Dynamic characteristics of brain networks in patients with obsessive-compulsive disorder based on naturalistic paradigm.

Spatiotemporal reconfiguration of functional networks by transcranial magnetic stimulation in Alzheimer's disease.

Rich-club connections dynamics are associated with long-term outcomes in major depressive disorder.

Enhanced cortical connectivity during passive robotic-assisted gait training in individuals with spinal cord injury: An EEG study.

A statistics-based simplification method to the Distribution Network Reconfiguration problem for large-scale networks

Dissociable Neurocognitive Mechanisms of State and Trait Anxiety in Working Memory: Threat-Induced Alterations in Decision Dynamics and Attenuation of Large-Scale Network Reconfiguration.

Role expansion of radiological technologists in intraoperative fluoroscopy in Japan: A simulation-based social network analysis of interprofessional collaborative structure.

From microstates to macroscales: A critical review of maximum entropy modeling and energy landscape analysis in functional MRI.

Adaptive reconfiguration of prefrontal networks during prolonged cognitive interference: Evidence from fNIRS.

Ultrafast and stable steady-state temperature perception is critically important for emerging applications such as electronic skin and intelligent human-machine interfaces, yet it remains a big challenge for flexible temperature sensors due to the difficulty in rapidly establishing and maintaining stable thermal gradients. Here, we propose a conductive/thermoelectric network reconfiguration strategy that enables both rapid formation of stable temperature differentials in flexible thermoelectric sensors. By in situ welding preassembled single-walled carbon nanotube frameworks with poly(3,4-ethylenedioxythiophene) on a porous melamine foam scaffold, an ion-free and continuous thermoelectric network has been constructed, substantially optimizing thermal conduction and stabilizing carrier migration pathways. The resulting sensor exhibits an ultrafast first-order response time of 58.6 ms and reaches steady state within 430 ms, even under a large temperature difference of 71.7 K, while maintaining highly stable output with negligible signal decay over prolonged operation. Moreover, the reconfigured network enables decoupled and simultaneous temperature-pressure sensing, eliminating the response-speed mismatch in dual-modal tactile systems. Benefiting from the ultrafast and stable temperature readout, the sensor achieves accurate respiratory monitoring and reliable thermal feature recognition, demonstrating strong potential for high-performance multimodal tactile sensing and intelligent health monitoring.

Interpersonal neural synchrony in joint music-making and conversation: toward an integrative Marr-level account.

ABSTRACT This article examines the conflicting narratives surrounding the origin and evolution of the Lakurawa terrorist group, tracing its transformation from a localised, community-based defence and intelligence network into a transnational militant organisation operating across the Nigeria–Niger borderlands. A central question of this inquiry is whether Lakurawa represents a genuinely new insurgent formation or a strategic reconfiguration of entrenched militant networks within Nigeria’s borderlands. While military analyses focus on immediate security needs and the justification of urgent actions, academic perspectives examine the deeper structural, historical, and social factors shaping the group’s evolution. I argue that the divergence between military and academic interpretations of Lakurawa’s emergence does not indicate empirical inconsistency but instead reflects distinct epistemic orientations and institutional logics. Using a constructivist approach, this study relies on triangulated secondary sources, including open-source intelligence, academic literature, community narratives, and regional conflict analyses. While primary data collection was not feasible due to the precarious security conditions in the study area, the research systematically interrogates contrasting interpretations of Lakurawa’s origins, strategic behaviour, and ideology, and the responses of state and community actors. The findings illuminate how localised informal defence structures can evolve into perceived transnational threats and the implications of such transformations for peacebuilding.

Understanding how functional brain networks in resting state configurations reorganize to perform cognitive tasks is critical for uncovering the nature and mechanisms underlying network dysconnectivity in psychiatric disorders. We applied energy landscape analysis (ELA), a statistical physics-based computational approach, to functional MRI data from 23 adolescent-onset schizophrenia (AOS) and 44 healthy control (HC) subjects, acquired during rest followed by executive function task. ELA maps brain activity into distinct network states and quantifies how the brain transitions among them, capturing differences in stability of network states and transition complexity across conditions. AOS and HC showed markedly different condition-dependent patterns of brain state organization and dynamics. At rest, AOS exhibited reduced dynamical complexity compared to HC (7 vs. 14 stable states) that reversed during the task with more than 2-fold increase in accessible but rarely occupied brain states, while HC showed an opposite pattern. These results suggest that cognitive demands unmask latent fragmentation of the energy landscape, comprising a proliferation of accessible but rarely occupied states not apparent at rest, in AOS. State occupancy analysis revealed a small number of dominant states accounting for the majority of brain activity time, with AOS showing greater persistence in the fully-active DMN state during task performance compared to HC. These findings suggest that the rest-to-task transition features fundamentally different neural dynamics in AOS compared to HC. Combined analysis of resting fMRI and task-induced brain dynamics revealed neural factors that may contribute to cognitive dysfunction and psychiatric symptoms in schizophrenia, with important implications for development of biomarkers and treatment targets.

Structural pathways of the brain facilitate functional communication, and their disruption in preclinical Alzheimer's disease may reflect network vulnerability and compensatory brain maintenance. However, it remains unclear how early amyloid-β affects structure-function alignment, whether effects are explained by functional network organisation, how they relate to cognition, and which biological processes contribute to their development. We included 460 older adults without dementia from AMYPAD-PNHS with functional MRI, diffusion MRI, and amyloid-β PET. Structure-function coupling was quantified using the structural-decoupling index (SDI) at global, sub-network, and regional scales. Linear models investigated the effect of amyloid-β burden on SDI. Mediation analyses evaluated whether functional graph topology explained amyloid-associated SDI effects and whether SDI mediated the relationship between amyloid-β burden and cognition. Regional gene expression data were integrated to assess transcriptomic determinants of amyloid-related structure-function coupling. Amyloid-positive individuals exhibit higher global SDI, driven by visual cortices. Mediation analyses demonstrate that amyloid-related SDI alterations are explained by reductions in local clustering, indicating less segregated processing. Despite higher SDI in amyloid-positive individuals, elevated SDI in visual regions mitigates the negative effect of amyloid-β burden on cognition. Amyloid-related SDI changes correlate with genes associated with amyloid-β metabolism, microglial activation, and synaptic remodelling. Early amyloid-β pathology is associated with decoupling of brain structure and function, primarily in visual cortices, mediated by network reconfiguration and shaped by regional molecular architecture. These findings suggest that lower structure-function coupling may represent a compensatory mechanism in preclinical Alzheimer's disease and highlight SDI as a biomarker for stratification and monitoring in prevention trials.

The escalating demand for intelligent stealth systems necessitates a paradigm shift from static absorbers to dynamic devices with autonomous and reversible control. Addressing challenges of fixed structure-frequency relationship, we draw direct inspiration from the adaptive coloration of cephalopod skin, which achieves dynamic stealth through reconfiguration of subcutaneous photonic structures. Following this principle, we design a programmable electromagnetic switch via a 4D-printing strategy, which promotes R6M matrix mixed with carbonyl iron directional arrangement. This design enables precise morphological control of absorbers based on a thermally convective temperature gradient by inducing metastable configurations of liquid crystal elastomer. The macroscopically topological reconfiguration and microscopical changes of percolation network both contribute to a dramatic, reversible modulation of electromagnetic characteristics. Consequently, the resonant frequency can precisely convert within X and Ku bands, with the minimum reflection loss enhanced from -30.22to -61.4dB and the effective bandwidth enlarged from 8.52 to 11.37GHz. Notably, this system exhibits excellent cyclic-stability over 100 times, establishing a robust electromagnetic switches. Our work establishes a deterministic mapping between thermal excitation, metastructure geometry, and electromagnetic behaviors, enabling precise and predictable tuning. This paradigm offers inspiration for next-generation electromagnetic protection, with clear potential for integration into adaptive cloaking systems.

Adult hippocampal neurogenesis is a metabolically demanding process requiring tight coordination between energy production and biosynthetic flux. Although voluntary running is a potent stimulus for this plasticity, the metabolic landscape sustaining the neurogenic niche remains incompletely defined. Using untargeted gas chromatography/mass spectrometry-based metabolomics to characterize the hippocampal metabolome of mice following eight weeks of voluntary running, we identified metabolic changes consistent with coordinated metabolic reprogramming that suggest an adaptive metabolic stress response. A significant catabolic shift, marked by depletion of glutamic and aspartic acids, is associated with increased bioenergetic utilization and possible integration of neurotransmitter-derived substrates into central carbon metabolism. The exercise-induced elevation of CoA-related metabolites and tricarboxylic acid cycle intermediates is indicative of increased mitochondrial bioenergetic demand. Simultaneously, elevated nitrogenous metabolites, such as asparagine and glycine, coincide with increased availability of biosynthetic precursors for nucleotide synthesis, redox balance, and structural remodeling linked to neurogenesis. Enrichment of one-carbon metabolism is compatible with integration of metabolic pathways involved in biosynthetic and regulatory processes related to neurogenic remodeling. Together, these findings align with the interpretation that voluntary running may act as a metabolic hormetic stimulus, linked to reconfiguration of hippocampal metabolic networks to support a permissive environment for neurogenic plasticity and cognitive resilience.

The rapid advances in detection technologies have raised greater demands on microwave-steady materials, particularly for curved surfaces and movable components of aircraft that are highly susceptible to detection. However, electromagnetic wave (EMW) absorbers based on composite metastructures or metal-backed resonant cavities often suffer from intrinsic rigidity, resulting in poor conformability to complex surfaces and consequently compromised microwave-absorption performance. Herein, inspired by the locally segmented deformability of soft-bodied organisms, a deformation-adaptive EGaIn/CIP-TPU nanofibrous absorber is developed through liquid-metal confinement within electrospun nanofibers, which integrates segmented fiber network reconfiguration with EGaIn/CIP-induced dielectric-magnetic synergistic attenuation for flexible microwave absorption. Specifically, the flexible microwave absorber delivers a minimum reflection loss (RL) of -51.4 dB at a matching thickness of 2.2 mm. Meanwhile, these absorbers exhibit elastic recovery ratios above 70% and show stable mechanical responses over 500 compression cycles. This study demonstrates an effective balance between mechanical adaptability and microwave-absorption performance, providing a promising strategy for next-generation flexible EMWA.

Liquid crystal elastomers (LCEs) are attractive for soft actuators and biomimetic systems owing to their rapid responsiveness and reversible deformations, yet achieving simultaneoushigh actuation stress and strain for complex macroscopic motions remains challenging. Herein, we report a liquid-crystalline polyurethane (LCPU)/MXene hybrid network, fabricated via in situ polymerization, that overcomes this long-standing trade-off. The flexible polydimethylsiloxane (PDMS) imparts large reversible deformability, while covalently anchored MXene simultaneously reinforce mechanical strength and enable efficient photothermal conversion, yielding robust thermal- and light-driven actuation. The dynamic hydrogen bonding network confers on-demand network reconfigurability and shape programmability within an optimal temperature window. The resulting actuators achieve a thermal-driven stress of 0.91MPa at 88% strain, while it increased to 1.58MPa under near-infrared (NIR) stimulation, yielding an exceptionally high work capacity of 546kJ m- 3. An active-passive composite actuator constructed from LCPU/MXene demonstrates programmable morphing under thermal stimuli. When employed as artificial biceps and quadriceps of robotic counterparts, these actuators perform diverse large-amplitude actuation tasks such as lifting and pushing under remote near-infrared irradiation. This thermal and light-driven LCPU/MXene system holds considerable promise as a versatile platform for artificial muscles, adaptive aerospace actuators, and related intelligent applications.

The realization of solar-charging within rechargeable batteries has been a dream of several generations of scientists, marking a transformation in sustainable energy storage. The key challenge is that the photo-rechargeable electrodes need to simultaneously possess high photovoltaic efficiency and cycling stability. Herein, through dynamic reconfiguration of sp-hybridized carbon networks via direct photoexcitation, we present nitrogen-substituted graphdiyne as a metal-free photoelectrode for integrated solar-charging in rechargeable batteries. Nitrogen-substituted graphdiyne accelerates oxygen evolution reaction kinetics by the synergistic effect of improved intermediate adsorption and hole-mediated oxidation under light excitation. Nitrogen-substituted graphdiyne-based photo-coupled positive electrodes are applicable to multiple metal||air batteries (Zn||air, Li||O2, Mg||air, Fe||air, and Al||air), including a low charging voltage of 1.33 V and 96.9% energy efficiency in Zn||air batteries, along with stability over 230 cycles at 100 mA cm-2. The Li||O2 battery achieved an efficiency of 96.3%, while Mg||air, Fe||air, and Al||air systems exhibited reduced charging voltages. This research has pioneered a class of photoelectrodes whose active sites are directly and dynamically defined by light, opening avenues for high-efficiency solar-driven energy conversion and storage.

A review of topology identification methods and applications for low voltage distribution networks