Publications by authors named "Senning Zheng"

6 Publications

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Human spatial navigation: Neural representations of spatial scales and reference frames obtained from an ALE meta-analysis.

Neuroimage 2021 Sep 12;238:118264. Epub 2021 Jun 12.

Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China. Electronic address:

Humans use different spatial reference frames (allocentric or egocentric) to navigate successfully toward their destination in different spatial scale spaces (environmental or vista). However, it remains unclear how the brain represents different spatial scales and different spatial reference frames. Thus, we conducted an activation likelihood estimation (ALE) meta-analysis of 47 fMRI articles involving human spatial navigation. We found that both the environmental and vista spaces activated the parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area in the right hemisphere. The environmental space showed stronger activation than the vista space in the occipital and frontal regions. No brain region exhibited stronger activation for the vista than the environmental space. The allocentric and egocentric reference frames activated the bilateral PPA and right RSC. The allocentric frame showed more stronger activations than the egocentric frame in the right culmen, left middle frontal gyrus, and precuneus. No brain region displayed stronger activation for the egocentric than the allocentric navigation. Our findings suggest that navigation in different spatial scale spaces can evoke specific and common brain regions, and that the brain regions representing spatial reference frames are not absolutely separated.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118264DOI Listing
September 2021

Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury.

Brain Imaging Behav 2020 Sep 2. Epub 2020 Sep 2.

Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.

Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.
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http://dx.doi.org/10.1007/s11682-020-00378-4DOI Listing
September 2020

Open eyes and closed eyes elicit different temporal properties of brain functional networks.

Neuroimage 2020 11 7;222:117230. Epub 2020 Aug 7.

Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China. Electronic address:

The eyes are our windows to the brain. There are differences in brain activity between people who have their eyes closed (EC) and eyes open (EO). Previous studies focused on differences in brain functional properties between these eyes conditions based on an assumption that brain activity is a static phenomenon. However, the dynamic nature of the brain activity in different eyes conditions is still unclear. In this study, we collected resting-state fMRI data from 21 healthy subjects in the EC and EO conditions. Using a sliding time window approach and a k-means clustering algorithm, we calculated the temporal properties of dynamic functional connectivity (dFC) states in the eyes conditions. We also used graph theory to estimate the dynamic topological properties of functional networks in the two conditions. We detected two dFC states, a hyper-connected State 1 and a hypo-connected State 2. We showed the following results: (i) subjects in the EC condition stayed longer in the hyper-connected State 1 than those in the EO; (ii) subjects in the EO condition stayed longer in the hypo-connected State 2 than those in the EC; and (iii) the dFC state transformed into the other state more frequently during EC than during EO. We also found the variance of the characteristic path length was higher during EC than during EO in the hyper-connected State 1. These results indicate that brain activity may be more active and unstable during EC than during EO. Our findings may provide insights into the dynamic nature of the resting-state brain and could be a useful reference for future rs-fMRI studies.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117230DOI Listing
November 2020

Abnormal intrinsic brain functional network dynamics in unmedicated depressed bipolar II disorder.

J Affect Disord 2019 06 1;253:402-409. Epub 2019 May 1.

Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute of Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China. Electronic address:

Background: Previous studies analyzed brain functional connectivity (FC) based on resting-state fMRI (RS-fMRI) data to reveal the neuropathology of bipolar disorder (BD) and suggested that their FC alterations are at widespread network-level. However, few studies have analyzed the dynamic functional network connectivity (dFNC) in BD. Thus, we aimed to reveal the dFNC properties of BD in this study.

Methods: The RS-fMRI data were collected from 51 unmedicated depressed BD II patients and 50 healthy controls. We analyzed the dFNC properties by using an independent component analysis, sliding window correlation, k-means clustering, and graph theory methods.

Results: The intrinsic brain FNC could be clustered into three configuration states, one with sparse connections between all functional networks (State 1), another with negative correlations between the salience network, cerebellum, basal ganglia and the sensory networks (State 2), and a third with negative correlations between the default mode network and the other functional networks (State 3). The BD patients had increased time in State 2, decreased time in State 3, and increased transition number between states. And the time spent in State 2 was positively correlated with the HDRS24 score in the BD patients. In addition, the BD patients had increased dynamic variance in the small-world properties of FNC.

Limitations: This study did not examine data from BD patients in other episodes and other BD types.

Conclusions: This study detected abnormal dFNC properties in BD, which indicated their FNC unstability and provided new insights into the neuropathology of their affective and cognitive deficits.
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http://dx.doi.org/10.1016/j.jad.2019.04.103DOI Listing
June 2019

Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple-network model.

Psychol Med 2020 02 14;50(3):465-474. Epub 2019 Mar 14.

School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou510631, China.

Background: Previous studies have analyzed brain functional connectivity to reveal the neural physiopathology of bipolar disorder (BD) and major depressive disorder (MDD) based on the triple-network model [involving the salience network, default mode network (DMN), and central executive network (CEN)]. However, most studies assumed that the brain intrinsic fluctuations throughout the entire scan are static. Thus, we aimed to reveal the dynamic functional network connectivity (dFNC) in the triple networks of BD and MDD.

Methods: We collected resting state fMRI data from 51 unmedicated depressed BD II patients, 51 unmedicated depressed MDD patients, and 52 healthy controls. We analyzed the dFNC by using an independent component analysis, sliding window correlation and k-means clustering, and used the parameters of dFNC state properties and dFNC variability for group comparisons.

Results: The dFNC within the triple networks could be clustered into four configuration states, three of them showing dense connections (States 1, 2, and 4) and the other one showing sparse connections (State 3). Both BD and MDD patients spent more time in State 3 and showed decreased dFNC variability between posterior DMN and right CEN (rCEN) compared with controls. The MDD patients showed specific decreased dFNC variability between anterior DMN and rCEN compared with controls.

Conclusions: This study revealed more common but less specific dFNC alterations within the triple networks in unmedicated depressed BD II and MDD patients, which indicated their decreased information processing and communication ability and may help us to understand their abnormal affective and cognitive functions clinically.
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http://dx.doi.org/10.1017/S003329171900028XDOI Listing
February 2020

The impact of negative mood state on sleep-related attentional bias in insomnia.

J Sleep Res 2019 04 23;28(2):e12748. Epub 2018 Aug 23.

School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for the Study of Applied Psychology and MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou, China.

Sleep-related attentional bias is thought to play a role in the maintenance of insomnia. However, this concept has been questioned by several studies that did not show the presence of sleep-related attentional bias in clinical insomnia or poor sleepers. Our goal in the present study was to test whether the mood state of individuals with insomnia affects the presence of sleep-related attentional bias. To this end, 31 individuals with insomnia and 34 good sleepers were randomly assigned to a negative mood-inducing condition or a control condition. They then completed a visual probe task with three types of pictorial stimuli (general threat, sleep-related negative pictures and sleep-related positive pictures). Vigilance, maintenance and the overall bias indexes were calculated based on the reaction time. We found individuals with insomnia only showed a greater overall bias compared with good sleepers following a negative mood induction, regardless of the pictures presented. In addition, we found that a negative mood state was significantly correlated with the overall attentional bias in good sleepers but not in individuals with insomnia. These findings suggest that sleep-related attentional bias in insomnia can be modulated by mood state. This effect may reflect the dysregulation of top-down attentional control in individuals with insomnia.
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http://dx.doi.org/10.1111/jsr.12748DOI Listing
April 2019
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