B.Sc., Beijing Normal University, Zhuhai, Psychology (2013)
Ph.D., Beijing Normal University, Cognitive Neuroscience (2019)
Vinod Menon, Postdoctoral Faculty Sponsor
Network analysis reveals disrupted functional brain circuitry in drug-naive social anxiety disorder
2019; 190: 213–23
Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the "fear circuit", including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety.
View details for DOI 10.1016/j.neuroimage.2017.12.011
View details for Web of Science ID 000467540600019
View details for PubMedID 29223742
Long-term Chinese calligraphic handwriting reshapes the posterior cingulate cortex: A VBM study
2019; 14 (4): e0214917
As a special kind of handwriting with a brush, Chinese calligraphic handwriting (CCH) requires a large amount of practice with high levels of concentration and emotion regulation. Previous studies have showed that long-term CCH training has positive effects physically (induced by handwriting activities) and psychologically (induced by the state of relaxation and concentration), the latter of which is similar to the effects of meditation. The aim of this study was to investigate the long-term CCH training effect on anxiety and attention, as well as brain structure. Participants were 32 individuals who had at least five years of CCH experience and 44 controls. Results showed that CCH training benefited individuals' selective and divided attention but did not decrease their anxiety level. Moreover, the VBM analysis showed that long-term CCH training was mainly associated with smaller grey matter volumes (GMV) in the right precuneus/posterior cingulate cortex (PCC). No brain areas showed larger GMV in the CCH group than the control group. Using two sets of regions of interest (ROIs), one related to meditation and the other to handwriting, ROI analysis showed significant differences between the CCH and the control group only at the meditation-related ROIs, not at the handwriting-related ROIs. Finally, for the whole sample, the GMV of both the whole brain and the PCC were negatively correlated with selective attention and divided attention. The present study was cross-sectional and had a relatively small sample size, but its results suggested that CCH training might benefit attention and influence particular brain structure through mental processes such as meditation.
View details for DOI 10.1371/journal.pone.0214917
View details for Web of Science ID 000463314500085
View details for PubMedID 30947247
View details for PubMedCentralID PMC6448813
Long-term Chinese calligraphic handwriting training has a positive effect on brain network efficiency
2019; 14 (1): e0210962
As a visual art form, Chinese calligraphic handwriting (CCH) has been found to correlate with certain brain activity and to induce functional connectivity reorganization of the brain. This study investigated the effect of long-term CCH training on brain functional plasticity as assessed with network measures. With the resting-state fMRI data from 31 participants with at least five years of CCH training and 40 controls, we constructed brain functional networks, examined group differences at both the whole brain and modular levels, and correlated the topological characteristics with calligraphy skills. We found that, compared to the control group, the CCH group showed shorter characteristic path lengths and higher local efficiency in certain brain areas in the frontal and parietal cortices, limbic system, basal ganglia, and thalamus. Moreover, these network measures in the cingulate cortex, caudate nucleus, and thalamus were associated with CCH performance (i.e., copying and creating skills). These results suggest that long-term CCH training has a positive effect on the topological characteristics of brain networks.
View details for DOI 10.1371/journal.pone.0210962
View details for Web of Science ID 000457037500080
View details for PubMedID 30682084
View details for PubMedCentralID PMC6347361
Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns
HUMAN BRAIN MAPPING
2018; 39 (2): 902–15
The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease.
View details for DOI 10.1002/hbm.23890
View details for Web of Science ID 000419856200022
View details for PubMedID 29143409
Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory
2017; 27 (12): 5496–5508
Spatial working memory (SWM) is an important component of working memory and plays an essential role in driving high-level cognitive abilities. Recent studies have demonstrated that individual SWM is associated with global brain communication. However, whether specific network nodal connectivity, such as brain hub connectivity, is involved in individual SWM performances remains largely unknown. Here, we collected resting-state fMRI (R-fMRI) data from a large group of 130 young healthy participants and evaluated their SWM performances. A voxel-wise whole-brain network analysis approach was employed to study the relationship between the nodal functional connectivity strength (FCS) and the SWM behavioral scores and to further estimate the participation of brain hubs in individual SWM. We showed significant associations between nodal FCS and SWM performance primarily in the default mode, visual, dorsal attention, and fronto-parietal systems. Moreover, over 41% of these nodal regions were identified as brain network hubs, and these hubs' FCS values contributed to 57% of the variance of the individual SWM performances that all SWM-related regions could explain. Collectively, our findings highlight the cognitive significance of the brain network hubs in SWM, which furthers our understanding of how intrinsic brain network architectures underlie individual differences in SWM processing.
View details for DOI 10.1093/cercor/bhw317
View details for Web of Science ID 000416280200006
View details for PubMedID 28334075
Graph theoretical analysis of functional network for comprehension of sign language
2017; 1671: 55–66
Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t(24)=2.379, p=0.026), small-worldness (t(24)=2.604, p=0.016) and modularity (t(24)=3.513, p=0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action.
View details for DOI 10.1016/j.brainres.2017.06.031
View details for Web of Science ID 000409287200007
View details for PubMedID 28690129