zhouliqin469@126.com
@bnu.edu.cn
School of Psychology
Beijing Normal University
RESEARCH INTERESTS
visual attention, serial dependence, Bayesian inference
Scopus Publications
Scopus Publications
Yujie LIU, Chenmiao LIU, Liqin ZHOU, and Ke ZHOU
China Science Publishing & Media Ltd.
Xi Chen, Haoda Ren, Zhonghua Tang, Ke Zhou, Liqin Zhou, Zhentao Zuo, Xiaohua Cui, Xiaosong Chen, Zonghua Liu, Yong He,et al.
Springer Science and Business Media LLC
AbstractSpontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a recently proposed eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify five leading basic modes that dominate activity fluctuations. Each mode exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. Based on theoretical modelling, we further reconstruct individual functional connectivity as the weighted superposition of coactivation patterns corresponding to these leading basic modes. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity.
Zong Meng, Qi Chen, Liqin Zhou, Liang Xu, and Antao Chen
Oxford University Press (OUP)
Abstract Attentional blink pertains to the performance of participants with a severe decline in identifying the second target presented after the first target reported correctly within 200–500 ms in a rapid serial visual presentation. The current study was conducted to investigate the neural mechanism of the effect of the distractor (D1) that immediately follows first target to attentional blink by altering whether D1 was substituted with a blank with electroencephalography recording. The results showed that D1 interfered with the attentional enhancement and working memory encoding in both single-target rapid serial visual presentation task and dual-target rapid serial visual presentation task, which were mainly manifested in delayed and attenuated P3a and diminished P3b of first target. Single-trial analysis indicated that first target and second target will compete with each other for working memory encoding resources in short lag, but not in the long lag. In addition, D1 interfered with the working memory encoding of second target under short lag rather than long lag in the dual-target rapid serial visual presentation task. These results suggested that attentional blink can be attributed to the limited working memory encoding resource, whereas the amount of available resources is subject to modulation by attention. The D1 hinders the attention enhancement of first target, thereby exacerbating attentional blink.
Dai Zhang, Ruotong Zhang, Liqin Zhou, Ke Zhou, and Chunqi Chang
Oxford University Press (OUP)
Abstract Attention deficit hyperactivity disorder (ADHD) is a chronic neuropsychiatric disease that can markedly impair educational, social, and occupational function throughout life. Behavioral deficits may provide clues to the underlying neurological impairments. Children with ADHD exhibit a larger attentional blink (AB) deficit in rapid serial visual presentation (RSVP) tasks than typically developing children, so we examined whether brain connectivity in the neural network associated with AB can predict ADHD symptoms and thus serve as potential biomarkers of the underlying neuropathology. We first employed a connectome-based predictive model analysis of adult resting-state functional magnetic resonance imaging data to identify a distributed brain network for AB. The summed functional connectivity (FC) strength within the AB network reliably predicted individual differences in AB magnitude measured by a classical dual-target RSVP task. Furthermore, the summed FC strength within the AB network predicted individual differences in ADHD Rating Scale scores from an independent dataset of pediatric patients. Our findings suggest that the individual AB network could serve as an applicable neuroimaging-based biomarker of AB deficit and ADHD symptoms.
Dai Zhang, Liqin Zhou, Anmin Yang, Shanshan Li, Chunqi Chang, Jia Liu, and Ke Zhou
Oxford University Press (OUP)
Abstract The approximate number system (ANS) is vital for survival and reproduction in animals and is crucial for constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, a neuromarker to characterize an individual’s ANS acuity is lacking, especially one based on whole-brain functional connectivity (FC). Here, based on the resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from a large sample, we identified a distributed brain network (i.e. a numerosity network) using a connectome-based predictive modeling (CPM) analysis. The summed FC strength within the numerosity network reliably predicted individual differences in ANS acuity regarding behavior, as measured using a nonsymbolic number-comparison task. Furthermore, in an independent dataset of the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network also specifically predicted individual differences in arithmetic skills, but not domain-general cognitive abilities. Therefore, our findings revealed that the identified numerosity network could serve as an applicable neuroimaging-based biomarker of nonverbal number acuity and arithmetic skills.
Liqin Zhou, Anmin Yang, Ming Meng, and Ke Zhou
American Association for the Advancement of Science (AAAS)
Recent studies found that the deep convolutional neural networks (DCNNs) trained to recognize facial identities spontaneously learned features that support facial expression recognition, and vice versa. Here, we showed that the self-emerged expression-selective units in a VGG-Face trained for facial identification were tuned to distinct basic expressions and, importantly, exhibited hallmarks of human expression recognition (i.e., facial expression confusion and categorical perception). We then investigated whether the emergence of expression-selective units is attributed to either face-specific experience or domain-general processing by conducting the same analysis on a VGG-16 trained for object classification and an untrained VGG-Face without any visual experience, both having the identical architecture with the pretrained VGG-Face. Although similar expression-selective units were found in both DCNNs, they did not exhibit reliable human-like characteristics of facial expression perception. Together, these findings revealed the necessity of domain-specific visual experience of face identity for the development of facial expression perception, highlighting the contribution of nurture to form human-like facial expression perception.
Liqin Zhou, Zhonghua Tang, Zhentao Zuo, and Ke Zhou
Oxford University Press (OUP)
Abstract Quality sleep is vital for physical and mental health. No matter whether sleep problems are a consequence of or contributory factor to mental disorders, people with psychosis often suffer from severe sleep disturbances. Previous research has shown that acute sleep deprivation (SD) can cause transient brain dysfunction and lead to various cognitive impairments in healthy individuals. However, the relationship between sleep disturbance and bistable perception remains unclear. Here, we investigated whether the bistable perception could be affected by SD and elucidated the functional brain changes accompanying SD effects on bistable perception using functional magnetic resonance imaging. We found that the 28-h SD resulted in slower perceptual transitions in healthy individuals. The reduced perceptual transition was accompanied by the decreased activations in rivalry-related frontoparietal areas, including the right superior parietal lobule, right frontal eye field, and right temporoparietal junction. We speculated that SD might disrupt the normal function of these regions crucial for bistable perception, which mediated the slower rivalry-related perceptual transitions in behavior. Our findings revealed the neural changes underlying the abnormal bistable perception following the SD. It also suggested that SD might offer a new window to understand the neural mechanisms underlying the bistable perception.
Liqin Zhou, Zonglei Zhen, Jia Liu, and Ke Zhou
Oxford University Press (OUP)
Abstract The attentional blink (AB) has been central in characterizing the limit of temporal attention and consciousness. The neural mechanism of the AB is still in hot debate. With a large sample size, we combined multiple behavioral tests, multimodal MRI measures, and transcranial magnetic stimulation to investigate the neural basis underlying the individual differences in the AB. We found that AB magnitude correlated with the executive control functioning of working memory (WM) in behavior, which was fully mediated by T1 performance. Structural variations in the right temporoparietal junction (rTPJ) and its intrinsic functional connectivity with the left inferior frontal junction (lIFJ) accounted for the individual differences in the AB, which was moderated by the executive control of working memory. Disrupting the function of the lIFJ attenuated the AB deficit. Our findings clarified the neural correlates of the individual differences in the AB and elucidated its relationship with the consolidation-driven inhibitory control process.
Liqin Zhou, Jiahui Ding, and Ke Zhou
Association for Research in Vision and Ophthalmology (ARVO)
Attentional blink (AB) speaks to a phenomenon that, when reporting two targets in a rapid serial visual presentation, the second target (T2) is often missed if it followed the first target (T1) within an interval of less than 500 ms. An interesting exception is the preserved performance of T2 at Lag 1 position (Lag-1 sparing), or even in an extended period, which recently has been termed temporal integration. Both T1 and T2 can be successfully reported but with a loss of their temporal order. The integration has been attributed to the temporal distance between the two targets. However, previous studies on temporal perception have revealed that similarity between two stimuli modulated their temporal order judgment, suggesting that temporal integration is affected by stimulus characteristics. In the present study, we investigated whether stimulus characteristics modulated temporal integration in the AB. We manipulated the categorical similarity between T1 and T2 targets and found that the order reversals were significantly higher in the same-category condition than that in the different-category condition. Our results thus provided clear evidence for the contribution of categorical similarity to the temporal integration in the AB.