Publications by authors named "Shao-Wei Xue"

20 Publications

  • Page 1 of 1

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.

J Psychiatr Res 2021 Jun 8;138:569-575. Epub 2021 May 8.

College of Education, Hangzhou Normal University, Hangzhou, 311121, China.

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.
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http://dx.doi.org/10.1016/j.jpsychires.2021.05.010DOI Listing
June 2021

Aberrant state-related dynamic amplitude of low-frequency fluctuations of the emotion network in major depressive disorder.

J Psychiatr Res 2021 01 3;133:23-31. Epub 2020 Dec 3.

Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 311121, China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou 311121, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou 311121, China.

Major depressive disorder (MDD) is a highly prevalent mental disorder that is typically characterized by pervasive and persistent low mood. This durable emotional disturbance may represent a key aspect of the neuropathology of MDD, typified by the wide-ranging distribution of brain alterations involved in emotion processing. However, little is known about whether these alterations are represented as the state properties of dynamic amplitude of low-frequency fluctuation (dALFF) variability in the emotion network. To address this question, we investigated the time-varying intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI). Data were obtained from 50 MDD patients and 37 sex- and age-matched healthy controls; a sliding-window method was used to assess dALFF in the emotion network, and two reoccurring dALFF states throughout the entire R-fMRI scan were then identified using a k-means clustering method. The results showed that MDD patients had a significant decrease in dALFF variability in the emotion network and its three modules located in the lateral paralimbic, media posterior, and visual association regions. Altered state-wise dALFF was also observed in MDD patients. Specifically, we found that these altered dALFF measurements in the emotion network were related to scores on the Hamilton Rating Scale for Depression (HAMD) among patients with MDD. The detection and estimation of these temporal dynamic alterations could advance our knowledge about the brain mechanisms underlying emotional dysfunction in MDD.
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http://dx.doi.org/10.1016/j.jpsychires.2020.12.003DOI Listing
January 2021

Musculoskeletal ultrasound in the Differential Diagnosis of Gouty Arthritis and Rheumatoid Arthritis.

Pak J Med Sci 2020 Jul-Aug;36(5):977-981

Zi-yu Jiao, Department of Ultrasound, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, P. R. China.

Objective: To explore the role of musculoskeletal ultrasound (MSUS) in the differential diagnosis of gouty arthritis (GA) and rheumatoid arthritis (RA) and to analyze the ultrasound imaging features of the two diseases.

Methods: A retrospective study was carried out. A total of 66 patients who had been admitted to The First Medical Center of Chinese PLA General Hospital from May 2018 to March 2019 were enrolled. Among them, 34 patients were diagnosed with RA and were included in the RA group; 32 patients were diagnosed with gouty arthritis and were included in the GA group. The imaging features of musculoskeletal ultrasound were compared between the two groups of patients.

Results: A total of 34 patients were included in the RA group, including 17 males and 17 females. A total of 32 patients were included in the GA group, including 14 males and 18 females. There were no significant differences in gender composition, age, and duration of disease between the two groups (>0.05). In the RA group, there were joint bone erosions with a clear boundary in seven cases and with a blurred boundary in 27 cases; synovial hyperplasia was observed in 27 cases, and point-like hyperechoic masses were observed in four cases. In the GA group, there were joint bone erosions with a clear boundary in 27 cases and with a blurred boundary in five cases; synovial hyperplasia was observed in four cases, tophus was observed in 23 cases, point-like hyperechoic masses were observed in 27 cases, and the tram-track sign was observed in 23 cases. The differences in bone erosion boundaries (c2=26.854, <0.01), synovial hyperplasia (c2=29.631, <0.01), tophus (<0.01), point-like hyperechoic mass (c2=33.095, <0.01), and tram-track sign (<0.01) were statistically significant between the two groups of patients. In the RA group, blood flow signaling was Grade 0 in one case, Grade-I in five cases, Grade-II in 14 cases, and Grade-III in 14 cases. In the GA group, blood flow signaling was Grade 0 in 26 cases, Grade-I in three cases, Grade-II in three cases, and Grade-III in zero cases. The difference in the synovial blood flow signaling between the two groups of patients was statistically significant (c2=34.323, <0.01).

Conclusions: MSUS has certain diagnostic value in the differentiation of GA and RA. Moreover, the two conditions have their own ultrasound imaging features.
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http://dx.doi.org/10.12669/pjms.36.5.2716DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372673PMC
July 2020

[Value of Thermal Tomography in Early Diagnosis of Breast Cancer in Animal Models].

Zhongguo Yi Xue Ke Xue Yuan Xue Bao 2020 Apr;42(2):236-241

Department of Ultrasound,the Second Medical Center, Chinese PLA General Hospital,Beijing 100853,China.

To obtain ultrasound and thermal tomography images of breast cancer during its growth and to assess the value of thermal tomography in detecting breast cancer. Breast cancer models were established with NOD/SCID mice and SD rats. These animal models were examined by thermal tomography,plain ultrasound,and contrast-enhanced ultrasound. Tumor tissues were stained with CD34 to explore the relationship between tumor heat production and vascular pathology. Thermal tomography detected breast cancer 2-4 days earlier than ultrasound. The expression of CD34 in tumor tissues was increased,along with thickened,increased,and irregular blood vessels. Thermal tomography can detect early breast cancer and is a promising tool for screening breast cancer.
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http://dx.doi.org/10.3881/j.issn.1000-503X.11988DOI Listing
April 2020

Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach.

Neuropsychiatr Dis Treat 2020 10;16:691-702. Epub 2020 Mar 10.

Center for Cognition and Brain Disorders, Institute of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 311121, People's Republic of China.

Purpose: In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from whole-brain resting-state functional connectivity patterns using machine learning.

Patients And Methods: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests.

Results: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD ( < 0.05).

Conclusion: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.
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http://dx.doi.org/10.2147/NDT.S239013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071874PMC
March 2020

Intranasal Oxytocin Increases Perceptual Salience of Faces in the Absence of Awareness.

Psychiatry Investig 2020 Apr 24;17(4):292-298. Epub 2020 Mar 24.

Center for Cognition and Brain Disorders, Institutes of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China.

Objective: The neuropeptide oxytocin has been found to improve human social cognition and promote prosocial behavior. However, it is still unclear about the mechanisms underlying these effects of oxytocin on neural processes, such as visual perception and awareness. Especially, it is still unclear whether oxytocin influences perceptual salience of social stimuli in the absence of awareness.

Methods: In a randomized double-blind, placebo-controlled trial we applied an interocular suppression paradigm and eye tracking methods to investigate the influence of intranasally administered oxytocin on perceptual salience of social stimuli. Suppression times and pupillometric data were measured during subjects being presented with gradually introduced pictures of social stimuli (neutral expression faces) or nonsocial stimuli (grayscale watch pictures) that were suppressed and invisible in 10 men who were administered 24 IU oxytocin and 10 men who were administered a placebo.

Results: The results demonstrated that the oxytocin group perceived social stimuli more quickly accompanied by subsequent larger increasing pupil diameter than nonsocial stimuli, indicating an increased unconscious salience of social stimuli.

Conclusion: These findings provided new insights into oxytocin's modulatory role to social information processing, suggesting that oxytocin might enhance attentional bias to social stimuli even after removal of awareness.
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http://dx.doi.org/10.30773/pi.2019.0130DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176568PMC
April 2020

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder.

Neuropsychiatr Dis Treat 2019 11;15:2629-2638. Epub 2019 Sep 11.

Center for Cognition and Brain Disorders, Institutes of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 311121, People's Republic of China.

Purpose: Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients.

Patients And Methods: We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns.

Results: The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients.

Conclusion: This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.
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http://dx.doi.org/10.2147/NDT.S220743DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6750201PMC
September 2019

Altered hypothalamic functional connectivity patterns in major depressive disorder.

Neuroreport 2019 11;30(16):1115-1120

Center for Cognition and Brain Disorders, Institutes of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University.

The hypothalamus is a limbic structure involved in the emergence and persistence of major depressive disorder symptoms. Previous studies have indicated that major depressive disorder patients exhibited dysregulation between the hypothalamus and cerebral regions. However, it is still unclear about the exact hypothalamic functional connectivity patterns with other brain regions based on resting-state functional MRI in major depressive disorder. Here, we investigated the whole-brain voxel-based hypothalamic resting-state functional connectivity in 55 patients with major depressive disorder and 40 age sex-matched healthy controls. The results showed that major depressive disorder patients had a significant decrease in resting-state functional connectivity of the bilateral hypothalamus with the right insula, superior temporal gyrus, inferior frontal gyrus, and Rolandic operculum compared with healthy controls. This study suggests that the pathophysiology of major depressive disorder might be associated with the abnormal hypothalamic resting-state functional connectivity.
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http://dx.doi.org/10.1097/WNR.0000000000001335DOI Listing
November 2019

Resting-state brain entropy in schizophrenia.

Compr Psychiatry 2019 02 4;89:16-21. Epub 2018 Dec 4.

Department of Radiology, Lewis Katz School of Medicine, Temple University, USA. Electronic address:

Background: The human brain presents ongoing temporal fluctuations whose dynamic range indicates the capacity of information processing and can be approximately quantified with entropy. Using functional magnetic resonance imaging (fMRI), recent studies have shown a stable distribution pattern of temporal brain entropy (tBEN) in healthy subjects, which may be affected by neuropsychiatric diseases such as schizophrenia. Assessing tBEN may reciprocally provide a new tool to characterize those disorders.

Methods: The current study aimed to identify tBEN changes in schizophrenia patients using publicly available data from the Centers of Biomedical Research Excellence (COBRE) project. Forty-three schizophrenia patients and 59 sex- and age-matched healthy control subjects were included, and tBEN was calculated from their resting-state fMRI scans.

Results: Compared with healthy controls, patients showed decreased tBEN in the right middle prefrontal cortex, bilateral thalamus, right hippocampus and bilateral caudate and increased tBEN in the left lingual gyrus, left precuneus, right fusiform face area and right superior occipital gyrus. In schizophrenia patients, tBEN in the left cuneus and middle occipital gyrus was negatively correlated with the positive and negative syndrome scores (PANSS). Age of onset was inversely correlated with tBEN in the right fusiform gyrus and left insula.

Conclusion: Our findings demonstrate a detrimental tBEN reduction in schizophrenia that is related to clinical characteristics. The tBEN increase in a few regions might be a result of tBEN redistribution across the whole brain in schizophrenia.
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http://dx.doi.org/10.1016/j.comppsych.2018.11.015DOI Listing
February 2019

Does emotion regulation engage the same neural circuit as working memory? A meta-analytical comparison between cognitive reappraisal of negative emotion and 2-back working memory task.

PLoS One 2018 13;13(9):e0203753. Epub 2018 Sep 13.

Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China.

Research into cognitive emotion regulation (ER) extends our understanding of human cognition, which is capable of processing objective information and is crucial in maintaining subjective/internal homeostasis. Among various ER strategies, the alleviation of negative emotion via reappraisal is of particular importance for adaptation and psychological well-being. Although still debated, previous neuroimaging studies tend to infer that the reappraisal ER is mediated by the capability of working memory (WM), which has not been examined empirically. This meta-analytical study of published neuroimaging literature used activation likelihood estimation (ALE) to compare the neural circuits that regulate negative emotion (reappraisal tasks; 46 studies/1254 subjects) and execute WM (2-back tasks; 50 studies/1312 subjects), with special emphasis on the prefrontal cortex (PFC). Taking the canonical WM network as a reference, ALE results revealed that the dorsal midline PFC was partly shared by both ER and WM, whereas ER-specific PFC structures were delineated in the inferior, middle, and superior frontal cortices, as well as in the posterior brain regions. The peak coordinates of ER in the middle frontal cortex were dorsal to those of WM by 15.1 mm (left) and 21.6 mm (right). The results support specialized emotion-related neural substrates in the PFC, negating the assumption that reappraisal ER and WM rely on the same neural resources. The holistic picture of "emotional brain" may need to incorporate the emotion-related PFC circuit, together with subcortical and limbic emotion centers.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0203753PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136767PMC
February 2019

Spontaneous activity in medial orbitofrontal cortex correlates with trait anxiety in healthy male adults.

J Zhejiang Univ Sci B 2018 Aug.;19(8):643-653

Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou 311121, China.

Medial orbitofrontal cortex (mOFC) abnormalities have been observed in various anxiety disorders. However, the relationship between mOFC activity and anxiety among the healthy population has not been fully examined. Here, we conducted a resting state functional magnetic resonance imaging (R-fMRI) study with 56 healthy male adults from the Nathan Kline Institute/Rockland Sample (NKI-RS) to examine the relationship between the fractional amplitude of low-frequency fluctuation (fALFF) signals and trait anxiety across the whole brain. A Louvain method for module detection based on graph theory was further employed in the automated functional subdivision to explore subregional correlates of trait anxiety. The results showed that trait anxiety was related to fALFF in the mOFC. Additionally, the resting-state functional connectivity (RSFC) between the right subregions of the mOFC and the precuneus was correlated with trait anxiety. These findings provided evidence about the involvement of the mOFC in anxiety processing among the healthy population.
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http://dx.doi.org/10.1631/jzus.B1700481DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102183PMC
December 2018

Functional connectivity maps based on hippocampal and thalamic dynamics may account for the default-mode network.

Eur J Neurosci 2018 03 8;47(5):388-398. Epub 2018 Feb 8.

Center for Cognition and Brain Disorders, Hangzhou Normal University, Room 301, No. 19, Shuyuan Building, No. 2318, Yuhangtang Rd, Hangzhou 311121, China.

The default-mode network (DMN) has been reported to comprise a set of inter-connected transmodal cortical areas, including the posterior cingulate cortex (PCC), medial prefrontal cortex, posterior inferior parietal lobule, lateral temporal region and others. However, the subcortical constituents of the DMN are still not clear. This study aimed to examine whether the correlation maps derived from subcortical structures may also account for neural pattern of the DMN. Structural magnetic resonance imaging (MRI) and resting-state functional MRI scans of 36 subjects were selected from the Rockland sample (Nathan Kline Institute). The hippocampus and thalamus were chosen as subcortical regions of interest (ROIs). Each ROI was partitioned into composite modules which in turn provided simplified and representative dynamics of blood-oxygen-level-dependent (BOLD) signals. PCC-seeded and ROI-based correlation maps were compared by conjunction analyses and paired t-tests (corrected P < 0.05). Our results unveiled that the hippocampus-, thalamus- and PCC-centred correlation patterns actually overlapped to a substantial degree. Integrating the signals in the thalamus and hippocampus altogether fully explained the PCC-seeded DMN. Supplementary analyses based on the BOLD dynamics in several subcortical nuclei (caudate, putamen and globus pallidus) were dissimilar to the DMN. The DMN derived from the ROI/seed-based approach may represent combined limbic and region-specific informatics (and their closely interacting neural substrates). The possible causes for previous methods of task-induced deactivation and seed-based correlation that failed to depict the holistic limbic picture are discussed. The neocortical manifestation of DMN may reflect the limbic information in the transmodal brain regions.
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http://dx.doi.org/10.1111/ejn.13828DOI Listing
March 2018

Increased Low-Frequency Resting-State Brain Activity by High-Frequency Repetitive TMS on the Left Dorsolateral Prefrontal Cortex.

Front Psychol 2017 22;8:2266. Epub 2017 Dec 22.

Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.

Beneficial effects of repetitive transcranial magnetic stimulation (rTMS) on left dorsolateral prefrontal cortex (DLPFC) have been consistently shown for treating various neuropsychiatrical or neuropsychological disorders, but relatively little is known about its neural mechanisms. Here we conducted a randomized, double-blind, SHAM-controlled study to assess the effects of high-frequency left DLPFC rTMS on resting-state activity. Thirty-eight young healthy subjects received two sessions of either real rTMS ( 18, 90% motor-threshold; left DLPFC at 20 Hz) or SHAM TMS ( 20) and functional magnetic resonance imaging scan during rest in 2 days separated by 48 h. Resting-state bran activity was measured with the fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC). Increased fALFF was found in rostral anterior cingulate cortex (rACC) after 20 Hz rTMS, while no changes were observed after SHAM stimulation. Using the suprathreshold rACC cluster as the seed, increased FC was found in left temporal cortex (stimulation vs. group interaction). These data suggest that high-frequency rTMS on left DLPFC enhances low-frequency resting-state brain activity in the target site and remote sites as reflected by fALFF and FC.
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http://dx.doi.org/10.3389/fpsyg.2017.02266DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744634PMC
December 2017

Revisiting the Functional and Structural Connectivity of Large-Scale Cortical Networks.

Brain Connect 2018 04 2;8(3):129-138. Epub 2018 Mar 2.

1 Center for Cognition and Brain Disorders, Hangzhou Normal University , Hangzhou, China .

Multimodal neuroimaging research has become increasingly popular, and structure-function correspondence is tacitly assumed. Researchers have not yet adequately assessed whether the functional connectivity (FC) and structural connectivity (SC) of large-scale cortical networks are in agreement. Structural magnetic resonance imaging (sMRI), resting-state functional MRI (rfMRI), and diffusion-weighted imaging (DWI) data sets from 36 healthy subjects (age 27.4) were selected from a Rockland sample (Enhanced Nathan Kline Institute). The cerebral cortex was parcellated into 62 regions according to the Desikan-Killiany atlas for FC and SC analyses. Thresholded correlations in rfMRI and tractography derived from DWI were used to construct FC and SC maps, respectively. A community detection algorithm was applied to reveal the underlying organization, and modular consistency was quantified to bridge cross-modal comparisons. The distributions of correlation coefficients in FC and SC maps were significantly different. Approximately one-fourth of the connections in the SC map were located at a correlation level below 0.2 (df 253). The index of modular consistency in the within-modality interindividual condition (either FC or SC) was considerably greater than that in the between-modality intraindividual analog. In addition, the SC-FC differential map (SC connections with lower correlations) revealed reliable modular structures. Based on these results, the hypothesized FC-SC agreement is partially valid. Contingent on extant neuroimaging tools and analytical conventions, the neural informatics of FC and SC should be regarded as complementary rather than concordant. Furthermore, the results verify the physiological significance of moderately (or mildly) correlated brain signals in rfMRI, which are often discarded by stringent thresholding.
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http://dx.doi.org/10.1089/brain.2017.0536DOI Listing
April 2018

Increased resting-state brain entropy in Alzheimer's disease.

Neuroreport 2018 03;29(4):286-290

Institutes of Psychological Sciences.

Entropy analysis of resting-state functional MRI (R-fMRI) is a novel approach to characterize brain temporal dynamics and facilitates the identification of abnormal brain activity caused by several disease conditions. However, Alzheimer's disease (AD)-related brain entropy mapping based on R-fMRI has not been assessed. Here, we measured the sample entropy and voxel-wise connectivity of the network degree centrality (DC) of the intrinsic brain activity acquired by R-fMRI in 26 patients with AD and 26 healthy controls. Compared with the controls, AD patients showed increased entropy in the middle temporal gyrus and the precentral gyrus and also showed decreased DC in the precuneus. Moreover, the magnitude of the negative correlation between local brain activity (entropy) and network connectivity (DC) was increased in AD patients in comparison with healthy controls. These findings provide new evidence on AD-related brain entropy alterations.
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http://dx.doi.org/10.1097/WNR.0000000000000942DOI Listing
March 2018

Examination of the validity of the atlas-informed approach to functional parcellation: a resting functional MRI study.

Neuroreport 2017 Aug;28(11):649-653

aDepartment of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University bZhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China cDepartment of Psychiatry, Dajia Lee's General Hospital, Lee's Medical Corporation, Taichung, Taiwan.

With the advancement in MRI, functional parcellation (FP) of brain structure(s) has become an important topic. However, the large number of voxels is a major obstacle. A-priori partitioning of the brain into several regions of interest (ROIs) is the main data-reduction strategy to simplify brain informatics. This study aims to examine the validity of ROI-based approach to FP by exploring the concordance of the relative distance structures between voxel-wise (raw data) and atlas-informed analyses. Structural and resting state functional MRI (rfMRI) scans of 26 right-handed healthy individuals were selected from the Rockland dataset. Four target regions were included in the analyses, that is, left and right thalamus and amygdala. For each voxel in the target region, four classes of correlation maps (sampling strategies) were constructed from the rfMRI: whole brain, cortex, 150 ROIs, and 70 ROIs (ROIs are informed by anatomical atlases). The relative distance metric between two different voxels was defined as the mean absolute difference of their associated correlation maps. Considering all the possible pairs of voxels in a target region, the relative distance structure was derived and stored in a matrix (distance map). For every target region, the distance maps were very similar across the four classes of sampling strategies, with the grand mean correlation coefficient reaching 0.95. The results confirm the validity of previous ROI-based analyses of rfMRI data in FP. The rationale and limitation are discussed and an analytic strategy of whole-brain FP is proposed.
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http://dx.doi.org/10.1097/WNR.0000000000000808DOI Listing
August 2017

Linking graph features of anatomical architecture to regional brain activity: A multi-modal MRI study.

Neurosci Lett 2017 06 4;651:123-127. Epub 2017 May 4.

Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou 310015, China. Electronic address:

Background: Previous empirical research has treated regional neural responses and network architecture separately. However, anecdotal reports have suggested a close relationship between the two. This study aims to investigate the influence of structural connectivity on regional spontaneous activities.

Methods: Datasets of structural magnetic resonance imaging (sMRI), resting state functional MRI (rs-fMRI) and diffusion weighted imaging (DWI) of 36 right-handed healthy subjects (average age 27.4) were selected from the NKI Rockland sample. In the sMRI data, the cerebral cortex was parcellated into 70 regions of interest (ROIs) according to an anatomical atlas. Two indices were calculated from rs-fMRI for each ROI: the regional homogeneity (ReHo) and the amplitude of low frequency fluctuation (ALFF). Diffusion tensor imaging was computed from DWI and was converted to tractography. Four graph indices of structural connectivity were retrieved from the tractography results and the 70 ROIs, as follows: nodal degree, clustering coefficient, local efficiency and betweenness centrality.

Results: ReHo values were significantly correlated with all 4 graph features, whereas ALFF values were significantly correlated with nodal degrees and clustering coefficients. Both ReHo and ALFF tended to increase with segregation (clustering coefficient and local efficiency) and decrease with centrality (nodal degree and betweenness centrality).

Discussion: Though derived from local spontaneous activities, ReHo and ALFF may reflect the network properties of the underlying anatomical architecture. The results supported the hypothesis that the properties of the network structure may shape the regional neural response profiles.
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http://dx.doi.org/10.1016/j.neulet.2017.05.005DOI Listing
June 2017

Short-term meditation induces changes in brain resting EEG theta networks.

Brain Cogn 2014 Jun 13;87:1-6. Epub 2014 Mar 13.

Department of Psychology, University of Oregon, Eugene, OR 97403, USA.

Many studies have reported meditation training has beneficial effects on brain structure and function. However, very little is known about meditation-induced changes in brain complex networks. We used network analysis of electroencephalography theta activity data at rest before and after 1-week of integrative body-mind training (IBMT) and relaxation training. The results demonstrated the IBMT group (but not the relaxation group) exhibited significantly smaller average path length and larger clustering coefficient of the entire network and two midline electrode nodes (Fz and Pz) after training, indicating enhanced capacity of local specialization and global information integration in the brain. The findings provide the evidence for meditation-induced network plasticity and suggest that IBMT might be helpful for alterations in brain networks.
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http://dx.doi.org/10.1016/j.bandc.2014.02.008DOI Listing
June 2014

Different neural manifestations of two slow frequency bands in resting functional magnetic resonance imaging: a systemic survey at regional, interregional, and network levels.

Brain Connect 2014 May 24;4(4):242-55. Epub 2014 Mar 24.

1 Center for Cognition and Brain Disorders, Hangzhou Normal University , Hangzhou, China .

Temporal and spectral perspectives are two fundamental facets in deciphering fluctuating signals. In resting state, the dynamics of blood oxygen level-dependent (BOLD) signals recorded by functional magnetic resonance imaging (fMRI) have been proven to be strikingly informative (0.01-0.1 Hz). The distinction between slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) has been described, but the pertinent data have never been systematically investigated. This study used fMRI to measure spontaneous brain activity and to explore the different spectral characteristics of slow-4 and slow-5 at regional, interregional, and network levels, respectively assessed by regional homogeneity (ReHo) and mean amplitude of low-frequency fluctuation (mALFF), functional connectivity (FC) patterns, and graph theory. Results of paired t-tests supported/replicated recent research dividing low-frequency BOLD fluctuation into slow-4 and slow-5 for ReHo and mALFF. Interregional analyses showed that for brain regions reaching statistical significance, FC strengths at slow-4 were always weaker than those at slow-5. Community detection algorithm was applied to FC data and unveiled two modules sensitive to frequency effects: one comprised sensorimotor structure, and the other encompassed limbic/paralimbic system. Graph theoretical analysis verified that slow-4 and slow-5 differed in local segregation measures. Although the manifestation of frequency differences seemed complicated, the associated brain regions can be grossly categorized into limbic/paralimbic, midline, and sensorimotor systems. Our results suggest that future resting fMRI research addressing the three above systems either from neuropsychiatric or psychological perspectives may consider using spectrum-specific analytical strategies.
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http://dx.doi.org/10.1089/brain.2013.0182DOI Listing
May 2014

Personal and impersonal stimuli differentially engage brain networks during moral reasoning.

Brain Cogn 2013 Feb 17;81(1):24-8. Epub 2012 Nov 17.

Institute of Neuroinformatics and Laboratory for Body and Mind, Dalian University of Technology, Dalian 116024, China.

Moral decision making has recently attracted considerable attention as a core feature of all human endeavors. Previous functional magnetic resonance imaging studies about moral judgment have identified brain areas associated with cognitive or emotional engagement. Here, we applied graph theory-based network analysis of event-related potentials during moral decision making to reveal the personal/impersonal distinction in the organization of functional connectivity. Our results indicated that the personal task had more larger long-range connections involved in frontal regions and the right hemisphere, and higher network efficiency of some frontal electrodes such as F2 than the impersonal. These might be related to brain resource reorganization contributing to efficient conflict resolution. These findings provide new insights into neural mechanisms of moral dilemmas.
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http://dx.doi.org/10.1016/j.bandc.2012.09.004DOI Listing
February 2013