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Latent circuit inference from heterogeneous neural responses during cognitive tasks
Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity and task variables leave unknown how heterogeneous responses arise from connectivity to drive behavior. We develop the latent circuit model, a dimensionality reduction approach in which task variables interact via low-dimensional recurrent connectivity to produce behavioral output. We apply the latent circuit inference to recurrent neural networks trained to perform a context-dependent decision-making task and find a suppression mechanism in which contextual representations inhibit irrelevant sensory responses. We validate this mechanism by confirming the behavioral effects of patterned connectivity perturbations predicted by the latent circuit model. We find similar suppression of irrelevant sensory responses in the prefrontal cortex of monkeys performing the same task. We show that incorporating causal interactions among task variables is critical for identifying behaviorally relevant computations from neural response data.
Intracellular assembly of supramolecular peptide nanostructures controlled by visible light
The complex dynamics of synthetic supramolecular systems in living cellular environments impede the correlation between the transient hierarchical species and their biological functions. Achieving this correlation demands a breakthrough that combines the precise control of supramolecular events at discrete time points via synthetic chemistry with their real-time visualization in native cells. In the present study, we reported two peptide sequences that undergo visible light-induced molecular and supramolecular transformations to form various assembly species in cells. In contrast to endogenous stimulus-responsive assembly, the proposed photochemistry enables full control over the photolysis reaction where the monomer generation and local concentration regulate the subsequent assembly kinetics. Phasor-fluorescence lifetime imaging traced the formation of various assembly states in cells associated with monomer activation and consumption, whereas correlative light-electron microscopy revealed the intracellular nanofibres formed. The temporally resolved assembly process shows that the emergence of cytotoxicity correlates with the accumulation of oligomers beyond the cellular efflux threshold.
Segment Anything for Microscopy
Accurate segmentation of objects in microscopy images remains a bottleneck for many researchers despite the number of tools developed for this purpose. Here, we present Segment Anything for Microscopy (μSAM), a tool for segmentation and tracking in multidimensional microscopy data. It is based on Segment Anything, a vision foundation model for image segmentation. We extend it by fine-tuning generalist models for light and electron microscopy that clearly improve segmentation quality for a wide range of imaging conditions. We also implement interactive and automatic segmentation in a napari plugin that can speed up diverse segmentation tasks and provides a unified solution for microscopy annotation across different microscopy modalities. Our work constitutes the application of vision foundation models in microscopy, laying the groundwork for solving image analysis tasks in this domain with a small set of powerful deep learning models.
Observation of non-Hermitian topological synchronization
Non-Hermitian topology plays a pivotal role in physical science and technology, exerting a profound impact across various scientific disciplines. Recently, the interplay between topological physics and nonlinear synchronization has aroused a great interest, leading to the emergence of an intriguing phenomenon known as topological synchronization, wherein nonlinear oscillators at boundaries synchronize through topological boundary states. To the best of our knowledge, however, this phenomenon has yet to be experimentally validated, and the study of non-Hermitian topological synchronization remains in its infancy. Here, we investigate non-Hermitian topological synchronization, uncovering the influence of system size and boundary site geometry on synchronization effects. We demonstrate that simply varying the lattice size allows transitions between three distinct types of non-Hermitian topological synchronization. Furthermore, we reveal that the geometry of the boundary sites introduces a degree of freedom, enabling the control over the configuration of non-Hermitian topological synchronization. These findings are experimentally validated using non-Hermitian nonlinear topological circuits. This work significantly broadens the scope of nonlinear non-Hermitian topological physics and opens new avenues for the application of synchronization phenomena in future technologies.
Responsive DNA artificial cells for contact and behavior regulation of mammalian cells
Artificial cells have emerged as synthetic entities designed to mimic the functionalities of natural cells, but their interactive ability with mammalian cells remains challenging. Herein, we develop a generalizable and modular strategy to engineer DNA-empowered stimulable artificial cells designated to regulate mammalian cells (STARM) via synthetic contact-dependent communication. Constructed through temperature-controlled DNA self-assembly involving liquid-liquid phase separation (LLPS), STARMs feature organized all-DNA cytoplasm-mimic and membrane-mimic compartments. These compartments can integrate functional nucleic acid (FNA) modules and light-responsive gold nanorods (AuNRs) to establish a programmable sense-and-respond mechanism to specific stimuli, such as light or ions, orchestrating diverse biological functions, including tissue formation and cellular signaling. By combining two designer STARMs into a dual-channel system, we achieve orthogonally regulated cellular signaling in multicellular communities. Ultimately, the in vivo therapeutic efficacy of STARM in light-guided muscle regeneration in living animals demonstrates the promising potential of smart artificial cells in regenerative medicine.
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