Dr. Zhang received her Ph.D. degree in 2019 in Biomedical Engineering from Tsinghua University School of Medicine. She was a Visiting Student Researcher in the Radiology Department at Stanford in 2017-2018. Her dissertation research focused on identifying neuroimaging markers for depression vulnerability through fMRI and simultaneous fPET-fMRI.
Dr. Zhang was interested in methods development for dynamic fMRI and fPET analysis, especially in characterizing brain dynamics through resting-state fMRI in psychiatric diseases (depression and anxiety).
Dr. Zhang joined PanLab in 2020 on two projects: 1) examining human structural and functional changes relevant to drug abuse on the brain’s risk and reward circuits; 2) engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE).
Bachelor of Engineering, Capital Medical University (2013)
Doctor of Philosophy, Tsinghua University (2019)
Leanne Williams, Postdoctoral Faculty Sponsor
Reduced functional connectivity of default mode network subsystems in depression: Meta-analytic evidence and relationship with trait rumination.
2021; 30: 102570
Resting-state functional connectivity changes in the default mode network (DMN) of patients with major depressive disorder (MDD) have been linked to rumination. The DMN is divided into three subsystems: a midline Core, a dorsal medial prefrontal cortex (DMPFC) subsystem, and a medial temporal lobe (MTL) subsystem. We examined resting-state functional connectivity within and between DMN subsystems in MDD and its association with rumination. First, we conducted a meta-analysis on a large multi-site dataset of 618 MDD and 683 controls to quantify the differences in DMN subsystem functional connectivity between MDD and controls. Second, we tested the association of DMN subsystem functional connectivity and rumination in a sample of 115 unmedicated participants with symptoms of anxiety/depression and 48 controls. In our meta-analysis, only functional connectivity in the DMN Core was significantly reduced in MDD compared to controls (g = -0.246, CI = [-0.417; -0.074], pFDR = 0.048). Functional connectivity in the DMPFC subsystem and between the Core and DMPFC subsystems was slightly reduced but not significantly (g = -0.162, CI = [-0.310; -0.013], pFDR = 0.096; g = -0.249, CI = [-0.464; -0.034], pFDR = 0.084). Results were heterogeneous across sites for connectivity in the Core and between Core and DMPFC (I2 = 0.348 and I2 = 0.576 respectively). Prediction intervals consistently encompassed 0. In the independent sample we collected, functional connectivity within the DMN Core, DMPFC and between Core and DMPFC was not reduced in MDD compared to controls (all pFDR > 0.05). Trait rumination did not predict connectivity within and between DMN subsystems (all pFDR > 0.05). We conclude that MDD as a diagnostic category shows slightly reduced functional connectivity within the DMN Core, independent of illness duration, treatment, symptoms and trait rumination. However, this effect is small, highly variable and heterogeneous across samples, so that we could only detect it at the meta-analytic level, with a sample size of several hundreds. Our results indicate that reduced Core DMN connectivity has significant limitations as a potential clinical or prognostic marker for the diagnosis of MDD and might be more relevant to consider as a characteristic distinguishing a subgroup of individuals within this diagnostic category.
View details for DOI 10.1016/j.nicl.2021.102570
View details for PubMedID 33540370
Deep learning-based MR fingerprinting ASL ReconStruction (DeepMARS)
MAGNETIC RESONANCE IN MEDICINE
2020; 84 (2): 1024–34
To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF-ASL) perfusion maps using deep learning.A fully connected neural network, denoted as DeepMARS, was trained using simulation data and added Gaussian noise. Two MRF-ASL models were used to generate the simulation data, specifically a single-compartment model with 4 unknowns parameters and a two-compartment model with 7 unknown parameters. The DeepMARS method was evaluated using MRF-ASL data from healthy subjects (N = 7) and patients with Moymoya disease (N = 3). Computation time, coefficient of determination (R2 ), and intraclass correlation coefficient (ICC) were compared between DeepMARS and conventional dictionary matching (DM). The relationship between DeepMARS and Look-Locker PASL was evaluated by a linear mixed model.Computation time per voxel was <0.5 ms for DeepMARS and >4 seconds for DM in the single-compartment model. Compared with DM, the DeepMARS showed higher R2 and significantly improved ICC for single-compartment derived bolus arrival time (BAT) and two-compartment derived cerebral blood flow (CBF) and higher or similar R2 /ICC for other parameters. In addition, the DeepMARS was significantly correlated with Look-Locker PASL for BAT (single-compartment) and CBF (two-compartment). Moreover, for Moyamoya patients, the location of diminished CBF and prolonged BAT shown in DeepMARS was consistent with the position of occluded arteries shown in time-of-flight MR angiography.Reconstruction of MRF-ASL with DeepMARS is faster and more reproducible than DM.
View details for DOI 10.1002/mrm.28166
View details for Web of Science ID 000510713500001
View details for PubMedID 32017236
Dynamic changes in thalamic connectivity following stress and its association with future depression severity
BRAIN AND BEHAVIOR
2019; 9 (12): e01445
Tracking stress-induced brain activity and connectivity dynamically and examining activity/connectivity-associated recovery ability after stress might be an effective way of detecting stress vulnerability.Using two widely used stress paradigms, a speech task (social stress) and a mathematical calculation task (mental loading stress), we examined common changes in regional homogeneity (ReHo) and functional connectivity (FC) before, during, and after the two stressful tasks in thirty-nine college students. A counting breath relaxation task was employed as a contrast task. ReHo and FC were compared between subjects with higher versus lower depression symptoms (assessed by the Beck Depression Inventory, BDI). We developed a recovery index (RI) based on dynamic changes of ReHo/FC to evaluate individuals' ability to recover from a stressful state. To assess RI's usefulness in predicting future depression severity, BDI was also measured at one-year follow-up.Our results revealed a ReHo decrease after both stressful tasks and a ReHo increase after the relaxation task in bilateral thalamus. The ReHo decrease after both stressful tasks was more significant in the higher BDI than the lower BDI group. Higher ReHo RI of the right thalamus in the higher BDI groups was significantly correlated with lower BDI severity at one-year follow-up. Bilateral thalamus also showed increased FC with the default mode network and decreased FC with the executive control network after the stressful tasks.These findings highlight the importance of tracking resting activity and connectivity of thalamus dynamically for detecting stress vulnerability.
View details for DOI 10.1002/brb3.1445
View details for Web of Science ID 000492395500001
View details for PubMedID 31651099
View details for PubMedCentralID PMC6908855
Downward cross-modal plasticity in single-sided deafness
2019; 197: 608–17
The auditory cortex has been shown to participate in visual processing in individuals with complete auditory deprivation. However, it remains unclear whether partial hearing deprivation like single-sided deafness (SSD) leads to similar cross-modal plasticity. To investigate this, we enrolled individuals with long-term SSD, into functional MRI scans under resting-state and a visuo-spatial working memory task. Contrary to previous findings in bilateral deafness, our study revealed decreased activation in the auditory cortex in both left (LSSD) and right (RSSD) single-sided deafness compared to normal hearing controls, with statistical significance in RSSD. The degree of involvement was correlated with residual hearing ability in RSSD. These observations suggest that SSD can lead to a downward cross-modal plasticity: the more hearing ability lost, the fewer brain resources in the auditory cortex can be applied to visual tasks. In addition, the fronto-parietal cortex was observed to be less activated during the visual task in RSSD while the resting-state fMRI revealed increased functional connectivity between the fronto-parietal cortex and the auditory cortex, suggesting fronto-parietal resources may be recruited less by vision but more by hearing. The LSSD showed a similar alteration trend with RSSD, but without statistical significance. Together these findings may indicate that when hearing is partially deprived in SSD, there may be redistribution for brain resources between hearing and vision, and vision tends to allocate less resources. Our findings in this pilot study of unilateral auditory-deprived individuals enrich the understanding of cross-modal plasticity in the brain.
View details for DOI 10.1016/j.neuroimage.2019.05.031
View details for Web of Science ID 000472161500056
View details for PubMedID 31091475
Exploring common changes after acute mental stress and acute tryptophan depletion: Resting-state fMRI studies
JOURNAL OF PSYCHIATRIC RESEARCH
2019; 113: 172–80
Stress and low serotonin levels are important biological factors in depression and anxiety etiologies. Although studies indicate that low serotonin levels, stress, and other factors may interact in depression/anxiety psychopathology, few studies have investigated the potentially shared neural substrates. We conducted resting-state fMRI scans pre- and post-stress task, and under control and tryptophan depletion condition, to explore the common changes induced by acute mental stress (AMS) and acute tryptophan depletion (ATD). The present study targeted regions within core brain networks - default mode network, salience network, executive control network, and emotion network - reported altered in AMS and ATD, and used regional homogeneity (ReHo) and functional connectivity (FC) analyses to explore their overlapped effects. We additionally examined the relationships among core neural networks - operationalized as an index of resource allocation bias that quantifies the shift from internal to external modes of processing. We found both manipulations induced increased ReHo of the amygdala and decreased ReHo of the posterior cingulate cortex (PCC). The PCC-amygdala FC was negatively correlated with the change of negative affect, whereas the right dorsolateral prefrontal cortex and right anterior insula FC was positively associated with anxiety level. In addition, we found that a greater shift to an external mode was correlated with higher anxiety level under both conditions. Common changes induced by acute mental stress and acute tryptophan depletion confirmed our hypothesis that AMS and ATD induce changes in common neural pathways, which in turn might mark vulnerability to depression and anxiety.
View details for DOI 10.1016/j.jpsychires.2019.03.025
View details for Web of Science ID 000467670000025
View details for PubMedID 30959228
Physical exercise increases involvement of motor networks as a compensatory mechanism during a cognitively challenging task
INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY
2018; 33 (8): 1153–59
Neuroimaging studies suggest that older adults may compensate for declines in cognitive function through neural compensation and reorganization of neural resources. While neural compensation as a key component of cognitive reserve is an important factor that mediates cognitive decline, the field lacks a quantitative measure of neural compensatory ability, and little is known about factors that may modify compensation, such as physical exercise.Twenty-five healthy older adults participated in a 6-week dance training exercise program. Gait speed, cognitive function, and functional magnetic resonance imaging during a challenging memory task were measured before and after the exercise program. In this study, we used a newly proposed data-driven independent component analysis approach to measure neural compensatory ability and tested the effect of physical exercise on neural compensation through a longitudinal study.After the exercise program, participants showed significantly improved memory performance in Logical Memory Test (WMS(LM)) (P < .001) and Rey Auditory Verbal Learning Test (P = .001) and increased gait speed measured by the 6-minute walking test (P = .01). Among all identified neural networks, only the motor cortices and cerebellum showed greater involvement during the memory task after exercise. Importantly, subjects who activated the motor network only after exercise (but not before exercise) showed WMS(LM) increases.We conclude that physical exercise improved gait speed, cognitive function, and compensatory ability through increased involvement of motor-related networks.
View details for DOI 10.1002/gps.4909
View details for Web of Science ID 000438028900019
View details for PubMedID 29851152
Dual-TRACER: High resolution fMRI with constrained evolution reconstruction
2018; 164: 172–82
fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm2) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection.
View details for DOI 10.1016/j.neuroimage.2017.02.087
View details for Web of Science ID 000417972000016
View details for PubMedID 28263924