multi-scale block local ternary patterns (MBLTP). Instead of a single pixel, its computation is done based on the average value of blocks. The ternary pattern is adopted to reflect the differences between the pixels and the threshold. The experimental results in the databases of Competition on Fingerprint Liveness Detection 2011 (LivDet 2011) show its superiority.

Exploring the effective connectivity of resting state networks in Mild Cognitive Impairment: An fMRI study combining ICA and multivariate Granger causality analysis

Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimers disease (AD). Recent neuroimaging studies have shown that the cognitive and memory decline in AD and MCI patients is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses of small-world attributes. However, the causal interactions among the spatially isolated but function-related resting state networks (RSNs) are still largely unexplored in MCI patients. In this study, we first identified eight RSNs by independent components analysis (ICA) from resting state functional MRI data of 16 MCI patients and 18 age-matched healthy subjects respectively. Then, we performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that MCI patients exhibited decreased causal interactions among the RSNs in both intensity and quantity compared with normal controls. Results from mGCA indicated that the causal interactions involving the default mode network (DMN) became weaker in MCI patients, while stronger causal connectivity emerged related to the memory network and executive control network. Our findings suggested that the DMN played a less important role in MCI patients. Increased causal connectivity of the memory network and executive control network may elucidate the dysfunctional and compensatory processes in the brain networks of MCI patients. These preliminary findings may be helpful for further understanding the pathological mechanisms of MCI and provide a new clue to explore the neurophysiological mechanisms of MCI.

Acupuncture Induces Divergent Alterations of Functional Connectivity within Conventional Frequency Bands: Evidence from MEG Recordings

As an ancient Chinese healing modality which has gained increasing popularity in modern society, acupuncture involves stimulation with fine needles inserted into acupoints. Both traditional literature and clinical data indicated that modulation effects largely depend on specific designated acupoints. However, scientific representations of acupoint specificity remain controversial. In the present study, considering the new findings on the sustained effects of acupuncture and its time-varied temporal characteristics, we employed an electrophysiological imaging modality namely magnetoencephalography with a temporal resolution on the order of milliseconds. Taken into account the differential band-limited signal modulations induced by acupuncture, we sought to explore whether or not stimulation at Stomach Meridian 36 (ST36) and a nearby non-meridian point (NAP) would evoke divergent functional connectivity alterations within delta, theta, alpha, beta and gamma bands. Whole-head scanning was performed on 28 healthy participants during an eyes-closed no-task condition both preceding and following acupuncture. Data analysis involved calculation of band-limited power (BLP) followed by pair-wise BLP correlations. Further averaging was conducted to obtain local and remote connectivity. Statistical analyses revealed the increased connection degree of the left temporal cortex within delta (0.5–4 Hz), beta (13–30 Hz) and gamma (30–48 Hz) bands following verum acupuncture. Moreover, we not only validated the closer linkage of the left temporal cortex with the prefrontal and frontal cortices, but further pinpointed that such patterns were more extensively distributed in the ST36 group in the delta and beta bands compared to the restriction only to the delta band for NAP. Psychophysical results for significant pain threshold elevation further confirmed the analgesic effect of acupuncture at ST36. In conclusion, our findings may provide a new perspective to lend support for the specificity of neural expression underlying acupuncture.