Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments

Hangzhou, China

Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments

Hangzhou, China
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An L.,Peking University | Cao Q.-J.,Peking University | Sui M.-Q.,Peking University | Sun L.,Peking University | And 5 more authors.
Neuroscience Bulletin | Year: 2013

Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF) are two approaches to depicting different regional characteristics of resting-state functional magnetic resonance imaging (RS-fMRI) data. Whether they can complementarily reveal brain regional functional abnormalities in attention-deficit/hyperactivity disorder (ADHD) remains unknown. In this study, we applied ReHo and ALFF to 23 medication-naïve boys diagnosed with ADHD and 25 age-matched healthy male controls using whole-brain voxel-wise analysis. Correlation analyses were conducted in the ADHD group to investigate the relationship between the regional spontaneous brain activity measured by the two approaches and the clinical symptoms of ADHD. We found that the ReHo method showed widely-distributed differences between the two groups in the fronto-cingulo-occipito-cerebellar circuitry, while the ALFF method showed a difference only in the right occipital area. When a larger smoothing kernel and a more lenient threshold were used for ALFF, more overlapped regions were found between ALFF and ReHo, and ALFF even found some new regions with group differences. The ADHD symptom scores were correlated with the ReHo values in the right cerebellum, dorsal anterior cingulate cortex and left lingual gyrus in the ADHD group, while no correlation was detected between ALFF and ADHD symptoms. In conclusion, ReHo may be more sensitive to regional abnormalities, at least in boys with ADHD, than ALFF. And ALFF may be complementary to ReHo in measuring local spontaneous activity. Combination of the two may yield a more comprehensive pathophy-siological framework for ADHD. © 2013 Shanghai Institutes for Biological Sciences, CAS and Springer-Verlag Berlin Heidelberg.


Shin D.-J.,University of Seoul | Jung W.H.,Seoul National University | He Y.,Beijing Normal University | Wang J.,Beijing Normal University | And 10 more authors.
Biological Psychiatry | Year: 2014

Background Previous neuroimaging studies of obsessive-compulsive disorder (OCD) have reported both baseline functional alterations and pharmacological changes in localized brain regions and connections; however, the effects of selective serotonin reuptake inhibitor (SSRI) treatment on the whole-brain functional network have not yet been elucidated. Methods Twenty-five drug-free OCD patients underwent resting-state functional magnetic resonance imaging. After 16-weeks, seventeen patients who received SSRI treatment were rescanned. Twenty-three matched healthy control subjects were examined at baseline for comparison, and 21 of them were rescanned after 16 weeks. Topological properties of brain networks (including small-world, efficiency, modularity, and connectivity degree) were analyzed cross-sectionally and longitudinally with graph-theory approach. Results At baseline, OCD patients relative to healthy control subjects showed decreased small-world efficiency (including local clustering coefficient, local efficiency, and small-worldness) and functional association between default-mode and frontoparietal modules as well as widespread altered connectivity degrees in many brain areas. We observed clinical improvement in OCD patients after 16 weeks of SSRI treatment, which was accompanied by significantly elevated small-world efficiency, modular organization, and connectivity degree. Improvement of obsessive-compulsive symptoms was significantly correlated with changes in connectivity degree in right ventral frontal cortex in OCD patients after treatment. Conclusions This is first study to use graph-theory approach for investigating valuable biomarkers for the effects of SSRI on neuronal circuitries of OCD patients. Our findings suggest that OCD phenomenology might be the outcome of disrupted optimal balance in the brain networks and that reinstating this balance after SSRI treatment accompanies significant symptom improvement. © 2014 Society of Biological Psychiatry.


Wang B.,Zhejiang Normal University | Wang B.,Hangzhou Normal University | Wang B.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | Hilchey M.D.,Dalhousie University | And 3 more authors.
Neuroscience Letters | Year: 2014

Inhibition of return (IOR) commonly refers to the effect of prolonged response times to targets at previously attended locations. It is a well-documented fact that IOR is not restricted to previously attended locations, but rather has a spatial gradient. Based on a myriad of manual/saccadic dissociations, many researchers now believe that there are at least two forms of IOR completely dissociable on the basis of response type. The present study evaluated whether these two forms of IOR are encoded in similar representations of space. Across a range of conditions, there was little indication that the two forms could be differentiated on the basis of their spatial distributions. Furthermore, the present study also found that the gradient of IOR was steepest for cues appearing nearest fixation. © 2014 Elsevier Ireland Ltd.


Niu H.,Beijing Normal University | Li Z.,Beijing Normal University | Liao X.,Hangzhou Normal University | Liao X.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | And 5 more authors.
PLoS ONE | Year: 2013

Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience. © 2013 Niu et al.


Wang J.,Beijing Normal University | Wang J.,Hangzhou Normal University | Wang J.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | Wang X.,Peking University | And 4 more authors.
Human Brain Mapping | Year: 2015

The apolipoprotein E (APOE) e{open}4 allele is a well-established genetic risk factor for Alzheimer's disease (AD). Recent research has demonstrated an APOE e{open}4-mediated modulation of intrinsic functional brain networks in cognitively normal individuals. However, it remains largely unknown whether and how APOE e{open}4 affects the brain's functional network architecture in patients with AD. Using resting-state functional MRI and graph-theory approaches, we systematically investigated the topological organization of whole-brain functional networks in 16 APOE e{open}4 carriers and 26 matched noncarriers with AD at three levels: global whole-brain, intermediate module, and regional node/connection. Neuropsychological analysis showed that the APOE e{open}4 carriers performed worse on delayed memory but better on a late item generation of a verbal fluency task (associated with executive function) than noncarriers. Whole-brain graph analyses revealed that APOE e{open}4 significantly disrupted whole-brain topological organization as characterized by (i) reduced parallel information transformation efficiency; (ii) decreased intramodular connectivity within the posterior default mode network (pDMN) and intermodular connectivity of the pDMN and executive control network (ECN) with other neuroanatomical systems; and (iii) impaired functional hubs and their rich-club connectivities that primarily involve the pDMN, ECN, and sensorimotor systems. Further simulation analysis indicated that these altered connectivity profiles of the pDMN and ECN largely accounted for the abnormal global network topology. Finally, the changes in network topology exhibited significant correlations with the patients' cognitive performances. Together, our findings suggest that the APOE genotype modulates large-scale brain networks in AD and shed new light on the gene-connectome interaction in this disease. © 2015 Wiley Periodicals, Inc.


Wang J.,Beijing Normal University | Wang J.,Hangzhou Normal University | Wang J.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | Wang X.,Beijing Normal University | And 5 more authors.
Frontiers in Human Neuroscience | Year: 2015

Recent studies have suggested that the brain's structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website. © 2015 Wang, Wang, Xia, Liao, Evans and He.


Lv Y.,Max Planck Institute for Human Cognitive and Brain Sciences | Lv Y.,Hangzhou Normal University | Margulies D.S.,Max Planck Institute for Human Cognitive and Brain Sciences | Margulies D.S.,Humboldt University of Berlin | And 5 more authors.
PLoS ONE | Year: 2013

Resting-state functional magnetic resonance imaging (RS-fMRI) has been widely used to investigate temporally correlated fluctuations between distributed brain areas, as well as to characterize local synchronization of low frequency (<0.1 Hz) spontaneous fMRI signal. Regional homogeneity (ReHo) was proposed as a voxel-wise measure of the synchronization of the timecourses of neighboring voxels and has been used in many studies of brain disorders. However, the interpretation of ReHo remains challenging because the effect of high frequency task on ReHo is still not clear. In order to investigate the effect of a high-frequency task on the modulation of local synchronization of resting-state activity, we employed three right-finger movement scanning sessions: slow-event related ('Slow'), fast-event related ('Fast'), and continuous finger pressure ('Tonic'), from 21 healthy participants and compared the ReHo of the three task states with that of resting-state ('Rest'). In the contralateral sensorimotor cortex, 'Slow' task state showed greater ReHo than 'Rest' in low frequency band (0-0.08Hz) fMRI signal, but lower ReHo in high frequency band (0.08-1.67 Hz); 'Fast' task state showed lower ReHo than 'Rest' in both the low and high frequency band; 'Tonic' state did not show any significant difference compared to 'Rest'. The results in the contralateral sensorimotor cortex suggest that local synchronization of BOLD signal varies with different finger tapping speed. In the ipsilateral sensorimotor cortex, all the three task states had lower ReHo than the 'Rest' state both in the low and high frequency, suggesting a similar effect of fast and slow finger tapping frequencies on local synchronization of BOLD signal in the ipsilateral motor cortex. © 2013 Lv et al.


Liu Y.,Capital Medical University | Liu Y.,VU University Amsterdam | Liu Y.,Tianjin Medical University | Wang J.,Hangzhou Normal University | And 14 more authors.
Neurology | Year: 2015

Objective: To investigate spinal cord and brain atrophy in neuromyelitis optica (NMO), and its relationship with other MRI measurements and clinical disability, compared with patients with multiple sclerosis (MS) and healthy controls (HC). Methods: We recruited 35 patients with NMO, 35 patients with MS, and 35 HC, who underwent both spinal cord and brain MRI. Mean upper cervical cord area (MUCCA), brain parenchymal fraction (BPF), gray matter fraction (GMF), white matter fraction (WMF), and spinal cord and brain lesion loads were measured and compared among groups. Multivariate associations between MUCCA and brain volume measurement and clinical variables were assessed by partial correlations and multiple linear regression. Results: Patients with NMO showed smaller MUCCA than HC (p 0.004), and patients with MS had a trend of smaller MUCCA compared to HC (p 0.07), with no significant difference between the patient groups. Patients with NMO showed lower BPF than HC, and patients with MS had lower BPF and GMF than patients with NMO. In NMO, MUCCA was correlated with Expanded Disability Status Scale score (EDSS), number of relapses, and total spinal cord lesion length, while in MS, MUCCA was correlated with WMF and EDSS. MUCCA was the only independent variable for predicting clinical disability measured by EDSS in NMO (R 2 0.55, p < 0.001) and MS (R 2 0.17, p 0.013). Conclusion: NMO showed predominately spinal cord atrophy with mild brain atrophy, while MS demonstrated more brain atrophy, especially in the gray matter. MUCCA is the main MRI-derived parameter for explaining clinical disability in NMO and MS, and may serve as a potential biomarker for further clinical trials, especially in NMO. © 2015 American Academy of Neurology.


Zhao J.,Chinese Academy of Sciences | Zhao J.,Hangzhou Normal University | Zhao J.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | Kipp K.,University of Ulm | And 8 more authors.
Journal of Cognitive Neuroscience | Year: 2014

The left-lateralized N170 component of ERPs for words compared with various control stimuli is considered as an electrophysiological manifestation of visual expertise for written words. To understand the information sensitivity of the effect, researchers distinguish between coarse tuning for words (the N170 amplitude difference between words and symbol strings) and fine tuning for words (the N170 amplitude difference between words and consonant strings). Earlier developmental ERP studies demonstrated that the coarse tuning for words occurred early in children (8 years old), whereas the fine tuning for words emerged much later (10 years old). Given that there are large individual differences in reading ability in young children, these tuning effects may emerge earlier than expected in some children. This study measured N170 responses to words and control stimuli in a large group of 7-year-olds that varied widely in reading ability. In both low and high reading ability groups, we observed the coarse neural tuning for words. More interestingly, we found that a stronger N170 for words than consonant strings emerged in children with high but not low reading ability. Our study demonstrates for the first time that fine neural tuning for orthographic properties of words can be observed in young children with high reading ability, suggesting that the emergent age of this effect is much earlier than previously assumed. The modulation of this effect by reading ability suggests that fine tuning is flexible and highly related to experience. Moreover, we found a correlation between this tuning effect at left occipitotemporal electrodes and children’s reading ability, suggesting that the fine tuning might be a biomarker of reading skills at the very beginning of learning to read. © 2014 Massachusetts Institute of Technology.


Zhao J.,CAS Institute of Psychology | Zhao J.,Hangzhou Normal University | Zhao J.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments | Wang L.,CAS Institute of Psychology | And 5 more authors.
Scientific Reports | Year: 2014

The human visual system is extremely sensitive to the direction information retrieved from biological motion. In the current study, we investigate the functional impact of this sensitivity on attentional orienting in young children. We found that children as early as 4 years old, like adults, showed a robust reflexive attentional orienting effect to the walking direction of an upright point-light walker, indicating that biological motion signals can automatically direct spatial attention at an early age. More importantly, the inversion effect associated with attentional orienting emerges by 4 years old and gradually develops into a similar pattern found in adults. These results provide strong evidence that biological motion cues can guide the distribution of spatial attention in young children, and highlight a critical development from a broadly-to finely-tuned process of utilizing biological motion cues in the human social brain.

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