Inhibitory Decay and Supercritical Brain Dynamics During Sleep Deprivation Dai Zhang, Liqin Zhou, Rong Wang, Yuehua Han, Zhentao Zuo, et al. Advanced Science, 2026 Sleep deprivation (SD) changes brain‐wide dynamics, but the circuit‐level perturbation that can generate this systems‐level shift remains unclear. We scanned 26 participants at seven time points across 36 h of continuous wakefulness and assessed criticality from resting‐state functional Magnetic Resonance Imaging (rs‐fMRI) blood‐oxygen‐level‐dependent (BOLD) signals using neuronal avalanche metrics (branching ratio and mean avalanche size). The branching ratio increased from 0.98 at baseline to 1.08 after 36 h, indicating a progressive shift from near‐critical to supercritical propagation. Interestingly, the shift was heterogeneous. Visual and sensorimotor networks showed the largest deviations, whereas the limbic network remained close to criticality. Criticality changes tracked accumulated subjective sleep pressure but were largely dissociated from psychomotor vigilance lapses. SD also reshaped functional network organization, with the functional connectivity (FC) degree distribution shifting toward more high‐degree nodes. In a recurrent excitatory–inhibitory network model, gamma‐band power provided an interpretable proxy for effective gain and inhibitory control. Using this proxy, selectively reducing inhibitory efficacy was sufficient to capture the direction of the near‐critical‐to‐supercritical drift and a limbic‐like resilience pattern, supporting inhibitory decay as a plausible candidate circuit‐level mechanism linking SD to large‐scale propagation instability.
The distinct development of stimulus and response serial dependence Liqin Zhou, Yujie Liu, Yuhan Jiang, Wenbo Wang, Pengfei Xu, et al. Psychonomic Bulletin and Review, 2024 Serial dependence (SD) is a phenomenon wherein current perceptions are biased by the previous stimulus and response. This helps to attenuate perceptual noise and variability in sensory input and facilitates stable ongoing perceptions of the environment. However, little is known about the developmental trajectory of SD. This study investigates how the stimulus and response biases of the SD effect develop across three age groups. Conventional analyses, in which previous stimulus and response biases were assessed separately, revealed significant changes in the biases over time. Previous stimulus bias shifted from repulsion to attraction, while previous response bias evolved from attraction to greater attraction. However, there was a strong correlation between stimulus and response orientations. Therefore, a generalized linear mixed-effects (GLME) analysis that simultaneously considered both previous stimulus and response, outperformed separate analyses. This revealed that previous stimulus and response resulted in two distinct biases with different developmental trajectories. The repulsion bias of previous stimulus remained relatively stable across all age groups, whereas the attraction bias of previous response was significantly stronger in adults than in children and adolescents. These findings demonstrate that the repulsion bias towards preceding stimuli is established early in the developing brain (at least by around 10 years old), while the attraction bias towards responses is not fully developed until adulthood. Our findings provide new insights into the development of the SD phenomenon and how humans integrate two opposing mechanisms into their perceptual responses to external input during development.
Reviving Bistable Perception in Patients With Depression by Decreasing the Overestimation of Prior Precision Wenbo Wang, Changbo Zhu, Ting Jia, Meidan Zu, Yandong Tang, et al. Cognitive Science, 2024 Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin‐targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top‐down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.
Leading basic modes of spontaneous activity drive individual functional connectivity organization in the resting human brain Xi Chen, Haoda Ren, Zhonghua Tang, Ke Zhou, Liqin Zhou, et al. Communications Biology, 2023 Spontaneous 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.
