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The critical brain hypothesis suggests that efficient neural computation can be achieved through critical brain dynamics. However, the relationship between human cognitive performance and scale‐free brain dynamics remains unclear. In this study, we investigated the whole‐brain avalanche activity and its individual variability in the human resting‐state functional magnetic resonance imaging (fMRI) data. We showed that though the group‐level analysis was inaccurate because of individual variability, the subject wise scale‐free avalanche activity was significantly associated with maximal synchronization entropy of their brain activity. Meanwhile, the complexity of functional connectivity, as well as structure–function coupling, is maximized in subjects with maximal synchronization entropy. We also observed order–disorder phase transitions in resting‐state brain dynamics and found that there were longer times spent in the subcritical regime. These results imply that large‐scale brain dynamics favor the slightly subcritical regime of phase transition. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance and found that these regions were located in the prefrontal cortex and inferior parietal cortex, which were believed to be important nodes of brain networks underlying human intelligence. Our results reveal the possible role that avalanche criticality plays in cognitive performance and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.

A recent study by Witvliet et al. reconstructed the entire brain connectome for eight Caenorhabditis elegans spanning from birth to adulthood and described how synapse changes shape the connectome topology during development. Their data suggest some convergent developmental principles in connectome maturation between C. elegans and humans.

Criticality is considered a dynamic signature of healthy brain activity that can be measured on the short-term timescale with neural avalanches and long-term timescale with long-range temporal correlation (LRTC). It is unclear how the brain dynamics change in adult moyamoya disease (MMD). We used BOLD-fMRI for LRTC analysis from 16 hemorrhagic (HMMD) and 34 ischemic (IMMD) patients and 25 healthy controls. Afterwards, they were examined by EEG recordings in the eyes-closed (EC), eyes-open (EO), and working memory (WM) states. The EEG data of 11HMMDand 13IMMDpatients and 21 healthy controls were in good quality for analysis. Regarding the 4 metrics of neural avalanches (e.g., size (α), duration (β),κvalue, and branching parameter (σ)), both MMD subtypes exhibited subcritical states in the EC state. When switching to the WM state,HMMDremained inactive, whileIMMDsurpassed controls and became supercritical (p<0.05). Regarding LRTC, the amplitude envelope in the EC state was more analogous to random noise in the MMD patients than in controls. During state transitions, LRTC decreased sharply in the controls but remained chaotic in the MMD individuals (p<0.05). The spatial LRTC reduction distribution based on both EEG and fMRI in the EC state implied that, compared with controls, the two MMD subtypes might exhibit mutually independent but partially overlapping patterns. The regions showing decreased LRTC in both EEG and fMRI were the left supplemental motor area ofHMMDand right pre-/postcentral gyrus and right inferior temporal gyrus ofIMMD. This study not only sheds light on the decayed critical dynamics of MMD in both the resting and task states for the first time but also proposes several EEG and fMRI features to identify its two subtypes.

The critical brain hypothesis suggests that efficient neural computation can be realized through dynamics of the brain characterized by scale-free avalanche activities. However, the relation between human cognitive performance and the avalanche criticality in large-scale brain networks remains unclear. In this study, we analyzed the mean synchronization and synchronization entropy of blood oxygenation level signals from resting-state fMRI. We found that the scale-free avalanche activity was associated with intermediate synchronization and maximal synchronization entropy. The complexity of functional connectivity, as well as structure-function coupling, is maximized by criticality, which is consistent with theoretical predictions. We observed order-disorder phase transitions in resting-state brain dynamics and found that there were longer times spent in the subcritical regime. These results support the hypothesis that large-scale brain networks lie in the vicinity of a critical point. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance, and found these regions were located in the prefrontal cortex and inferior parietal cortex, which are believed to be important nodes of brain networks underlying human intelligence. Our results reveal the role that avalanche criticality plays in cognitive performance, and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.

Criticality is considered a dynamic signature of healthy brain activity that can be measured on the short-term timescale with neural avalanches and long-term timescale with long-range temporal correlation (LRTC). It is unclear how the brain dynamics change in moyamoya disease (MMD). We used BOLD-fMRI for LRTC analysis from 16 hemorrhagic (HMMD) and 35 ischemic (IMMD) patients, and 26 healthy controls. Besides, 11 HMMD, 13 IMMD, and 21 controls of the cohort completed EEG experiments in the eyes-closed (EC), eyes-open (EO), and working-memory (WM) states. Regarding 4 metrics of neural avalanches, both MMD subtypes exhibited subcritical states in the EC state. When switching to the WM state, HMMD remained inactive, while IMMD surpassed controls and became supercritical (P

The structural, elastic, piezoelectric and electronic properties of the orthorhombic phase KNbO3 and (BaTiO3, LiTaO3)-modified KNbO3 were investigated by first-principles calculations. The results show that the modifications have effects on the elastic properties of KNbO3 and strengthen the anisotropy. Born effective charge shows that piezoelectricity derived from the interaction between O-Nb atoms. Piezoelectric constant has been significantly improved by 3∼5 times with the modifications of BaTiO3 or LiTaO3. This study may provide a theoretical insight of KNbO3 and a better understanding of (BaTiO3, LiTaO3)-modified KNbO3 for their piezoelectricity.